How Well Do We Know the Beta-Decay of 16N and Oxygen Formation in Helium Burning

We review the status of the 12C(a,g)16O reaction rate, of importance for stellar processes in a progenitor star prior to a super-nova collapse. Several attempts to constrain the p-wave S-factor of the 12C(a,g)16O reaction at Helium burning temperatures (200 MK) using the beta-delayed alpha-particle emission of 16N have been made, and it is claimed that this S-factor is known, as quoted by the TRIUMF collaboration. In contrast reanalyses (by G.M. hale) of all thus far available data (including the 16N data) does not rule out a small S-factor solution. Furthermore, we improved our previous Yale-UConn study of the beta- delayed alpha-particle emission of \n16 by improving our statistical sample (by more than a factor of 5), improving the energy resolution of the experiment (by 20%), and in understanding our line shape, deduced from measured quantities. Our newly measured spectrum of the beta-delayed alpha-particle emission of 16N is not consistent with the TRIUMF('94) data, but is consistent with the Seattle('95) data, as well as the earlier (unaltered !) data of Mainz('71). The implication of this discrepancies for the extracted astrophysical p-wave s-factor is briefly discussed.Comment: 6 pages, 4 figures, Invited Talk, Physics With Radioactive Beams, Puri, India, Jan. 12-17, 1998, Work Supported by USDOE Grant No. DE-FG02-94ER4087

Graph Dynamical Networks for Unsupervised Learning of Atomic Scale Dynamics in Materials

Understanding the dynamical processes that govern the performance of functional materials is essential for the design of next generation materials to tackle global energy and environmental challenges. Many of these processes involve the dynamics of individual atoms or small molecules in condensed phases, e.g. lithium ions in electrolytes, water molecules in membranes, molten atoms at interfaces, etc., which are difficult to understand due to the complexity of local environments. In this work, we develop graph dynamical networks, an unsupervised learning approach for understanding atomic scale dynamics in arbitrary phases and environments from molecular dynamics simulations. We show that important dynamical information can be learned for various multi-component amorphous material systems, which is difficult to obtain otherwise. With the large amounts of molecular dynamics data generated everyday in nearly every aspect of materials design, this approach provides a broadly useful, automated tool to understand atomic scale dynamics in material systems.Comment: 25 + 7 pages, 5 + 3 figure

Securing field learning using a twenty-first century Cook's Tour

This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Geography in Higher Education on 22/01/2015, available online: http://wwww.tandfonline.com/http://dx.doi.org/10.1080/03098265.2014.1003801This paper evaluates the effectiveness of incorporating digital video into a traditional Cook’s Tour as part of a 7-day road trip around the east coast of New Zealand’s North Island over a 4-year period

The elaborate interplay of natural killer cells and vaccinia virus

Vaccinia virus (VACV) is a poxvirus and is the vaccine used to eradicate smallpox. It is also an expression vector for heterologous antigens and an oncolytic virus for cancer therapy. VACV encodes multiple proteins that aid evasion of the host immune response. There is, however, an incomplete understanding of how this immune suppression by VACV is consistent with such a strong immune response and subsequent memory. There is especially little known about the relationship between natural killer (NK) cells and VACV. Previous studies showed that during VACV infection, NK cells proliferate, are activated, limit viral replication, kill VACV-infected cells and display memory-like qualities. However, how NK cells recognise and interact with VACV-infected cells, which ligand(s) trigger NK cell activation, which NK receptors (NKR) are involved, and whether VACV uses strategies to interfere with the NK cell response remains elusive. This thesis aimed to address such questions using screening methods in parallel to candidate-based approach to tackle the challenges caused by the high diversity of NKRs and NK ligands. First, the responsiveness of murine NK cells to systemic VACV infection was studied ex vivo. Transcriptomic analysis, along with validation at the protein level, indicated NK cell activation and preparedness to mediate effector functions. Analysis of NK cell transcriptomic signature indicated that the stimuli triggering NK cell activation in the context of VACV infection correspond primarily with direct cell recognition but also cytokines such as Il-12 and -18, and IFNs. NKRs expression level in response to VACV was investigated, both at the transcript and protein level, and candidate NKRs involved specifically in the response to VACV were defined. Using a published dataset, the human and murine NK cell response to VACV was compared, revealing strong similarities. Second, the modulation of the plasma membrane (PM) proteome after VACV infection was studied using a proteomic screen that allowed to i) determine how VACV affects NK ligands expression; ii) give insights into VACV host surface protein modulation mechanism; iii) highlight previously unrecognised VACV strategies to evade NK cell response, iv) establish for the first time, a comprehensive analysis of VACV proteins expressed at the host PM and, v) suggest VACV surface proteins that potentially engage with NK cells. Third, the impact of the absence of VACV A56, an NK ligand candidate, and the murine natural cytotoxicity receptor (NCR) NKp46, were studied, in vitro and in vivo, in the context of VACV infection. This confirmed that VACV A56 prevents cell fusion, anchors VACV K2 and VCP (virus complement control protein) at the cell surface and enhances the binding of human and murine NCRs to VACV-infected cells. Further, it revealed that A56 deletion did not affect plaque size or EEV (extracellular enveloped virus) release, did not alter NK ligands surface expression, but led to decreased VACV-infected cells killing by murine NK cells. Lastly, the impact of VACV A56 and NKp46 deletion, on VACV infection outcome were assessed in vivo, in the acute and the memory stage and did not reveal substantial differences. Collectively, these data constitute a valuable resource concerning the interaction of VACV with NK cells and the factors influencing their interplay. These data can contribute to improve the development of VACV-based vaccines vectors and oncolytic viruses, and further our understanding of host-pathogen interactions

Tracer Measurements in Growing Sea Ice Support Convective Gravity Drainage Parameterizations

Gravity drainage is the dominant process redistributing solutes in growing sea ice. Modeling gravity drainage is therefore necessary to predict physical and biogeochemical variables in sea ice. We evaluate seven gravity drainage parameterizations, spanning the range of approaches in the literature, using tracer measurements in a sea ice growth experiment. Artificial sea ice is grown to around 17 cm thickness in a new experimental facility, the Roland von Glasow air‐sea‐ice chamber. We use NaCl (present in the water initially) and rhodamine (injected into the water after 10 cm of sea ice growth) as independent tracers of brine dynamics. We measure vertical profiles of bulk salinity in situ, as well as bulk salinity and rhodamine in discrete samples taken at the end of the experiment. Convective parameterizations that diagnose gravity drainage using Rayleigh numbers outperform a simpler convective parameterization and diffusive parameterizations when compared to observations. This study is the first to numerically model solutes decoupled from salinity using convective gravity drainage parameterizations. Our results show that (1) convective, Rayleigh number‐based parameterizations are our most accurate and precise tool for predicting sea ice bulk salinity; and (2) these parameterizations can be generalized to brine dynamics parameterizations, and hence can predict the dynamics of any solute in growing sea ic

Transmission System and Rural Electrification Scheme in Nigeria: Issues, Challenges, Constraints and Way forward

This paper x-rayed the transmission system and rural electrification scheme in Nigeria. The electric power transmission network and rural electrification scheme were critically reviewed in terms of issues, challenges, constraints, roles and current state of the power systems to identify their areas of strength and shortcomings in the Nigeria power sector. The paper further proposes the way forward to enhance the performance of the Nigeria’s electric power transmission system and rural electrification scheme