A nonparametric method of comparing the partial areas under two correlated receiver operating characteristic curves

A non-parametric method was developed and tested to compare the partial areas under two correlated Receiver Operating Characteristic curves. Based on the theory of generalized U-statistics the mathematical formulas have been derived for computing ROC area, and the variance and covariance between the portions of two ROC curves. A practical SAS application also has been developed to facilitate the calculations. The accuracy of the non-parametric method was evaluated by comparing it to other methods. By applying our method to the data from a published ROC analysis of CT image, our results are very close to theirs. A hypothetical example was used to demonstrate the effects of two crossed ROC curves. The two ROC areas are the same. However each portion of the area between two ROC curves were found to be significantly different by the partial ROC curve analysis. For computation of ROC curves with large scales, such as a logistic regression model, we applied our method to the breast cancer study with Medicare claims data. It yielded the same ROC area computation as the SAS Logistic procedure. Our method also provides an alternative to the global summary of ROC area comparison by directly comparing the true-positive rates for two regression models and by determining the range of false-positive values where the models differ. ^

Growth Codes: Intermediate Performance Analysis and Application to Video

Growth codes are a subclass of Rateless codes that have found interesting applications in data dissemination problems. Compared to other Rateless and conventional channel codes, Growth codes show improved intermediate performance which is particularly useful in applications where partial data presents some utility. In this paper, we investigate the asymptotic performance of Growth codes using the Wormald method, which was proposed for studying the Peeling Decoder of LDPC and LDGM codes. Compared to previous works, the Wormald differential equations are set on nodes' perspective which enables a numerical solution to the computation of the expected asymptotic decoding performance of Growth codes. Our framework is appropriate for any class of Rateless codes that does not include a precoding step. We further study the performance of Growth codes with moderate and large size codeblocks through simulations and we use the generalized logistic function to model the decoding probability. We then exploit the decoding probability model in an illustrative application of Growth codes to error resilient video transmission. The video transmission problem is cast as a joint source and channel rate allocation problem that is shown to be convex with respect to the channel rate. This illustrative application permits to highlight the main advantage of Growth codes, namely improved performance in the intermediate loss region.

Proof internalization in generalized Frege systems for classical logic

We present a general method for inserting proofs in Frege systems for classical logic that produces systems that can internalize their own proofs.

Wanting to Get More or Protecting One's Assets: Age-Differential Effects of Gain Versus Loss Perceptions on the Willingness to Engage in Collective Action

OBJECTIVES: The present research examined motivational differences across adulthood that might contribute to age-related differences in the willingness to engage in collective action. Two experiments addressed the role of gain and loss orientation for age-related differences in the willingness to engage in collective action across adulthood. METHOD: In Experiment 1, N = 169 adults (20-85 years) were confronted with a hypothetical scenario that involved either an impending increase or decrease of health insurance costs for their respective age group. In Experiment 2, N = 231 adults (18-83 years) were asked to list an advantage or disadvantage they perceived in being a member of their age group. Subsequently, participants indicated their willingness to engage in collective action on behalf of their age group. RESULTS: Both experiments suggest that, with increasing age, people are more willing to engage in collective action when they are confronted with the prospect of loss or a disadvantage. DISCUSSION: The findings highlight the role of motivational processes for involvement in collective action across adulthood. With increasing age, (anticipated) loss or perceived disadvantages become more important for the willingness to participate in collective action.

An international study on the serological differential diagnosis of human cystic and alveolar echinococcosis.

An enzyme-linked immunosorbent assay (ELISA) for the serological differentiation of cystic (Echinococcus granulosus) and alveolar (E. multilocularis) echinococcosis in man has been evaluated. A discrimination rate of 95.1% was found for 82 sera from patients of geographically disparate endemic areas. This rate was essentially the same as that found for 57 Swiss patients, indicating that inter- and intraspecific strain differences do not influence the test results. The assay method is suitable for immunodiagnostic purposes as well as for seroepidemiological studies.

An adaptive Newton-method based on a dynamical systems approach

The traditional Newton method for solving nonlinear operator equations in Banach spaces is discussed within the context of the continuous Newton method. This setting makes it possible to interpret the Newton method as a discrete dynamical system and thereby to cast it in the framework of an adaptive step size control procedure. In so doing, our goal is to reduce the chaotic behavior of the original method without losing its quadratic convergence property close to the roots. The performance of the modified scheme is illustrated with various examples from algebraic and differential equations.

Estimation and calibration of the water isotope differential diffusion length in ice core records

Palaeoclimatic information can be retrieved from the diffusion of the stable water isotope signal during firnification of snow. The diffusion length, a measure for the amount of diffusion a layer has experienced, depends on the firn temperature and the accumulation rate. We show that the estimation of the diffusion length using power spectral densities (PSDs) of the record of a single isotope species can be biased by uncertainties in spectral properties of the isotope signal prior to diffusion. By using a second water isotope and calculating the difference in diffusion lengths between the two isotopes, this problem is circumvented. We study the PSD method applied to two isotopes in detail and additionally present a new forward diffusion method for retrieving the differential diffusion length based on the Pearson correlation between the two isotope signals. The two methods are discussed and extensively tested on synthetic data which are generated in a Monte Carlo manner. We show that calibration of the PSD method with this synthetic data is necessary to be able to objectively determine the differential diffusion length. The correlation-based method proves to be a good alternative for the PSD method as it yields precision equal to or somewhat higher than the PSD method. The use of synthetic data also allows us to estimate the accuracy and precision of the two methods and to choose the best sampling strategy to obtain past temperatures with the required precision. In addition to application to synthetic data the two methods are tested on stable-isotope records from the EPICA (European Project for Ice Coring in Antarctica) ice core drilled in Dronning Maud Land, Antarctica, showing that reliable firn temperatures can be reconstructed with a typical uncertainty of 1.5 and 2 °C for the Holocene period and 2 and 2.5 °C for the last glacial period for the correlation and PSD method, respectively.

Differential influence of maternal and fetal pregnancy factors on the in-vitro induction of human regulatory T cells: a preliminary study.

PROBLEM Given the important role of regulatory T cells (Treg) for successful pregnancy, the ability of soluble maternal and fetal pregnancy factors to induce human Treg was investigated. METHOD OF STUDY Peripheral blood mononuclear cells (PBMCs) or isolated CD4+CD25‒ cells were cultured in the presence of pooled second or third trimester pregnancy sera, steroid hormones or supernatants from placental explants, and the numbers and function of induced CD4+CD25+FOXP3+ Treg were analysed. RESULTS Third trimester pregnancy sera and supernatants of early placental explants, but not sex steroid hormones, induced an increase of Tregs from PBMCs. Early placental supernatant containing high levels of tumour necrosis factor-α, interferon-γ, interleukins -1, -6 and -17, soluble human leucocyte antigen-G, and transforming growth factor-β1, increased the proportion of Treg most effectively and was able to induce interleukin-10-secreting-Treg from CD4+CD25‒cells. CONCLUSIONS Compared with circulating maternal factors, placental- and fetal-derived factors appear to exert a more powerful effect on numerical changes of Treg, thereby supporting fetomaternal tolerance during human pregnancy.

Differential diagnosis of the honey bee trypanosomatids Crithidia mellificae and Lotmaria passim

Trypanosomatids infecting honey bees have been poorly studied with molecular methods until recently. After the description of Crithidia mellificae (Langridge and McGhee, 1967) it took about forty years until molecular data for honey bee trypanosomatids became available and were used to identify and describe a new trypanosomatid species from honey bees, Lotmaria passim (Evans and Schwarz, 2014). However, an easy method to distinguish them without sequencing is not yet available. Research on the related bumble bee parasites Crithidia bombi and Crithidia expoeki revealed a fragment length polymorphism in the internal transcribed spacer 1 (ITS1), which enabled species discrimination. In search of fragment length polymorphisms for differential diagnostics in honey bee trypanosomatids, we studied honey bee trypanosomatid cell cultures of C. mellificae and L. passim. This research resulted in the identification of fragment length polymorphisms in ITS1 and ITS1-2 markers, which enabled us to develop a diagnostic method to differentiate both honey bee trypanosomatid species without the need for sequencing. However, the amplification success of the ITS1 marker depends probably on the trypanosomatid infection level. Further investigation confirmed that L. passim is the dominant species in Belgium, Japan and Switzerland. We found C. mellificae only rarely in Belgian honey bee samples, but not in honey bee samples from other countries. C. mellificae was also detected in mason bees (Osmia bicornis and Osmia cornuta) besides in honey bees. Further, the characterization and comparison of additional markers from L. passim strain SF (published as C. mellificae strain SF) and a Belgian honey bee sample revealed very low divergence in the 18S rRNA, ITS1-2, 28S rRNA and cytochrome b sequences. Nevertheless, a variable stretch was observed in the gp63 virulence factor.

A LAPLACE TRANSFORM PAIR MODEL TO DETERMINE BREMSSTRAHLUNG SPECTRA FROM ATTENUATION DATA (RADIATION, X-RAY, SPECTRAL MODELING)

Every x-ray attenuation curve inherently contains all the information necessary to extract the complete energy spectrum of a beam. To date, attempts to obtain accurate spectral information from attenuation data have been inadequate.^ This investigation presents a mathematical pair model, grounded in physical reality by the Laplace Transformation, to describe the attenuation of a photon beam and the corresponding bremsstrahlung spectral distribution. In addition the Laplace model has been mathematically extended to include characteristic radiation in a physically meaningful way. A method to determine the fraction of characteristic radiation in any diagnostic x-ray beam was introduced for use with the extended model.^ This work has examined the reconstructive capability of the Laplace pair model for a photon beam range of from 50 kVp to 25 MV, using both theoretical and experimental methods.^ In the diagnostic region, excellent agreement between a wide variety of experimental spectra and those reconstructed with the Laplace model was obtained when the atomic composition of the attenuators was accurately known. The model successfully reproduced a 2 MV spectrum but demonstrated difficulty in accurately reconstructing orthovoltage and 6 MV spectra. The 25 MV spectrum was successfully reconstructed although poor agreement with the spectrum obtained by Levy was found.^ The analysis of errors, performed with diagnostic energy data, demonstrated the relative insensitivity of the model to typical experimental errors and confirmed that the model can be successfully used to theoretically derive accurate spectral information from experimental attenuation data. ^

Continued Fraction Solutions to Hermite's, Legendre's and Laguerre's Differential Equation

The continued fraction method for solving differential equations is illustrated using three famous differential equations used in quantum chemistry.

Explicit and Implicit Methods In Solving Differential Equations

Differential equations are equations that involve an unknown function and derivatives. Euler's method are efficient methods to yield fairly accurate approximations of the actual solutions. By manipulating such methods, one can find ways to provide good approximations compared to the exact solution of parabolic partial differential equations and nonlinear parabolic differential equations.

Comparison of multiple comparison methods for identifying differential gene expression in simulated and real papillary thyroid cancer microarray data

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.^

Detecting genetic and nutritional lung cancer risk factors related to folate metabolism using Bayesian generalized linear models

Complex diseases, such as cancer, are caused by various genetic and environmental factors, and their interactions. Joint analysis of these factors and their interactions would increase the power to detect risk factors but is statistically. Bayesian generalized linear models using student-t prior distributions on coefficients, is a novel method to simultaneously analyze genetic factors, environmental factors, and interactions. I performed simulation studies using three different disease models and demonstrated that the variable selection performance of Bayesian generalized linear models is comparable to that of Bayesian stochastic search variable selection, an improved method for variable selection when compared to standard methods. I further evaluated the variable selection performance of Bayesian generalized linear models using different numbers of candidate covariates and different sample sizes, and provided a guideline for required sample size to achieve a high power of variable selection using Bayesian generalize linear models, considering different scales of number of candidate covariates. ^ Polymorphisms in folate metabolism genes and nutritional factors have been previously associated with lung cancer risk. In this study, I simultaneously analyzed 115 tag SNPs in folate metabolism genes, 14 nutritional factors, and all possible genetic-nutritional interactions from 1239 lung cancer cases and 1692 controls using Bayesian generalized linear models stratified by never, former, and current smoking status. SNPs in MTRR were significantly associated with lung cancer risk across never, former, and current smokers. In never smokers, three SNPs in TYMS and three gene-nutrient interactions, including an interaction between SHMT1 and vitamin B12, an interaction between MTRR and total fat intake, and an interaction between MTR and alcohol use, were also identified as associated with lung cancer risk. These lung cancer risk factors are worthy of further investigation.^

BIOMEDICAL LANGUAGE UNDERSTANDING AND EXTRACTION (BLUE-TEXT): A MINIMAL SYNTACTIC, SEMANTIC METHOD

Clinical text understanding (CTU) is of interest to health informatics because critical clinical information frequently represented as unconstrained text in electronic health records are extensively used by human experts to guide clinical practice, decision making, and to document delivery of care, but are largely unusable by information systems for queries and computations. Recent initiatives advocating for translational research call for generation of technologies that can integrate structured clinical data with unstructured data, provide a unified interface to all data, and contextualize clinical information for reuse in multidisciplinary and collaborative environment envisioned by CTSA program. This implies that technologies for the processing and interpretation of clinical text should be evaluated not only in terms of their validity and reliability in their intended environment, but also in light of their interoperability, and ability to support information integration and contextualization in a distributed and dynamic environment. This vision adds a new layer of information representation requirements that needs to be accounted for when conceptualizing implementation or acquisition of clinical text processing tools and technologies for multidisciplinary research. On the other hand, electronic health records frequently contain unconstrained clinical text with high variability in use of terms and documentation practices, and without commitmentto grammatical or syntactic structure of the language (e.g. Triage notes, physician and nurse notes, chief complaints, etc). This hinders performance of natural language processing technologies which typically rely heavily on the syntax of language and grammatical structure of the text. This document introduces our method to transform unconstrained clinical text found in electronic health information systems to a formal (computationally understandable) representation that is suitable for querying, integration, contextualization and reuse, and is resilient to the grammatical and syntactic irregularities of the clinical text. We present our design rationale, method, and results of evaluation in processing chief complaints and triage notes from 8 different emergency departments in Houston Texas. At the end, we will discuss significance of our contribution in enabling use of clinical text in a practical bio-surveillance setting.