The Anatomy of the Knee and Gamma-Families

It is shown that the fine stucture of the cosmic ray energy spectrum in the knee region, if explained by the Single Source Model (SSM), can, in principle, be clearly revealed and magnified in the size spectrum of extensive air showers (EAS) associated with gamma families. Existing experimental data on EAS at mountain level give support to this hypothesis.Comment: 4 pages, 3 figures, to appear in the Proceedings of 14th International Symposium on Very High Energy Cosmic Ray Interactions, Weihai, China, 15-22.08.06, Nucl.Phys.B (Proc.Suppl.), 200

Quantifying Eulerian Eddy Leakiness in an Idealized Model

An idealized eddy‐resolving ocean basin, closely resembling the North Pacific Ocean, is simulated using MITgcm. We identify rotationally coherent Lagrangian vortices (RCLVs) and sea surface height (SSH) eddies based on the Lagrangian and Eulerian framework, respectively. General statistical results show that RCLVs have a much smaller coherent core than SSH eddies with the ratio of radius is about 0.5. RCLVs are often enclosed by SSH anomaly contours, but SSH eddy identification method fails to detect more than half of RCLVs. Based on their locations, two types of eddies are classified into three categories: overlapping RCLVs and SSH eddies, nonoverlapping SSH eddies, and nonoverlapping RCLVs. Using Lagrangian particles, we examine the processes of leakage and intrusion around SSH eddies. For overlapping SSH eddies, over the lifetime, the material coherent core only accounts for about 25% and about 50% of initial water leak from eddy interior. The remaining 25% of water can still remain inside the boundary, but only in the form of filaments outside the coherent core. For nonoverlapping SSH eddies, more water leakage (about 60%) occurs at a faster rate. Guided by the number and radius of SSH eddies, fixed circles and moving circles are randomly selected to diagnose the material flux around these circles. We find that the leakage and intrusion trends of moving circles are quite similar to that of nonoverlapping SSH eddies, suggesting that the material coherence properties of nonoverlapping SSH eddies are not significantly different from random pieces of ocean with the same size

What does perturbative QCD really have to say about neutron stars

The implications of perturbative QCD (PQCD) calculations on neutron stars are carefully examined. While PQCD calculations above baryon chemical potential $\mu_B\sim2.4$ GeV demonstrate the potential of ruling out a wide range of neutron star equations of state (EOSs), these types of constraints only affect the most massive neutron stars in the vicinity of the Tolman-Oppenheimer-Volkoff (TOV) limit, resulting in bounds on neutron star EOSs that are orthogonal to those from current or future astrophysical observations, even if observations near the TOV limit are made. Assuming the most constraining scenario, PQCD considerations favor low values of the speed of sound squared $C_s$ at high $\mu_B$ relevant for heavy neutron stars, but leave predictions for the radii and tidal deformabilities almost unchanged for all the masses. Such considerations become irrelevant if the maximum speed of sound squared inside neutron stars does not exceed about $C_{s,\mathrm{max}}\sim0.5$, or if the matching to PQCD is performed above $\mu_B\simeq2.9$ GeV. Furthermore, the large uncertainties associated with the current PQCD predictions make it impossible to place any meaningful bounds on neutron star EOSs as of now. Interestingly, if PQCD predictions for pressure at around $\mu_B\simeq2.4$ GeV is refined and found to be low ($\lesssim 1.5$ GeV/fm$^3$), evidence for a soft neutron star inner core EOS would point to the presence of a strongly interacting phase dominated by non-perturbative physics beyond neutron star densities.Comment: 15 pages, 11 figure

Consistency of differentially expressed gene rankings based on subsets of microarray data.

Data derived from gene expression microarrays are frequently used to identify candidate genes which can characterize and distinguish between two biological phenotypes. A key step in this process is the selection of an appropriate test statistic to identify which genes are differentially expressed between the two tissues. Although many methods have been explicitly developed for this purpose, the traditional (-test still remains a popular choice. In this study, we evaluate the empirical impact of choice of test-statistic on the resulting list of differentially expressed genes, in particular when the available sample size is small. We evaluated several different methods for detecting differentially expressed genes (t-test, empirical Bayes, and SAM) using ten different publicly available data sets. First, we obtained gene lists based on the full data using the different methods. Then, we selected subsamples from the full data, and obtained gene lists based on these subsamples. The consistency was quantified using several scores. Factors evaluated in the empirical study included the size of the subset and the length of the differentially expressed gene list. We found that when the sample size of the subset is small, the resulting gene list based on the t-test has a very low consistency, while empirical Bayes and SAM have much higher consistencies. This result is particularly evident when considering only the top ranked genes. When sample sizes are larger, all three methods have the same performance. We recommend that investigators use these moderated versions in lieu of the t-test when the sample size is small

Integrated analysis of miRNA/mRNA expression and gene methylation using sparse canonical correlation analysis.

MicroRNAs (miRNAs) are a large number of small endogenous non-coding RNA molecules (18-25 nucleotides in length) which regulate expression of genes post-transcriptionally. While a variety of algorithms exist for determining the targets of miRNAs, they are generally based on sequence information and frequently produce lists consisting of thousands of genes. Canonical correlation analysis (CCA) is a multivariate statistical method that can be used to find linear relationships between two data sets, and here we apply CCA to find the linear combination of differentially expressed miRNAs and their corresponding target genes having maximal negative correlation. Due to the high dimensionality, sparse CCA is used to constrain the problem and obtain a solution. A novel gene set enrichment analysis statistic is proposed based on the sparse CCA results for estimating the significance of predefined gene sets. The methods are illustrated with both a simulation study and real miRNA-mRNA expression data. DNA methylation is a process of adding a methyl group to DNA by a group of enzymes collectively known as DNA methyltransferases which is an epigenetic modification critical to normal genome regulation and development. In order to understand the role of DNA methylation in gene differentiation, we analyze genome-scale DNA methylation patterns and gene expression data using sparse CCA to find linear combinations between the two data sets which have maximal negative correlation. In a similar spirit to the miRNA-mRNA study, we create a GSEA statistic with weight vectors from the sparse CCA method and assess the significance of predefined gene sets. The method is exemplified with real gene expression / DNA methylation data regarding the development of the embryonic murine palate

Kindling Watch-Fires: Being a Brief Sketch of the Life of Rev. Vivian A. Dake

https://place.asburyseminary.edu/freemethodistbooks/1010/thumbnail.jp

A study of histological changes in corn leaves under stress with an investigation of their photographic densityusing infrared film

Hickory King corn was germinated in sand and then supplied nutrients using Hoagland\u27s solutions. When the corn plants reached the three-leaf stage, four kinds of stress were induced in separate pots in order to study their photographic density using infrared film as it related to the internal structure of the leaves. The four stresses used in this study were: disease caused by maize dwarf mosaic virus, manganese toxicity, nitrogen deficiency, and water deficiency. Leaves from the four stress conditions and from control plants were examined microscopically to determine what anatomical anomalies could be found to explain their photographic densities as imaged on infrared film. Photographs were made with a Pentax single lens reflex 35 mm camera using Kodak E-4 Ektachrome infrared film. Batch 36128-UQ, and a Tiffen 12 filter over the lens. Photographs were evaluated using a Macbeth Quantalog Transmission Densitometer, Model TD 404. Sections were cut from leaves immediately after photographing and fixed in FAA. These sections were then dehydrated in TBA and sectioned in paraffin. Sections were stained in Safranin-0 and Fast Green and evaluated for anatomical changes. Results of this study showed that photographic density increased with increasing leaf thickness when a red densitometer filter was used. Gross morphology of the corn leaves was evaluated qualitatively with respect to the several theories of light reflectance from leaves. Parameters considered in morphological evaluations included; number and size of vacuoles in parenchymal tissue; presence of air spaces in the mesophyll; size, number, and shape of mesophyll cells; size of air pockets under stomata; number of chloroplasts; size and shape changes in bulliform cells; and the amount of protoplasm in mesophyll cells