Active Set methods for solving large sample average approximations of chance constrained optimisation problems

This article describes a novel approach to chance-constrained programming based on the sample average approximation (SAA) method. Recent work focuses on heuristic approximations to the SAA problem and we introduce a novel approach which improves on some existing methods. Our Active Set method allows one to solve SAAs of chance-constrained programs with very large numbers of scenarios quickly. We demonstrate that increasing the number of scenarios is more important than improving accuracy with small numbers of scenarios. We use an example of the portfolio selection problem to demonstrate the relative performance of previous and new methods. Extending the Active Set method to an integer-programming model further highlights its applicability and further improves over previous approaches.Comment: 26 pages, 7 figures, This paper sets forth the material presented at the Decision Making Under Uncertainty workshop held at the University of Queensland, 11 July 202

The construction of a Solanum habrochaites LYC4 introgression line population and the identification of QTLs for resistance to Botrytis cinerea

Tomato (Solanum lycopersicum) is susceptible to grey mold (Botrytis cinerea). Partial resistance to this fungus has been identified in accessions of wild relatives of tomato such as Solanum habrochaites LYC4. In a previous F2 mapping study, three QTLs conferring resistance to B. cinerea (Rbcq1, Rbcq2 and Rbcq4a) were identified. As it was probable that this study had not identified all QTLs involved in resistance we developed an introgression line (IL) population (n = 30), each containing a S. habrochaites introgression in the S. lycopersicum cv. Moneymaker genetic background. On average each IL contained 5.2% of the S. habrochaites genome and together the lines provide an estimated coverage of 95%. The level of susceptibility to B. cinerea for each of the ILs was assessed in a greenhouse trial and compared to the susceptible parent S. lycopersicum cv. Moneymaker. The effect of the three previously identified loci could be confirmed and seven additional loci were detected. Some ILs contains multiple QTLs and the increased resistance to B. cinerea in these ILs is in line with a completely additive model. We conclude that this set of QTLs offers good perspectives for breeding of B. cinerea resistant cultivars and that screening an IL population is more sensitive for detection of QTLs conferring resistance to B. cinerea than the analysis in an F2 population

Improving coal quality estimations with geostatistics and geophysical logs

In most modern coal mines, there are many coal quality parameters that are measured on samples taken from boreholes. These data are used to generate spatial models of the coal quality parameters, typically using inverse distance as an interpolation method. At the same time, downhole geophysical logging of numerous additional boreholes is used to measure various physical properties but no coal quality samples are taken. The work presented in this paper uses two of the most important coal quality variables-ash and volatile matter-and assesses the efficacy of using a number of geostatistical interpolation methods to improve the accuracy of the interpolated models, including the use of auxiliary variables from geophysical logs. A multivariate spatial statistical analysis of ash, volatile matter and several auxiliary variables is used to establish a co-regionalization model that relates all of the variables as manifestations of an underlying geological characteristic. A case study of a coal mine in Queensland, Australia, is used to compare the interpolation methods of inverse distance to ordinary kriging, universal kriging, co-kriging, regression kriging and kriging with an external drift. The relative merits of these six methods are compared using the mean error and the root mean square error as measures of bias and accuracy. The study demonstrates that there is significant opportunity to improve the estimations of coal quality when using kriging with an external drift. The results show that when using the depth of a sample as an external drift variable there is a significant improvement in the accuracy of estimation for volatile matter, and when using wireline density logs as the drift variable there is improvement in the estimation of the in situ ash. The economic benefit of these findings is that cheaper proxies for coal quality parameters can significantly increase data density and the quality of estimations

Potentiation of cytotoxic chemotherapy by growth hormone-releasing hormone agonists

The dismal prognosis of malignant brain tumors drives the development of new treatment modalities. In view of the multiple activities of growth hormone-releasing hormone (GHRH), we hypothesized that pretreatment with a GHRH agonist, JI-34, might increase the susceptibility of U-87 MG glioblastoma multiforme (GBM) cells to subsequent treatment with the cytotoxic drug, doxorubicin (DOX). This concept was corroborated by our findings, in vivo, showing that the combination of the GHRH agonist, JI-34, and DOX inhibited the growth of GBM tumors, transplanted into nude mice, more than DOX alone. In vitro, the pretreatment of GBM cells with JI-34 potentiated inhibitory effects of DOX on cell proliferation, diminished cell size and viability, and promoted apoptotic processes, as shown by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide proliferation assay, ApoLive-Glo multiplex assay, and cell volumetric assay. Proteomic studies further revealed that the pretreatment with GHRH agonist evoked differentiation decreasing the expression of the neuroectodermal stem cell antigen, nestin, and up-regulating the glial maturation marker, GFAP. The GHRH agonist also reduced the release of humoral regulators of glial growth, such as FGF basic and TGFβ. Proteomic and gene-expression (RT-PCR) studies confirmed the strong proapoptotic activity (increase in p53, decrease in v-myc and Bcl-2) and anti-invasive potential (decrease in integrin α3) of the combination of GHRH agonist and DOX. These findings indicate that the GHRH agonists can potentiate the anticancer activity of the traditional chemotherapeutic drug, DOX, by multiple mechanisms including the induction of differentiation of cancer cells