A study for hypergolic vapor sensor development

In summary, the following tasks were completed within the scope of this work: (1) a portable Monomethylhydrazine analyzer was developed, designed, fabricated and tested. (2) A portable NO2 analyzer was developed, designed, fabricated and tested. (3) Sampling probes and accessories were designed and fabricated for this instrumentation. (4) Improvements and modifications were made to the model 7630 Ecolyzer in preparation for field testing. (5) Instrument calibration procedures and hydrazine handling techniques necessary to the successful application of this hardware were developed

Toxic level hypergolic vapor detection sensor development

Development of an electrochemical sensor technology capable of PPB level hypergolic vapor sensing is reported. A portable instrument capable of meeting the design goals is described

The vanishing ideal of a finite set of points with multiplicity structures

Given a finite set of arbitrarily distributed points in affine space with arbitrary multiplicity structures, we present an algorithm to compute the reduced Groebner basis of the vanishing ideal under the lexicographic ordering. Our method discloses the essential geometric connection between the relative position of the points with multiplicity structures and the quotient basis of the vanishing ideal, so we will explicitly know the set of leading terms of elements of I. We split the problem into several smaller ones which can be solved by induction over variables and then use our new algorithm for intersection of ideals to compute the result of the original problem. The new algorithm for intersection of ideals is mainly based on the Extended Euclidean Algorithm.Comment: 12 pages,12 figures,ASCM 201

Field-usable portable analyzer for chlorinated organic compounds

In 1992, a chemical sensor was developed which showed almost perfect selectivity to vapors of chlorinated solvents. When interfaced to an instrument, a chemical analyzer will be produced that has near- absolute selectivity to vapors of volatile chlorinated organic compounds. TRI has just completed the second of a 2-phase program to develop this new instrument system, which is called the RCL MONITOR. In Phase II, this instrument was deployed in 5 EM40 operations. Phase II applications covered clean-up process monitoring, environmental modeling, routine monitoring, health and safety, and technology validation. Vapor levels between 0 and 100 ppM can be determined in 90 s with a lower detection limit of 0.5 ppM using the hand-portable instrument. Based on the favorable performance of the RCL MONITOR, the commercial instrument was released for commercial sales on Sept. 20, 1996

Health knowledge among the millennial generation

The Millennial Generation, also known as Generation Y, is the demographic cohort following Generation X, and is generally regarded to be composed of those individuals born between 1980 and 2000. They are the first to grow up in an environment where health-related information is widely available by internet, TV and other electronic media, yet we know very little about the scope of their health knowledge. This study was undertaken to quantify two domains of clinically relevant health knowledge: factual content and ability to solve health related questions (application) in nine clinically related medical areas. Study subjects correctly answered, on average, 75% of health application questions but only 54% of health content questions. Since students were better able to correctly answer questions dealing with applications compared to those on factual content contemporary US high school students may not use traditional hierarchical learning models in acquisition of their health knowledge

Knowledge-based gene expression classification via matrix factorization

Motivation: Modern machine learning methods based on matrix decomposition techniques, like independent component analysis (ICA) or non-negative matrix factorization (NMF), provide new and efficient analysis tools which are currently explored to analyze gene expression profiles. These exploratory feature extraction techniques yield expression modes (ICA) or metagenes (NMF). These extracted features are considered indicative of underlying regulatory processes. They can as well be applied to the classification of gene expression datasets by grouping samples into different categories for diagnostic purposes or group genes into functional categories for further investigation of related metabolic pathways and regulatory networks. Results: In this study we focus on unsupervised matrix factorization techniques and apply ICA and sparse NMF to microarray datasets. The latter monitor the gene expression levels of human peripheral blood cells during differentiation from monocytes to macrophages. We show that these tools are able to identify relevant signatures in the deduced component matrices and extract informative sets of marker genes from these gene expression profiles. The methods rely on the joint discriminative power of a set of marker genes rather than on single marker genes. With these sets of marker genes, corroborated by leave-one-out or random forest cross-validation, the datasets could easily be classified into related diagnostic categories. The latter correspond to either monocytes versus macrophages or healthy vs Niemann Pick C disease patients.Siemens AG, MunichDFG (Graduate College 638)DAAD (PPP Luso - Alem˜a and PPP Hispano - Alemanas

Generalized Romberg methods for integrals of derivatives

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46316/1/211_2005_Article_BF02165095.pd