Profiling of berries by comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry (GCxGC/TOF-MS)

poster C149, Proceedings Annual Biomedical Research Conference for Minority Students (ABRCMS 2011), November 9 - 12, 2011, America’s Center, St. Louis, MO, US

Comparing Military-Connected and NonMilitary-Connected Students’ Orientation Experiences

The purpose of this study was to compare the orientation experiences of military-connected and non-military-connected students. Specifically, this study explored the influence of an enhanced early-intervention orientation strategy for military-connected students transitioning from active duty to college. Data were collected from all transfer students participating in a university orientation program. Findings indicated that military connected students rated the overall orientation experience significantly higher than their non-military-connected counterparts. However, they rated their connectedness to campus significantly lower. Recommendations for improving orientation practices for military connected students are discussed

OmicsVis: an interactive tool for visually analyzing metabolomics data

When analyzing metabolomics data, cancer care researchers are searching for differences between known healthy samples and unhealthy samples. By analyzing and understanding these differences, researchers hope to identify cancer biomarkers. Due to the size and complexity of the data produced, however, analysis can still be very slow and time consuming. This is further complicated by the fact that datasets obtained will exhibit incidental differences in intensity and retention time, not related to actual chemical differences in the samples being evaluated. Additionally, automated tools to correct these errors do not always produce reliable results. This work presents a new analytics system that enables interactive comparative visualization and analytics of metabolomics data obtained by two-dimensional gas chromatography-mass spectrometry (GC × GC-MS). The key features of this system are the ability to produce visualizations of multiple GC × GC-MS data sets, and to explore those data sets interactively, allowing a user to discover differences and features in real time. The system provides statistical support in the form of difference, standard deviation, and kernel density estimation calculations to aid users in identifying meaningful differences between samples. These are combined with novel transfer functions and multiform, linked visualizations in order to provide researchers with a powerful new tool for GC × GC-MS exploration and bio-marker discovery

User-friendly method for GCxGC optimization

Almost 30 years are gone since the first paper about multidimensional GC was published by John B. Phillips 1. After several years of developing process, Comprehensive Two Dimensional Gas Chromatography systems are in the commercialization step of its live time. During this period, the advantages of GC×GC, regarding to classical D1 system, were clearly demonstrated 2. However, the new parameters involve in a GC×GC method are still not completely understand and people don’t use it at the maximum of its capacity. According to the literature more and more group are using GC×GC for different kind of applications. In most of these researches, GC×GC was used for its separation power. Unfortunately, the orthogonality and the column set are most of the time poorly optimized. To help people in this important step, we develop an user-friendly method to choose the best column combination and the best separation parameters for a particular application. All these developments were based on different mix of standard call the Century mix and the Dimandja mix. These are the descendants of the Phillips mix create in 2003 by J. Dimandja 3. These mixtures contain homologous series of compounds representing the polarity and the volatility range commonly sees in GC×GC. This method is based on the Retention Index obtained in a classical GC analysis and projected in the 2D space. Using this projection method, we identified four major types of orthogonality based on the peak dispersion obtained. We name those: Normal, Reverse, Hybrid and Transpose orthogonality. To characterize these observations, we developed the Orthogonality Index. Going back to the mathematical definition of orthogonality, this factor is the angle formed between the alkane line and the aromatic hydrocarbon line in the chromatographic space. Using this predictive tool, people should be able to choose the best column set and to optimize easily the separation parameters. 1. Phillips, J.B., Luu, D., Pawliszyn, J.B. & Carle, G.C. Multiplex gas chromatography by thermal modulation of a fused silica capillary column. Anal. Chem. 57, 2779–2787 (1985). 2. Dimandja, J.-M.D. Comprehensive 2-D GC provides high-performance separations in terms of selectivity, sensitivity, speed, and structure. Anal. Chem. 76, 167A–174A (2004). 3. Dimandja, J., Clouden, G. & Colón, I. Standardized test mixture for the characterization of comprehensive two-dimensional gas chromatography columns: the Phillips mix. J Chromatogr a 1019, 261–272 (2003)

Le pays de Katako-Kombe à l'époque coloniale (1904-1945)

Thèse de doctorat -- Université catholique de Louvain, 197

SUPPLY EQUATIONS OF CEREALS FOR NORTH AFRICA, ETHIOPIA, KENYA, NIGERIA AND SOUTH AFRICA

The need for this study stems from the problems of grain shortage in these parts of the world. The regions included in this study are: North Africa (Morocco, Algeria, Tunisia, Libya, United Arab Republic and Sudan), Ethiopia, Kenya, Nigeria, and the Republic of South Africa. The North Africa region was chosen to conform with previous analysis which was done on the demand side in a project of the Department of Agricultural Economics of Michigan State University. Other countries were also included in order to make the analysis comparable to the demand study. The methodology was basically determined by the data available. Therefore, an analysis on existing time series data was undertaken. It is not the purpose here to examine specific policies, but rather to study the general principles and factors considered of primary importance in the supply of cereals. More specifically, the purposes of this study are: 1) to examine some important economic variables that affect the supply of cereals for these regions; and 2) to generate projections of cereals production based upon supply equations derived in the analysis. At this stage, however, the results of the analysis are not complete and may not provide sufficient background to establish policies, since the analysis is restricted to the supply and the data is crude. Furthermore, the fact that our projections (especially for North Africa and Nigeria) involve data collected during the Middle East and Civil wars respectively, suggests that these projections may be unduly affected by unusual events in the period of analysis

Théorie des systèmes, philosophie des systèmes : étude critique

Doctorat en philosophie et lettres (philosophie) (ISP 3)--UCL, 198