Understanding magnesium corrosion - A framework for improved alloy performance

The purpose of this paper is to provide a succinct but nevertheless complete mechanistic overview of the various types of magnesium corrosion. The understanding of the corrosion processes of magnesium alloys builds upon our understanding of the corrosion of pure magnesium. This provides an understanding of the types of corrosion exhibited by,magnesium alloys, and also of the environmental factors Of most importance. This deep understanding is required as a foundation if we are to produce magnesium alloys much more resistant to corrosion than the present alloys. Much has already been achieved, but there is vast scope for improvement. This present analysis can provide a foundation and a theoretical framework for further, much needed research. There is still vast scope both for better fundamental understanding of corrosion processes, engineering usage of magnesium, and also on the corrosion protection of magnesium alloys in service.

Echinacea intake induces an immune response through altered expression of leucocyte hsp70, increased white cell counts and improved erythrocyte antioxidant defences

Objective: To study the effect of Echinacea tablets on the expression of leucocyte heat shock protein 70 (hsp70), erythrocyte haemolysis, plasma antioxidant status, serum chemistry, haematological values and plasma alkylamide concentrations. Method: Eleven healthy individuals (26-61 years of age) were evaluated at baseline (day 1) and on day 15 after consuming two commercially blended Echinacea tablets daily for 14 days. Results: Echinacea supplementation enhanced the fold increase in leucocyte hsp70 expression after a mild heat shock (P=0.029). White cell counts (WCC) were also increased (P=0.043). We also observed a preventative effect against free radical induced erythrocyte haemolysis (P=0.006) indicative of an antioxidant effect. Conclusion: The pilot study suggests that Echinacea may invoke an immune response through altered expression of hsp70 and increased WCC.

Statistical racing techniques for improved empirical evaluation of evolutionary algorithms

In empirical studies of Evolutionary Algorithms, it is usually desirable to evaluate and compare algorithms using as many different parameter settings and test problems as possible, in border to have a clear and detailed picture of their performance. Unfortunately, the total number of experiments required may be very large, which often makes such research work computationally prohibitive. In this paper, the application of a statistical method called racing is proposed as a general-purpose tool to reduce the computational requirements of large-scale experimental studies in evolutionary algorithms. Experimental results are presented that show that racing typically requires only a small fraction of the cost of an exhaustive experimental study.

BM+-tree: A hyperplane-based index method for high-dimensional metric spaces

In this paper, we propose a novel high-dimensional index method, the BM+-tree, to support efficient processing of similarity search queries in high-dimensional spaces. The main idea of the proposed index is to improve data partitioning efficiency in a high-dimensional space by using a rotary binary hyperplane, which further partitions a subspace and can also take advantage of the twin node concept used in the M+-tree. Compared with the key dimension concept in the M+-tree, the binary hyperplane is more effective in data filtering. High space utilization is achieved by dynamically performing data reallocation between twin nodes. In addition, a post processing step is used after index building to ensure effective filtration. Experimental results using two types of real data sets illustrate a significantly improved filtering efficiency.

Evaluation of a method for fusing LIDAR data and multispectral images for building detection

In this paper, we describe the evaluation of a method for building detection by the Dempster-Shafer fusion of LIDAR data and multispectral images. For that purpose, ground truth was digitised for two test sites with quite different characteristics. Using these data sets, the heuristic model for the probability mass assignments of the method is validated, and rules for the tuning of the parameters of this model are discussed. Further we evaluate the contributions of the individual cues used in the classification process to the quality of the classification results. Our results show the degree to which the overall correctness of the results can be improved by fusing LIDAR data with multispectral images.