Investigating High-Energy Proton-Induced Reactions on Spherical Nuclei: Implications for the Pre-Equilibrium Exciton Model

A number of accelerator-based isotope production facilities utilize 100- to 200-MeV proton beams due to the high production rates enabled by high-intensity beam capabilities and the greater diversity of isotope production brought on by the long range of high-energy protons. However, nuclear reaction modeling at these energies can be challenging because of the interplay between different reaction modes and a lack of existing guiding cross section data. A Tri-lab collaboration has been formed among the Lawrence Berkeley, Los Alamos, and Brookhaven National Laboratories to address these complexities by characterizing charged-particle nuclear reactions relevant to the production of established and novel radioisotopes. In the inaugural collaboration experiments, stacked-targets of niobium foils were irradiated at the Brookhaven Linac Isotope Producer (E$_p$=200 MeV) and the Los Alamos Isotope Production Facility (E$_p$=100 MeV) to measure $^{93}$Nb(p,x) cross sections between 50 and 200 MeV. The measured cross-section results were compared with literature data as well as the default calculations of the nuclear model codes TALYS, CoH, EMPIRE, and ALICE. We developed a standardized procedure that determines the reaction model parameters that best reproduce the most prominent reaction channels in a physically justifiable manner. The primary focus of the procedure was to determine the best parametrization for the pre-equilibrium two-component exciton model. This modeling study revealed a trend toward a relative decrease for internal transition rates at intermediate proton energies (E$_p$=20-60 MeV) in the current exciton model as compared to the default values. The results of this work are instrumental for the planning, execution, and analysis essential to isotope production.Comment: 37 pages, 62 figures. Revised version, published in Physical Review

Tandem fusion of hepatitis B core antigen allows assembly of virus-like particles in bacteria and plants with enhanced capacity to accommodate foreign proteins

The core protein of the hepatitis B virus, HBcAg, assembles into highly immunogenic viruslike particles (HBc VLPs) when expressed in a variety of heterologous systems. Specifically, the major insertion region (MIR) on the HBcAg protein allows the insertion of foreign sequences, which are then exposed on the tips of surface spike structures on the outside of the assembled particle. Here, we present a novel strategy which aids the display of whole proteins on the surface of HBc particles. This strategy, named tandem core, is based on the production of the HBcAg dimer as a single polypeptide chain by tandem fusion of two HBcAg open reading frames. This allows the insertion of large heterologous sequences in only one of the two MIRs in each spike, without compromising VLP formation. We present the use of tandem core technology in both plant and bacterial expression systems. The results show that tandem core particles can be produced with unmodified MIRs, or with one MIR in each tandem dimer modified to contain the entire sequence of GFP or of a camelid nanobody. Both inserted proteins are correctly folded and the nanobody fused to the surface of the tandem core particle (which we name tandibody) retains the ability to bind to its cognate antigen. This technology paves the way for the display of natively folded proteins on the surface of HBc particles either through direct fusion or through non-covalent attachment via a nanobody

Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies

Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some romantic relationships thrive more than others. This large-scale project used machine learning (i.e., Random Forests) to 1) quantify the extent to which relationship quality is predictable and 2) identify which constructs reliably predict relationship quality. Across 43 dyadic longitudinal datasets from 29 laboratories, the top relationship-specific predictors of relationship quality were perceived-partner commitment, appreciation, sexual satisfaction, perceived-partner satisfaction, and conflict. The top individual-difference predictors were life satisfaction, negative affect, depression, attachment avoidance, and attachment anxiety. Overall, relationship-specific variables predicted up to 45% of variance at baseline, and up to 18% of variance at the end of each study. Individual differences also performed well (21% and 12%, respectively). Actor-reported variables (i.e., own relationship-specific and individual-difference variables) predicted two to four times more variance than partner-reported variables (i.e., the partner’s ratings on those variables). Importantly, individual differences and partner reports had no predictive effects beyond actor-reported relationship-specific variables alone. These findings imply that the sum of all individual differences and partner experiences exert their influence on relationship quality via a person’s own relationship-specific experiences, and effects due to moderation by individual differences and moderation by partner-reports may be quite small. Finally, relationship-quality change (i.e., increases or decreases in relationship quality over the course of a study) was largely unpredictable from any combination of self-report variables. This collective effort should guide future models of relationships

Micelle Formation and Surface Interactions in Supercritical CO2. Fundamental Studies for the Extraction of Actinides from Contaminated Surfaces.

We are examining the potential of water in CO2 microemulsions as a new medium for the extraction of metal ions from contaminated surfaces with the ultimate goal of extracting actinides from heterogeneous waste to aid in decontamination and waste reduction

Micelle Formation and Surface Interactions in Supercritical CO2. Fundamental Studies for the Extraction of Actinides from Contaminated Surfaces.

The goals of this research program included: (1) Study solubility of extractants and formation of micelles--(a) Do surfactants form micelles in scCO{sub 2} and what is the mechanism of their formation? (b) Can the pressure/density of scCO{sub 2} be used to alter surfactant solubility or micelle structure? (c) Can surfactant micelles be used to transport water based microphases? (2) Examine the solubilization of metals--(a) What influence does metal binding have on the surfactant solubility or micelle structure? (b) What is the selectivity of metal binding in promising systems? (c) Are all solubilized metals bound to surfactant ligands or is an entire aqueous micro-environment solubilized by the surfactant/micelle? (d) Can metal species, as charged ions or neutral complexes, be insulated by fluorinated surfactants to enhance solubility in scCO{sub 2}? (3) Explore surface interactions with the matrix and mobility of micelles.--(a) What factors affect wetting of heterogeneous matrices (i.e., ligand type, CO{sub 2} pressure); (b) How deep can surfactants penetrate materials such as concrete? (4) Explore surface interactions with the actinide contaminant--(a) Can surfactant based micelles be used to deliver acidic, aqueous microphases to the actinide surface? (5) Evaluate these new systems for metal extraction from a model contaminated surface containing radionuclides or surrogate metals--(a) What is the rate of extraction? (b) What ratio of ligand to metal is required