6 resultados para Halley’s and Euler-Chebyshev’s Methods
em DigitalCommons@The Texas Medical Center
Resumo:
This paper defines and compares several models for describing excess influenza pneumonia mortality in Houston. First, the methodology used by the Center for Disease Control is examined and several variations of this methodology are studied. All of the models examined emphasize the difficulty of omitting epidemic weeks.^ In an attempt to find a better method of describing expected and epidemic mortality, time series methods are examined. Grouping in four-week periods, truncating the data series to adjust epidemic periods, and seasonally-adjusting the series y(,t), by:^ (DIAGRAM, TABLE OR GRAPHIC OMITTED...PLEASE SEE DAI)^ is the best method examined. This new series w(,t) is stationary and a moving average model MA(1) gives a good fit for forecasting influenza and pneumonia mortality in Houston.^ Influenza morbidity, other causes of death, sex, race, age, climate variables, environmental factors, and school absenteeism are all examined in terms of their relationship to influenza and pneumonia mortality. Both influenza morbidity and ischemic heart disease mortality show a very high relationship that remains when seasonal trends are removed from the data. However, when jointly modeling the three series it is obvious that the simple time series MA(1) model of truncated, seasonally-adjusted four-week data gives a better forecast.^
Resumo:
Two sets of mass spectrometry-based methods were developed specifically for the in vivo study of extracellular neuropeptide biochemistry. First, an integrated micro-concentration/desalting/matrix-addition device was constructed for matrix-assisted laser desorption ionization mass spectrometry (MALDI MS) to achieve attomole sensitivity for microdialysis samples. Second, capillary electrophoresis (CE) was incorporated into the above micro-liquid chromatography (LC) and MALDI MS system to provide two-dimensional separation and identification (i.e. electrophoretic mobility and molecular mass) for the analysis of complex mixtures. The latter technique includes two parts of instrumentation: (1) the coupling of a preconcentration LC column to the inlet of a CE capillary, and (2) the utilization of a matrix-precoated membrane target for continuous CE effluent deposition and for automatic MALDI MS analysis (imaging) of the CE track.^ Initial in vivo data reveals a carboxypeptidase A (CPA) activity in rat brain involved in extracellular neurotensin metabolism. Benzylsuccinic acid, a CPA inhibitor, inhibited neurotensin metabolite NT1-12 formation by 70%, while inhibitors of other major extracellular peptide metabolizing enzymes increased NT1-12 formation. CPA activity has not been observed in previous in vitro experiments. Next, the validity of the methodology was demonstrated in the detection and structural elucidation of an endogenous neuropeptide, (L)VV-hemorphin-7, in rat brain upon ATP stimulation. Finally, the combined micro-LC/CE/MALDI MS was used in the in vivo metabolic study of peptide E, a mu-selective opioid peptide with 25 amino acid residues. Profiles of 88 metabolites were obtained, their identity being determined by their mass-to-charge ratio and electrophoretic mobility. The results indicate that there are several primary cleavage sites in vivo for peptide E in the release of its enkephalin-containing fragments. ^
Resumo:
The difficulty of detecting differential gene expression in microarray data has existed for many years. Several correction procedures try to avoid the family-wise error rate in multiple comparison process, including the Bonferroni and Sidak single-step p-value adjustments, Holm's step-down correction method, and Benjamini and Hochberg's false discovery rate (FDR) correction procedure. Each multiple comparison technique has its advantages and weaknesses. We studied each multiple comparison method through numerical studies (simulations) and applied the methods to the real exploratory DNA microarray data, which detect of molecular signatures in papillary thyroid cancer (PTC) patients. According to our results of simulation studies, Benjamini and Hochberg step-up FDR controlling procedure is the best process among these multiple comparison methods and we discovered 1277 potential biomarkers among 54675 probe sets after applying the Benjamini and Hochberg's method to PTC microarray data.^
Resumo:
Developing countries are heavily burdened by limited access to safe drinking water and subsequent water-related diseases. Numerous water treatment interventions combat this public health crisis, encompassing both traditional and less-common methods. Of these, water disinfection serves as an important means to provide safe drinking water. Existing literature discusses a wide range of traditional treatment options and encourages the use of multi-barrier approaches including coagulation-flocculation, filtration, and disinfection. Most sources do not delve into approaches specifically appropriate for developing countries, nor do they exclusively examine water disinfection methods.^ The objective of this review is to focus on an extensive range of chemical, physio-chemical, and physical water disinfection techniques to provide a compilation, description and evaluation of options available. Such an objective provides further understanding and knowledge to better inform water treatment interventions and explores alternate means of water disinfection appropriate for developing countries. Appropriateness for developing countries corresponds to the effectiveness of an available, easy to use disinfection technique at providing safe drinking water at a low cost.^ Among chemical disinfectants, SWS sodium hypochlorite solution is preferred over sodium hypochlorite bleach due to consistent concentrations. Tablet forms are highly recommended chemical disinfectants because they are effective and very easy to use, but also because they are stable. Examples include sodium dichloroisocyanurate, calcium hypochlorite, and chlorine dioxide, which vary in cost depending on location and availability. Among physio-chemical disinfection options, electrolysis which produces mixed oxidants (MIOX) provides a highly effective disinfection option with a higher upfront cost but very low cost over the long term. Among physical disinfection options, solar disinfection (SODIS) applications are effective, but they treat only a fixed volume of water at a time. They come with higher initial costs but very low on-going costs. Additional effective disinfection techniques may be suitable depending on the location, availability and cost.^
Resumo:
Context: Black women are reported to have a higher prevalence of uterine fibroids, and a threefold higher incidence rate and relative risk for clinical uterine fibroid development as compared to women of other races. Uterine fibroid research has reported that black women experience greater uterine fibroid morbidity and disproportionate uterine fibroid disease burden. With increased interest in understanding uterine fibroid development, and race being a critical component of uterine fibroid assessment, it is imperative that the methods used to determine the race of research participants is defined and the operational definition of the use of race as a variable is reported for methodological guidance, and to enable the research community to compare statistical data and replicate studies. ^ Objectives: To systematically review and evaluate the methods used to assess race and racial disparities in uterine fibroid research. ^ Data Sources: Databases searched for this review include: OVID Medline, NML PubMed, Ebscohost Cumulative Index to Nursing and Allied Health Plus with Full Text, and Elsevier Scopus. ^ Review Methods: Articles published in English were retrieved from data sources between January 2011 and March 2011. Broad search terms, uterine fibroids and race, were employed to retrieve a comprehensive list of citations for review screening. The initial database yield included 947 articles, after duplicate extraction 485 articles remained. In addition, 771 bibliographic citations were reviewed to identify additional articles not found through the primary database search, of which 17 new articles were included. In the first screening, 502 titles and abstracts were screened against eligibility questions to determine citations of exclusion and to retrieve full text articles for review. In the second screening, 197 full texted articles were screened against eligibility questions to determine whether or not they met full inclusion/exclusion criteria. ^ Results: 100 articles met inclusion criteria and were used in the results of this systematic review. The evidence suggested that black women have a higher prevalence of uterine fibroids when compared to white women. None of the 14 studies reporting data on prevalence reported an operational definition or conceptual framework for the use of race. There were a limited number of studies reporting on the prevalence of risk factors among racial subgroups. Of the 3 studies, 2 studies reported prevalence of risk factors lower for black women than other races, which was contrary to hypothesis. And, of the three studies reporting on prevalence of risk factors among racial subgroups, none of them reported a conceptual framework for the use of race. ^ Conclusion: In the 100 uterine fibroid studies included in this review over half, 66%, reported a specific objective to assess and recruit study participants based upon their race and/or ethnicity, but most, 51%, failed to report a method of determining the actual race of the participants, and far fewer, 4% (only four South American studies), reported a conceptual framework and/or operational definition of race as a variable. However, most, 95%, of all studies reported race-based health outcomes. The inadequate methodological guidance on the use of race in uterine fibroid studies, purporting to assess race and racial disparities, may be a primary reason that uterine fibroid research continues to report racial disparities, but fails to understand the high prevalence and increased exposures among African-American women. A standardized method of assessing race throughout uterine fibroid research would appear to be helpful in elucidating what race is actually measuring, and the risk of exposures for that measurement. ^
Resumo:
Accurate quantitative estimation of exposure using retrospective data has been one of the most challenging tasks in the exposure assessment field. To improve these estimates, some models have been developed using published exposure databases with their corresponding exposure determinants. These models are designed to be applied to reported exposure determinants obtained from study subjects or exposure levels assigned by an industrial hygienist, so quantitative exposure estimates can be obtained. ^ In an effort to improve the prediction accuracy and generalizability of these models, and taking into account that the limitations encountered in previous studies might be due to limitations in the applicability of traditional statistical methods and concepts, the use of computer science- derived data analysis methods, predominantly machine learning approaches, were proposed and explored in this study. ^ The goal of this study was to develop a set of models using decision trees/ensemble and neural networks methods to predict occupational outcomes based on literature-derived databases, and compare, using cross-validation and data splitting techniques, the resulting prediction capacity to that of traditional regression models. Two cases were addressed: the categorical case, where the exposure level was measured as an exposure rating following the American Industrial Hygiene Association guidelines and the continuous case, where the result of the exposure is expressed as a concentration value. Previously developed literature-based exposure databases for 1,1,1 trichloroethane, methylene dichloride and, trichloroethylene were used. ^ When compared to regression estimations, results showed better accuracy of decision trees/ensemble techniques for the categorical case while neural networks were better for estimation of continuous exposure values. Overrepresentation of classes and overfitting were the main causes for poor neural network performance and accuracy. Estimations based on literature-based databases using machine learning techniques might provide an advantage when they are applied to other methodologies that combine `expert inputs' with current exposure measurements, like the Bayesian Decision Analysis tool. The use of machine learning techniques to more accurately estimate exposures from literature-based exposure databases might represent the starting point for the independence from the expert judgment.^