Spatial characterization of salt accumulation in early stage limestone weathering using probe permeametry

This research characterizes the weathering of natural building stone using an unsteady-state portable probe permeameter. Variations between the permeability properties of fresh rock and the same rocks after the early stages of a salt weathering simulation are used to examine the effects of salt accumulation on spatial variations in surface rock permeability properties in two limestones from Spain. The Fraga and Tudela limestones are from the Ebro basin and are of Miocene age. Both stone types figure largely in the architectural heritage of Spain and, in common with many other building limestones, they are prone to physical damage from salt crystallization in pore spaces. To examine feedbacks associated with salt accumulation during the early stages of this weathering process, samples of the two stone types were subjected to simulated salt weathering under laboratory conditions using magnesium sulphate and sodium chloride at concentrations of 5% and 15%. Permeability mapping and statistical analysis (aspatial statistics and spatial prediction) before and after salt accumulation are used to assess changes in the spatial variability of permeability and to correlate these changes with salt movement, porosity change, potential rock deterioration and textural characteristics. Statistical analyses of small-scale permeability measurements are used to evaluate the drivers for decay and hence aid the prediction of the weathering behaviour of the two limestones.

Screens, Closets, and Echo-Chambers of the Mind: The Struggle to Represent the Inner Life on Stage

Screens, Closets, and Echo-Chambers of the Mind: The Struggle to Represent the Inner Life on Stage

The early-stage risk capital market in Scotland since 2000: issues of scale, characteristics and market efficiency

In this paper we provide a detailed profile and analysis of the regional risk capital market in Scotland, using an innovative methodology and specially developed databases which cover risk capital investment in young companies in the periods 2000–04 and 2005–07. This identifies the investment activity of all actors in the market and provides estimates of the total flow of risk capital investment into early-stage Scottish companies over the period. The paper concludes by drawing out the implications for policy makers (providing a more robust evidence base for the development, implementation and monitoring of policy) and for academic researchers (on the methodologies for estimating market scale and efficiency).

Locally regularised two-stage learning algorithm for RBF network centre selection

Nonlinear models constructed from radial basis function (RBF) networks can easily be over-fitted due to the noise on the data. While information criteria, such as the final prediction error (FPE), can provide a trade-off between training error and network complexity, the tunable parameters that penalise a large size of network model are hard to determine and are usually network dependent. This article introduces a new locally regularised, two-stage stepwise construction algorithm for RBF networks. The main objective is to produce a parsomous network that generalises well over unseen data. This is achieved by utilising Bayesian learning within a two-stage stepwise construction procedure to penalise centres that are mainly interpreted by the noise.

Gene Expression Meta-Analysis Identifies VDAC1 as a Predictor of Poor Outcome in Early Stage Non-Small Cell Lung Cancer

Background: The bioenergetic status of non-small cell lung cancer correlates with tumour aggressiveness. The voltage dependent anion channel type 1 (VDAC1) is a component of the mitochondrial permeability transition pore, regulates mitochondrial ATP/ADP exchange suggesting that its over-expression could be associated with energy dependent processes including increased proliferation and invasiveness. To test this hypothesis, we conducted an in vivo gene-expression meta-analysis of surgically resected non-small cell lung cancer (NSCLC) using 602 individual expression profiles, to examine the impact of VDAC1 on survival.

The expression of RUNX3 in colorectal cancer is associated with disease stage and patient outcome

RUNX3 is believed to have tumour suppressor properties in several cancer types. Inactivation of RUNX3 has been shown to occur by methylation-induced transcriptional silencing and by mislocalization of the protein to the cytoplasm. The aim of this study was to examine the clinical significance of RUNX3 expression in a large series of colorectal cancers using immunohistochemistry and tissue arrays. With advancing tumour stage, expression of RUNX3 in the nucleus decreased, whereas expression restricted to the cytoplasmic compartment increased. Nuclear RUNX3 expression was associated with significantly better patient survival compared to tumours in which the expression of RUNX3 was restricted to the cytoplasm (P = 0.025). These results support a role for RUNX3 as a tumour suppressor in colorectal cancer.

Whose play is it anyway?: Theatre Studies, Translation Studies and translation for the stage

This article explores the historical neglect of translation as a consideration in the study and practice of theatre in the United States and Europe. While the study of literature is fairly strictly divided between English-language and Comparative Literature departments, theatre and drama have shown little concern about language as a barrier to reception of the dramatic text. Arguably, this discrepancy may be traced to a fundamental gap between the perceived status of the novel as a completed work of art and the playtext as work of art in progress, waiting to find its completion in performance.

The expression and prognostic impact of CXC-chemokines in stage II and III colorectal cancer epithelial and stromal tissue

BACKGROUND: The CXC-chemokine expression is linked with colorectal cancer (CRC) progression but their significance in resected CRC is unclear. We explored the prognostic impact of such expression in stage II and III CRC.

Prognostic Significance of TRAIL Signaling Molecules in Stage II and III Colorectal Cancer

Purpose: We previously found that cellular FLICE-inhibitory protein (c-FLIP), caspase 8, and tumor necrosis factor–related apoptosis-inducing ligand (TRAIL) receptor 2 (DR5) are major regulators of cell viability and chemotherapy-induced apoptosis in colorectal cancer. In this study, we determined the prognostic significance of c-FLIP, caspase 8, TRAIL and DR5 expression in tissues from patients with stage II and III colorectal cancer.

Experimental Design: Tissue microarrays were constructed from matched normal and tumor tissue derived from patients (n = 253) enrolled in a phase III trial of adjuvant 5-fluorouracil–based chemotherapy versus postoperative observation alone. TRAIL, DR5, caspase 8, and c-FLIP expression levels were determined by immunohistochemistry.

Results: Colorectal tumors displayed significantly higher expression levels of c-FLIP (P < 0.001), caspase 8 (P = 0.01), and DR5 (P < 0.001), but lower levels of TRAIL (P < 0.001) compared with matched normal tissue. In univariate analysis, higher TRAIL expression in the tumor was associated with worse overall survival (P = 0.026), with a trend to decreased relapse-free survival (RFS; P = 0.06), and higher tumor c-FLIP expression was associated with a significantly decreased RFS (P = 0.015). Using multivariate predictive modeling for RFS in all patients and including all biomarkers, age, treatment, and stage, we found that the model was significant when the mean tumor c-FLIP expression score and disease stage were included (P < 0.001). As regards overall survival, the overall model was predictive when both TRAIL expression and disease stage were included (P < 0.001).

Conclusions: High c-FLIP and TRAIL expression may be independent adverse prognostic markers in stage II and III colorectal cancer and might identify patients most at risk of relapse.

Two-stage RBF network construction based on particle swarm optimization

The conventional radial basis function (RBF) network optimization methods, such as orthogonal least squares or the two-stage selection, can produce a sparse network with satisfactory generalization capability. However, the RBF width, as a nonlinear parameter in the network, is not easy to determine. In the aforementioned methods, the width is always pre-determined, either by trial-and-error, or generated randomly. Furthermore, all hidden nodes share the same RBF width. This will inevitably reduce the network performance, and more RBF centres may then be needed to meet a desired modelling specification. In this paper we investigate a new two-stage construction algorithm for RBF networks. It utilizes the particle swarm optimization method to search for the optimal RBF centres and their associated widths. Although the new method needs more computation than conventional approaches, it can greatly reduce the model size and improve model generalization performance. The effectiveness of the proposed technique is confirmed by two numerical simulation examples.