Investigation of the composition of linear alkylbenzenes with emphasis on the identification and quantitation of some trace compounds using GS/MS system in both electron impact and chemical ionization modes

Linear alkylbenzenes, LAB, formed by the Alel3 or HF catalyzed alkylation of benzene are common raw materials for surfactant manufacture. Normally they are sulphonated using S03 or oleum to give the corresponding linear alkylbenzene sulphonates In >95 % yield. As concern has grown about the environmental impact of surfactants,' questions have been raised about the trace levels of unreacted raw materials, linear alkylbenzenes and minor impurities present in them. With the advent of modem analytical instruments and techniques, namely GCIMS, the opportunity has arisen to identify the exact nature of these impurities and to determine the actual levels of them present in the commercial linear ,alkylbenzenes. The object of the proposed study was to separate, identify and quantify major and minor components (1-10%) in commercial linear alkylbenzenes. The focus of this study was on the structure elucidation and determination of impurities and on the qualitative determination of them in all analyzed linear alkylbenzene samples. A gas chromatography/mass spectrometry, (GCIMS) study was performed o~ five samples from the same manufacturer (different production dates) and then it was followed by the analyses of ten commercial linear alkylbenzenes from four different suppliers. All the major components, namely linear alkylbenzene isomers, followed the same elution pattern with the 2-phenyl isomer eluting last. The individual isomers were identified by interpretation of their electron impact and chemical ionization mass spectra. The percent isomer distribution was found to be different from sample to sample. Average molecular weights were calculated using two methods, GC and GCIMS, and compared with the results reported on the Certificate of Analyses (C.O.A.) provided by the manufacturers of commercial linear alkylbenzenes. The GC results in most cases agreed with the reported values, whereas GC/MS results were significantly lower, between 0.41 and 3.29 amu. The minor components, impurities such as branched alkylbenzenes and dialkyltetralins eluted according to their molecular weights. Their fragmentation patterns were studied using electron impact ionization mode and their molecular weight ions confirmed by a 'soft ionization technique', chemical ionization. The level of impurities present i~ the analyzed commercial linear alkylbenzenes was expressed as the percent of the total sample weight, as well as, in mg/g. The percent of impurities was observed to vary between 4.5 % and 16.8 % with the highest being in sample "I". Quantitation (mg/g) of impurities such as branched alkylbenzenes and dialkyltetralins was done using cis/trans-l,4,6,7-tetramethyltetralin as an internal standard. Samples were analyzed using .GC/MS system operating under full scan and single ion monitoring data acquisition modes. The latter data acquisition mode, which offers higher sensitivity, was used to analyze all samples under investigation for presence of linear dialkyltetralins. Dialkyltetralins were reported quantitatively, whereas branched alkylbenzenes were reported semi-qualitatively. The GC/MS method that was developed during the course of this study allowed identification of some other trace impurities present in commercial LABs. Compounds such as non-linear dialkyltetralins, dialkylindanes, diphenylalkanes and alkylnaphthalenes were identified but their detailed structure elucidation and the quantitation was beyond the scope of this study. However, further investigation of these compounds will be the subject of a future study.

Method and truth in MÄ dhyamika

Abstract The study was undertaken to identify what motivates registered nurses to participate in continuing education activities. The primary questions were whether basic nursing education, employment status, clinical area, and position, as well as readiness for selfdirected learning influenced Canadian nurses' motivational orientations when deciding to participate in continuing education activities. Other individual differences (e.g., age) were also examined. The sample included 142 registered nurses employed at an urban community hospital. Three instruments were used for data collection: the Education Participation Scale, the Self-Directed Learning Readiness Scale, and a nursing survey consisting of demographic questions. Basic nursing education and employment status did not effect motivational orientation or self-directed learning readiness. Clinical area and level of position significantly influenced nurses' decisions to participate in continuing education activities. Motivational orientation had a significant relationship with selfdirected learning readiness. Implications for practice as a result of this study involves program planning and delivery. The identification of the motivational orientations of participants may assist in the development and delivery of continuing education programs that are beneficial, relevant, and address the identified learning needs of participants. Implications for future research also exist in relation to studying different groups of nurses, for example, registered nursing assistants, and investigating related issues, for example, what are the deterrents to participation in continuing education?

The identification, distribution and persistence of oxamyl and its degradation products in planted corn seed, seedling root and soil from oxamyl-treated corn seeds

A simple method was developed for treating corn seeds with oxamyl. It involved soaking the seeds to ensure oxamyl uptake, centrifugation to draw off excess solution, and drying under a stream of air to prevent the formation of fungus. The seeds were found to have an even distribution of oxamyl. Seeds remained fungus-free even 12 months after treatment. The highest nonphytotoxic treatment level was obtained by using a 4.00 mg/mL oxamyl solution. Extraction methods for the determination of oxamyl (methyl-N'N'-dimethyl-N-[(methylcarbamoyl)oxy]-l-thiooxamimidate), its oxime (methyl-N',N'-dimethyl-N-hydroxy-1-thiooxamimidate), and DMCF (N,N-dimethyl-1-cyanoformanade) in seed" root, and soil were developed. Seeds were processed by homogenizing, then shaking in methanol. Significantly more oxamyl was extracted from hydrated seeds as opposed to dry seeds. Soils were extracted by tumbling in methanol; recoveries range~ from 86 - 87% for oxamyl. Root was extracted to 93% efficiency for oxamyl by homogenizing the tissue in methanol. NucharAttaclay column cleanup afforded suitable extracts for analysis by RP-HPLC on a C18 column and UV detection at 254 nm. In the degradation study, oxamyl was found to dissipate from the seed down into the soil. It was also detected in the root. Oxime was detected in both the seed and soil, but not in the root. DMCF was detected in small amounts only in the seed.

Hyperspectral Mineral Identification using SVM and SOM

Remote sensing techniques involving hyperspectral imagery have applications in a number of sciences that study some aspects of the surface of the planet. The analysis of hyperspectral images is complex because of the large amount of information involved and the noise within that data. Investigating images with regard to identify minerals, rocks, vegetation and other materials is an application of hyperspectral remote sensing in the earth sciences. This thesis evaluates the performance of two classification and clustering techniques on hyperspectral images for mineral identification. Support Vector Machines (SVM) and Self-Organizing Maps (SOM) are applied as classification and clustering techniques, respectively. Principal Component Analysis (PCA) is used to prepare the data to be analyzed. The purpose of using PCA is to reduce the amount of data that needs to be processed by identifying the most important components within the data. A well-studied dataset from Cuprite, Nevada and a dataset of more complex data from Baffin Island were used to assess the performance of these techniques. The main goal of this research study is to evaluate the advantage of training a classifier based on a small amount of data compared to an unsupervised method. Determining the effect of feature extraction on the accuracy of the clustering and classification method is another goal of this research. This thesis concludes that using PCA increases the learning accuracy, and especially so in classification. SVM classifies Cuprite data with a high precision and the SOM challenges SVM on datasets with high level of noise (like Baffin Island).

Identification of Network-Based Risk Factors Associated with Gonorrhea

The evolving antimicrobial resistance coupled with a recent increase in incidence highlights the importance of reducing gonococcal transmission. Establishing novel risk factors associated with gonorrhea facilitates the development of appropriate prevention and disease control strategies. Sexual Network Analysis (NA), a novel research technique used to further understand sexually transmitted infections, was used to identify network-based risk factors in a defined region in Ontario, Canada experiencing an increase in the incidence of gonorrhea. Linear network structures were identified as important reservoirs of gonococcal transmission. Additionally, a significant association between a central network position and gonorrhea was observed. The central participants were more likely to be younger, report a greater number of risk factors, engage in anonymous sex, have multiple sex partners in the past six months and have sex with the same sex. The network-based risk factors identified through sexual NA, serving as a method of analyzing local surveillance data, support the development of strategies aimed at reducing gonococcal spread.