B_c Meson Production in Nuclear Collisions at RHIC

We study quantitatively the formation and evolution of B_c bound states in a space-time domain of deconfined quarks and gluons (quark-gluon plasma, QGP). At the Relativistic Heavy Ion Collider (RHIC) one expects for the first time that typical central collisions will result in multiple pairs of heavy (in this case charmed) quarks. This provides a new mechanism for the formation of heavy quarkonia which depends on the properties of the deconfined region. We find typical enhancements of about 500 fold for the B_c production yields over expectations from the elementary coherent hadronic B_c-meson production scenario. The final population of bound states may serve as a probe of the plasma phase parameters.Comment: 9 Pages, 11 Postscript Figure

Model-Assisted Forest Yield Estimation with Light Detection and Ranging

Previous studies have demonstrated that light detection and ranging (LiDAR)-derived variables can be used to model forest yield variables, such as biomass, volume, and number of stems. However, the next step is underrepresented in the literature: estimation of forest yield with appropriate confidence intervals. It is of great importance that the procedures required for conducting forest inventory with LiDAR and the estimation precision of such procedures are sufficiently documented to enable their evaluation and implementation by land managers. In this study, we demonstrated the regression estimator, a model-assisted estimator (approximately design-unbiased), using LiDAR-derived variables for estimation of total forest yield. The LiDAR-derived variables are statistics associated with vegetation height and cover. The estimation procedure requires complete coverage of the forest with LiDAR and a random sample of precisely georeferenced field measurement plots. Regression estimation relies on sample-based ordinary least squares (OLS) regression models relating forest yield and LiDAR-derived variables. Estimation was performed using the OLS models and LiDAR-derived variables for the entire population. Regression estimates of basal area, volume, stand density, and biomass were much more precise than simple random sampling estimates (design effects were 0.25, 0.24, 0.44, and 0.27, respectively).Keywords: Model-assisted, Regression estimation, Design-based LiDAR, Forest Inventor

Influence of lidar, Landsat imagery, disturbance history, plot location accuracy, and plot size on accuracy of imputation maps of forest composition and structure

This study investigated how lidar-derived vegetation indices, disturbance history from Landsat time series (LTS) imagery, plot location accuracy, and plot size influenced accuracy of statistical spatial models (nearest-neighbor imputation maps) of forest vegetation composition and structure. Nearest-neighbor (NN) imputation maps were developed for 539,000 ha in the central Oregon Cascades, USA. Mapped explanatory data included tasseled-cap indices and disturbance history metrics (year, magnitude, and duration of disturbance) from LTS imagery, lidar-derived vegetation metrics, climate, topography, and soil parent material. Vegetation data from USDA Forest Service forest inventory plots was summarized at two plot sizes (plot and subplot) and geographically located with two levels of accuracy (standard and improved). Maps of vegetation composition and structure were developed with the Gradient Nearest Neighbor (GNN) method of NN imputation using different combinations of explanatory variables, plot spatial resolution, and plot positional accuracy. Lidar vegetation indices greatly improved predictions of live tree structure, moderately improved predictions of snag density and down wood volume, but did not consistently improve species predictions. LTS disturbance metrics improved predictions of forest structure, but not to the degree of lidar indices, while also improving predictions of many species. Absence of disturbance attribution (i.e. disturbance type such as fire or timber harvest) in LTS disturbance metrics may have limited our ability to predict forest structure. Absence of corrected lidar intensity values may also have lowered accuracy of snag and species predictions. However, LTS disturbance attribution and lidar corrected intensity values may not be able to overcome fundamental limitations of remote sensing for predicting snags and down wood that are obscured by the forest canopy. Improved GPS plot locations had little influence on map accuracy, and we suggest under what conditions improved GPS plot locations may or may not improve the accuracy of predictive maps that link remote sensing with forest inventory plots. Subplot NN imputation maps had much lower accuracy compared to maps generated using response variables from larger whole plots. No single map had optimal results for every mapped variable, suggesting map users and developers need to prioritize what forest vegetation attributes are most important for any given map application.Keywords: Lidar, Landsat time series, Disturbance, Nearest-neighbor imputation, Forest composition and structur

1967: Abilene Christian College Bible Lectures - Full Text

LIFTING UP THE CHRIST” Being the Abilene Christian College Annual Bible Lectures 1967 $3.95 Published by ABILENE CHRISTIAN COLLEGE STUDENTS EXCHANGE ACC Station Abilene, Texa

1965: Abilene Christian College Bible Lectures - Full Text

LIFT UP YOUR EYES” Being the Abilene Christian College Annual Bible Lectures 1965 Price: $3.95 Published by ABILENE CHRISTIAN COLLEGE STUDENTS EXCHANGE ACC Station Abilene. Texa

Induction of Antibodies in Rhesus Macaques That Recognize a Fusion-Intermediate Conformation of HIV-1 gp41

A component to the problem of inducing broad neutralizing HIV-1 gp41 membrane proximal external region (MPER) antibodies is the need to focus the antibody response to the transiently exposed MPER pre-hairpin intermediate neutralization epitope. Here we describe a HIV-1 envelope (Env) gp140 oligomer prime followed by MPER peptide-liposomes boost strategy for eliciting serum antibody responses in rhesus macaques that bind to a gp41 fusion intermediate protein. This Env-liposome immunization strategy induced antibodies to the 2F5 neutralizing epitope 664DKW residues, and these antibodies preferentially bound to a gp41 fusion intermediate construct as well as to MPER scaffolds stabilized in the 2F5-bound conformation. However, no serum lipid binding activity was observed nor was serum neutralizing activity for HIV-1 pseudoviruses present. Nonetheless, the Env-liposome prime-boost immunization strategy induced antibodies that recognized a gp41 fusion intermediate protein and was successful in focusing the antibody response to the desired epitope

Inducing Cross-Clade Neutralizing Antibodies against HIV-1 by Immunofocusing

Background: Although vaccines are important in preventing viral infections by inducing neutralizing antibodies (nAbs), HIV-1 has proven to be a difficult target and escapes humoral immunity through various mechanisms. We sought to test whether HIV-1 Env mimics may serve as immunogens. Methodology/Principal Findings: Using random peptide phage display libraries, we identified the epitopes recognized by polyclonal antibodies of a rhesus monkey that had developed high-titer, broadly reactive nAbs after infection with a simianhuman immunodeficiency virus (SHIV) encoding env of a recently transmitted HIV-1 clade C (HIV-C). Phage peptide inserts were analyzed for conformational and linear homology using computational analysis; some peptides mimicked various domains of the original HIV-C Env, such as conformational V3 loop epitopes and the conserved linear region of the gp120 C-terminus. Next, we devised a novel prime/boost strategy to test the immunogenicity of such phage-displayed peptides and primed mice only once with HIV-C gp160 DNA followed by boosting with mixtures of recombinant phages. Conclusions/Significance: This strategy, which was designed to focus the immune system on a few Env epitopes (immunofocusing), not only induced HIV-C gp160 binding antibodies and cross-clade nAbs, but also linked a conserved HIV Env region for the first time to the induction of nAbs: the C-terminus of gp120. The identification of conserved antige