Classification and Pay Plans FY2014, June 2013

This document Classifications and Pay Plans is produced by the State of Iowa Executive Branch, Department of Administrative Services. Informational document about the pay plan codes and classification codes, how to use them.

Characterization and classification of matrix effects in biological samples analyses.

An exhaustive classification of matrix effects occurring when a sample preparation is performed prior to liquid-chromatography coupled to mass spectrometry (LC-MS) analyses was proposed. A total of eight different situations were identified allowing the recognition of the matrix effect typology via the calculation of four recovery values. A set of 198 compounds was used to evaluate matrix effects after solid phase extraction (SPE) from plasma or urine samples prior to LC-ESI-MS analysis. Matrix effect identification was achieved for all compounds and classified through an organization chart. Only 17% of the tested compounds did not present significant matrix effects.

Knowledge management: uncovering risky gaps underlying the criticisms and moving to another perspective

The comments related to the sustainability of knowledge management (KM) have shown signs that it possibly can be a discourse which determines a quick style, but otherwise have also allowed the building of a better understanding about the limits and weaknesses of the knowlege management. In addition to the criticisms, the conceptual bases of knowledge management have been undermined by a contradictory combination of paradigms; there are also contradictions between the theoretical perspective jubjacent to the knwoledge management and its operationality. As a way of minimizing the possibility that the knowledge management may be turned into an umbrella concept and fail, it is suggested that its approaches embody a more interpretative perspective, taking up the role of an instrument which enables and facilitates the processes and practices in building up knowledge and information, enhancing their focus on the support to the establishment of human competences in order to deal intelligently with the present overcharge of information resources and need for building up information in the organizations.

Analysis and spatial modeling of the indoor radon Swiss data

The present research deals with an important public health threat, which is the pollution created by radon gas accumulation inside dwellings. The spatial modeling of indoor radon in Switzerland is particularly complex and challenging because of many influencing factors that should be taken into account. Indoor radon data analysis must be addressed from both a statistical and a spatial point of view. As a multivariate process, it was important at first to define the influence of each factor. In particular, it was important to define the influence of geology as being closely associated to indoor radon. This association was indeed observed for the Swiss data but not probed to be the sole determinant for the spatial modeling. The statistical analysis of data, both at univariate and multivariate level, was followed by an exploratory spatial analysis. Many tools proposed in the literature were tested and adapted, including fractality, declustering and moving windows methods. The use of Quan-tité Morisita Index (QMI) as a procedure to evaluate data clustering in function of the radon level was proposed. The existing methods of declustering were revised and applied in an attempt to approach the global histogram parameters. The exploratory phase comes along with the definition of multiple scales of interest for indoor radon mapping in Switzerland. The analysis was done with a top-to-down resolution approach, from regional to local lev¬els in order to find the appropriate scales for modeling. In this sense, data partition was optimized in order to cope with stationary conditions of geostatistical models. Common methods of spatial modeling such as Κ Nearest Neighbors (KNN), variography and General Regression Neural Networks (GRNN) were proposed as exploratory tools. In the following section, different spatial interpolation methods were applied for a par-ticular dataset. A bottom to top method complexity approach was adopted and the results were analyzed together in order to find common definitions of continuity and neighborhood parameters. Additionally, a data filter based on cross-validation was tested with the purpose of reducing noise at local scale (the CVMF). At the end of the chapter, a series of test for data consistency and methods robustness were performed. This lead to conclude about the importance of data splitting and the limitation of generalization methods for reproducing statistical distributions. The last section was dedicated to modeling methods with probabilistic interpretations. Data transformation and simulations thus allowed the use of multigaussian models and helped take the indoor radon pollution data uncertainty into consideration. The catego-rization transform was presented as a solution for extreme values modeling through clas-sification. Simulation scenarios were proposed, including an alternative proposal for the reproduction of the global histogram based on the sampling domain. The sequential Gaussian simulation (SGS) was presented as the method giving the most complete information, while classification performed in a more robust way. An error measure was defined in relation to the decision function for data classification hardening. Within the classification methods, probabilistic neural networks (PNN) show to be better adapted for modeling of high threshold categorization and for automation. Support vector machines (SVM) on the contrary performed well under balanced category conditions. In general, it was concluded that a particular prediction or estimation method is not better under all conditions of scale and neighborhood definitions. Simulations should be the basis, while other methods can provide complementary information to accomplish an efficient indoor radon decision making.

Very high-resolution environmental predictors in species distribution models: moving beyond topography?

Recent advances in remote sensing technologies have facilitated the generation of very high resolution (VHR) environmental data. Exploratory studies suggested that, if used in species distribution models (SDMs), these data should enable modelling species' micro-habitats and allow improving predictions for fine-scale biodiversity management. In the present study, we tested the influence, in SDMs, of predictors derived from a VHR digital elevation model (DEM) by comparing the predictive power of models for 239 plant species and their assemblages fitted at six different resolutions in the Swiss Alps. We also tested whether changes of the model quality for a species is related to its functional and ecological characteristics. Refining the resolution only contributed to slight improvement of the models for more than half of the examined species, with the best results obtained at 5 m, but no significant improvement was observed, on average, across all species. Contrary to our expectations, we could not consistently correlate the changes in model performance with species characteristics such as vegetation height. Temperature, the most important variable in the SDMs across the different resolutions, did not contribute any substantial improvement. Our results suggest that improving resolution of topographic data only is not sufficient to improve SDM predictions - and therefore local management - compared to previously used resolutions (here 25 and 100 m). More effort should be dedicated now to conduct finer-scale in-situ environmental measurements (e.g. for temperature, moisture, snow) to obtain improved environmental measurements for fine-scale species mapping and management.

Typologies textuelles et partitions musicales : dissimilarités, classification et autocorrélation

Axée dans un premier temps sur le formalisme et les méthodes, cette thèse est construite sur trois concepts formalisés: une table de contingence, une matrice de dissimilarités euclidiennes et une matrice d'échange. À partir de ces derniers, plusieurs méthodes d'Analyse des données ou d'apprentissage automatique sont exprimées et développées: l'analyse factorielle des correspondances (AFC), vue comme un cas particulier du multidimensional scaling; la classification supervisée, ou non, combinée aux transformations de Schoenberg; et les indices d'autocorrélation et d'autocorrélation croisée, adaptés à des analyses multivariées et permettant de considérer diverses familles de voisinages. Ces méthodes débouchent dans un second temps sur une pratique de l'analyse exploratoire de différentes données textuelles et musicales. Pour les données textuelles, on s'intéresse à la classification automatique en types de discours de propositions énoncées, en se basant sur les catégories morphosyntaxiques (CMS) qu'elles contiennent. Bien que le lien statistique entre les CMS et les types de discours soit confirmé, les résultats de la classification obtenus avec la méthode K- means, combinée à une transformation de Schoenberg, ainsi qu'avec une variante floue de l'algorithme K-means, sont plus difficiles à interpréter. On traite aussi de la classification supervisée multi-étiquette en actes de dialogue de tours de parole, en se basant à nouveau sur les CMS qu'ils contiennent, mais aussi sur les lemmes et le sens des verbes. Les résultats obtenus par l'intermédiaire de l'analyse discriminante combinée à une transformation de Schoenberg sont prometteurs. Finalement, on examine l'autocorrélation textuelle, sous l'angle des similarités entre diverses positions d'un texte, pensé comme une séquence d'unités. En particulier, le phénomène d'alternance de la longueur des mots dans un texte est observé pour des voisinages d'empan variable. On étudie aussi les similarités en fonction de l'apparition, ou non, de certaines parties du discours, ainsi que les similarités sémantiques des diverses positions d'un texte. Concernant les données musicales, on propose une représentation d'une partition musicale sous forme d'une table de contingence. On commence par utiliser l'AFC et l'indice d'autocorrélation pour découvrir les structures existant dans chaque partition. Ensuite, on opère le même type d'approche sur les différentes voix d'une partition, grâce à l'analyse des correspondances multiples, dans une variante floue, et à l'indice d'autocorrélation croisée. Qu'il s'agisse de la partition complète ou des différentes voix qu'elle contient, des structures répétées sont effectivement détectées, à condition qu'elles ne soient pas transposées. Finalement, on propose de classer automatiquement vingt partitions de quatre compositeurs différents, chacune représentée par une table de contingence, par l'intermédiaire d'un indice mesurant la similarité de deux configurations. Les résultats ainsi obtenus permettent de regrouper avec succès la plupart des oeuvres selon leur compositeur.

Allergic reactions following contrast material administration: nomenclature, classification, and mechanisms

In forensic pathology routine, fatal cases of contrast agent exposure can be occasionally encountered. In such situations, beyond the difficulties inherent in establishing the cause of death due to nonspecific or absent autopsy and histology findings as well as limited laboratory investigations, pathologists may face other problems in formulating exhaustive, complete reports, and conclusions that are scientifically accurate. Indeed, terminology concerning adverse drug reactions and allergy nomenclature is confusing. Some terms, still utilized in forensic and radiological reports, are outdated and should be avoided. Additionally, not all forensic pathologists master contrast material classification and pathogenesis of contrast agent reactions. We present a review of the literature covering allergic reactions to contrast material exposure in order to update used terminology, explain the pathophysiology, and list currently available laboratory investigations for diagnosis in the forensic setting.

Tire traces: discrimination and classification of pyrolysis-GC/MS profiles

Tire traces can be observed on several crime scenes as vehicles are often used by criminals. The tread abrasion on the road, while braking or skidding, leads to the production of small rubber particles which can be collected for comparison purposes. This research focused on the statistical comparison of Py-GC/MS profiles of tire traces and tire treads. The optimisation of the analytical method was carried out using experimental designs. The aim was to determine the best pyrolysis parameters regarding the repeatability of the results. Thus, the pyrolysis factor effect could also be calculated. The pyrolysis temperature was found to be five time more important than time. Finally, a pyrolysis at 650 °C during 15 s was selected. Ten tires of different manufacturers and models were used for this study. Several samples were collected on each tire, and several replicates were carried out to study the variability within each tire (intravariability). More than eighty compounds were integrated for each analysis and the variability study showed that more than 75% presented a relative standard deviation (RSD) below 5% for the ten tires, thus supporting a low intravariability. The variability between the ten tires (intervariability) presented higher values and the ten most variant compounds had a RSD value above 13%, supporting their high potential of discrimination between the tires tested. Principal Component Analysis (PCA) was able to fully discriminate the ten tires with the help of the first three principal components. The ten tires were finally used to perform braking tests on a racetrack with a vehicle equipped with an anti-lock braking system. The resulting tire traces were adequately collected using sheets of white gelatine. As for tires, the intravariability for the traces was found to be lower than the intervariability. Clustering methods were carried out and the Ward's method based on the squared Euclidean distance was able to correctly group all of the tire traces replicates in the same cluster than the replicates of their corresponding tire. Blind tests on traces were performed and were correctly assigned to their tire source. These results support the hypothesis that the tested tires, of different manufacturers and models, can be discriminated by a statistical comparison of their chemical profiles. The traces were found to be not differentiable from their source but differentiable from all the other tires present in the subset. The results are promising and will be extended on a larger sample set.

Treatment implications of the emerging molecular classification system for melanoma.

Melanoma is an aggressive disease with few standard treatment options. The conventional classification system for this disease is based on histological growth patterns, with division into four subtypes: superficial spreading, lentigo maligna, nodular, and acral lentiginous. Major limitations of this classification system are absence of prognostic importance and little correlation with treatment outcomes. Recent preclinical and clinical findings support the notion that melanoma is not one malignant disorder but rather a family of distinct molecular diseases. Incorporation of genetic signatures into the conventional histopathological classification of melanoma has great implications for development of new and effective treatments. Genes of the mitogen-associated protein kinase (MAPK) pathway harbour alterations sometimes identified in people with melanoma. The mutation Val600Glu in the BRAF oncogene (designated BRAF(V600E)) has been associated with sensitivity in vitro and in vivo to agents that inhibit BRAF(V600E) or MEK (a kinase in the MAPK pathway). Melanomas arising from mucosal, acral, chronically sun-damaged surfaces sometimes have oncogenic mutations in KIT, against which several inhibitors have shown clinical efficacy. Some uveal melanomas have activating mutations in GNAQ and GNA11, rendering them potentially susceptible to MEK inhibition. These findings suggest that prospective genotyping of patients with melanoma should be used increasingly as we work to develop new and effective treatments for this disease.

What's so special about conversion disorder? A problem and a proposal for diagnostic classification.

Conversion disorder presents a problem for the revisions of DSM-IV and ICD-10, for reasons that are informative about the difficulties of psychiatric classification more generally. Giving up criteria based on psychological aetiology may be a painful sacrifice but it is still the right thing to do.

Keep on moving from English to Catalan : El determinisme lingüístic en la traducció del moviment

El propòsit d'aquest treball és fixar, basant-nos en l'anàlisi tipològica, les diferències lingüístiques en la construcció de les expressions de moviment de l'anglès i el català. Partim de la hipòtesi que en funció de l'origen de la llengua, s'apliquen solucions diferents a determinats problemes lingüístics que apareixen a l'hora de traduir un discurs. Analitzarem, doncs, el grau de fidelitat de la traducció quant a l'expressió del trajecte i de la manera. Per consegüent, estudiarem si hi ha cap pèrdua d'informació, de qualitat o de genuïnitat en relació amb el text original servint-nos de la comparació d'ambdós estils narratius.