The interaction of fast neutrons with shielding and fusion blanket materials

In the present work the neutron emission spectra from a graphite cube, and from natural uranium, lithium fluoride, graphite, lead and steel slabs bombarded with 14.1 MeV neutrons were measured to test nuclear data and calculational methods for D - T fusion reactor neutronics. The neutron spectra measured were performed by an organic scintillator using a pulse shape discrimination technique based on a charge comparison method to reject the gamma rays counts. A computer programme was used to analyse the experimental data by the differentiation unfolding method. The 14.1 MeV neutron source was obtained from T(d,n)4He reaction by the bombardment of T - Ti target with a deuteron beam of energy 130 KeV. The total neutron yield was monitored by the associated particle method using a silicon surface barrier detector. The numerical calculations were performed using the one-dimensional discrete-ordinate neutron transport code ANISN with the ZZ-FEWG 1/ 31-1F cross section library. A computer programme based on Gaussian smoothing function was used to smooth the calculated data and to match the experimental data. There was general agreement between measured and calculated spectra for the range of materials studied. The ANISN calculations carried out with P3 - S8 calculations together with representation of the slab assemblies by a hollow sphere with no reflection at the internal boundary were adequate to model the experimental data and hence it appears that the cross section set is satisfactory and for the materials tested needs no modification in the range 14.1 MeV to 2 MeV. Also it would be possible to carry out a study on fusion reactor blankets, using cylindrical geometry and including a series of concentric cylindrical shells to represent the torus wall, possible neutron converter and breeder regions, and reflector and shielding regions.

Nuclear magnetic resonance studies of molecular interactions and structures

This thesis is concerned with the investigation, by nuclear magnetic resonance spectroscopy, of the molecular interactions occurring in mixtures of benzene and cyclohexane to which either chloroform or deutero-chloroform has been added. The effect of the added polar molecule on the liquid structure has been studied using spin-lattice relaxation time, 1H chemical shift, and nuclear Overhauser effect measurements. The main purpose of the work has been to validate a model for molecular interaction involving local ordering of benzene around chloroform. A chemical method for removing dissolved oxygen from samples has been developed to encompass a number of types of sample, including quantitative mixtures, and its supremacy over conventional deoxygenation technique is shown. A set of spectrometer conditions, the use of which produces the minimal variation in peak height in the steady state, is presented. To separate the general diluting effects of deutero-chloroform from its effects due to the production of local order a series of mixtures involving carbon tetrachloride, instead of deutero-chloroform, have been used as non-interacting references. The effect of molecular interaction is shown to be explainable using a solvation model, whilst an approach involving 1:1 complex formation is shown not to account for the observations. It is calculated that each solvation shell, based on deutero-chloroform, contains about twelve molecules of benzene or cyclohexane. The equations produced to account for the T1 variations have been adapted to account for the 1H chemical shift variations in the same system. The shift measurements are shown to substantiate the solvent cage model with a cage capacity of twelve molecules around each chloroform molecule. Nuclear Overhauser effect data have been analysed quantitatively in a manner consistent with the solvation model. The results show that discrete shells only exist when the mole fraction of deutero-chloroform is below about 0.08.

Hypercapnia induces cleavage and nuclear localization of RelB protein, giving insight into CO2 sensing and signaling

Carbon dioxide (CO(2)) is increasingly being appreciated as an intracellular signaling molecule that affects inflammatory and immune responses. Elevated arterial CO(2) (hypercapnia) is encountered in a range of clinical conditions, including chronic obstructive pulmonary disease, and as a consequence of therapeutic ventilation in acute respiratory distress syndrome. In patients suffering from this syndrome, therapeutic hypoventilation strategy designed to reduce mechanical damage to the lungs is accompanied by systemic hypercapnia and associated acidosis, which are associated with improved patient outcome. However, the molecular mechanisms underlying the beneficial effects of hypercapnia and the relative contribution of elevated CO(2) or associated acidosis to this response remain poorly understood. Recently, a role for the non-canonical NF-?B pathway has been postulated to be important in signaling the cellular transcriptional response to CO(2). In this study, we demonstrate that in cells exposed to elevated CO(2), the NF-?B family member RelB was cleaved to a lower molecular weight form and translocated to the nucleus in both mouse embryonic fibroblasts and human pulmonary epithelial cells (A549). Furthermore, elevated nuclear RelB was observed in vivo and correlated with hypercapnia-induced protection against LPS-induced lung injury. Hypercapnia-induced RelB processing was sensitive to proteasomal inhibition by MG-132 but was independent of the activity of glycogen synthase kinase 3ß or MALT-1, both of which have been previously shown to mediate RelB processing. Taken together, these data demonstrate that RelB is a CO(2)-sensitive NF-?B family member that may contribute to the beneficial effects of hypercapnia in inflammatory diseases of the lung.

Semisupervised learning of hierarchical latent trait models for data visualization

Recently, we have developed the hierarchical Generative Topographic Mapping (HGTM), an interactive method for visualization of large high-dimensional real-valued data sets. In this paper, we propose a more general visualization system by extending HGTM in three ways, which allows the user to visualize a wider range of data sets and better support the model development process. 1) We integrate HGTM with noise models from the exponential family of distributions. The basic building block is the Latent Trait Model (LTM). This enables us to visualize data of inherently discrete nature, e.g., collections of documents, in a hierarchical manner. 2) We give the user a choice of initializing the child plots of the current plot in either interactive, or automatic mode. In the interactive mode, the user selects "regions of interest," whereas in the automatic mode, an unsupervised minimum message length (MML)-inspired construction of a mixture of LTMs is employed. The unsupervised construction is particularly useful when high-level plots are covered with dense clusters of highly overlapping data projections, making it difficult to use the interactive mode. Such a situation often arises when visualizing large data sets. 3) We derive general formulas for magnification factors in latent trait models. Magnification factors are a useful tool to improve our understanding of the visualization plots, since they can highlight the boundaries between data clusters. We illustrate our approach on a toy example and evaluate it on three more complex real data sets. © 2005 IEEE.