Supervised and Penalized Baseline Correction

Spectroscopic measurements can show distorted spectral shapes arising from a mixture of absorbing and scattering contributions. These distortions (or baselines) often manifest themselves as non-constant offsets or low-frequency oscillations. As a result, these baselines can adversely affect analytical and quantitative results. Baseline correction is an umbrella term where one applies pre-processing methods to obtain baseline spectra (the unwanted distortions) and then remove the distortions by differencing. However, current state-of-the art baseline correction methods do not utilize analyte concentrations even if they are available, or even if they contribute significantly to the observed spectral variability. We examine a class of state-of-the-art methods (penalized baseline correction) and modify them such that they can accommodate a priori analyte concentrations such that prediction can be enhanced. Performance will be assessed on two near infra-red data sets across both classical penalized baseline correction methods (without analyte information) and modified penalized baseline correction methods (leveraging analyte information).Comment: 27 pages; 9 figures; 2 tables; fixed typos; additional sanity checks for grammar and syntax; streamlined text and made minor cosmetic change

Monte Carlo Random Walk Simulations Based on Distributed Order Differential Equations with Applications to Cell Biology

Mathematics Subject Classification: 65C05, 60G50, 39A10, 92C37In this paper the multi-dimensional Monte-Carlo random walk simulation models governed by distributed fractional order differential equations (DODEs) and multi-term fractional order differential equations are constructed. The construction is based on the discretization leading to a generalized difference scheme (containing a finite number of terms in the time step and infinite number of terms in the space step) of the Cauchy problem for DODE. The scaling limits of the constructed random walks to a diffusion process in the sense of distributions is proved

Monte Carlo Random Walk Simulations Based on Distributed Order Differential Equations with Applications in Cell Biology

In this paper the multi-dimensional random walk models governed by distributed fractional order differential equations and multi-term fractional order differential equations are constructed. The scaling limits of these random walks to a diffusion process in the sense of distributions is proved. Simulations based upon multi-term fractional order differential equations are performed

Regularization Adaption Processes for Multivariate Calibration Maintenance

In the field of chemometrics, an important issue in multivariate calibration is model updating. Model updating is the adaption process in which a model obtained for a given set of samples and measurement conditions (primary) is updated to predict the analyte in new samples and measurement conditions (secondary). The calibration method partial least squares is applied with two new updating approaches. In one approach, only one updated model is obtained to predict the analyte amount in both primary and secondary conditions. The other approach forms two updated models in which one model is used to predict in primary conditions and second model based on the first model is used to predict in secondary conditions. Both approaches are evaluated with near-infrared spectral datasets. Datasets include spectra of soil, corn, olive oil adulterated with sunflower and pharmaceutical tablets. Fusion process and single merits are used to select models. Model selection methods are evaluated based on prediction errors using selected models

Fine Tuning Model Updating for Multivariate Calibration Maintenance

In the field of chemometrics, an important issue in multivariate calibration is model updating. Model updating is the adaption process in which a model obtained for a given set of samples and measurement conditions (primary) is updated to predict the analyte in new samples and measurement conditions (secondary). Primary and secondary conditions can be different due to variations in the geographical situation, instrumentation, or environment. Model updating can be performed using labeled data sets containing samples with reference analyte values for both conditions. A common approach is performed by sample augmenting the larger primary labeled sample set with a small weighted secondary labeled sample set. In this situation, only one updating model is obtained to predict the analyte amount in both primary and secondary conditions. The proposed new approach is similar to this common approach, but instead of one updated model, two models are formed simultaneously. One model is used to only predict samples from the primary conditions and the second model is based on this primary model but modified relative to the weighted augmented secondary samples. This second model is used to predict samples from the secondary conditions. Both model updating methods require multiple tuning parameters (penalties)

Potential Use of Antiviral Agents in Polio Eradication

These compounds may serve as starting points for the design of more potent poliovirus inhibitors

The Effect of Histidine-tryptophan-ketoglutarate Solution and University of Wisconsin Solution: An Analysis of the Eurotransplant Registry

Background Both University of Wisconsin (UW) and histidine-tryptophan-ketoglutarate (HTK) solutions are currently used in the Eurotransplant region for preservation of liver allografts. Previous studies on their effect have led to a lot of discussion. This study aims to compare the effect of HTK and UW on graft survival. Methods First liver transplantations in recipients 18 years or older from January 1, 2007, until December 31, 2016, were included. Graft survival was compared for livers preserved with HTK and UW at 30 days, 1, 3, and 5 years. Multivariable analysis of risk factors was performed and outcome was adjusted for important confounders. Results Of all 10 628 first liver transplantations, 8176 (77%) and 2452 (23%) were performed with livers preserved with HTK and UW, respectively. Kaplan-Meier curves showed significant differences in graft survival between HTK and UW at 30 days (89% vs 93%, P=<0.001), 1 year (75% vs 82%, P=<0.001), 3 years (67% vs 72%, P<0.001), and at 5 years (60% vs 67%, P<0.001). No significant differences in outcome were observed in separate analyses of Germany or non-German countries. In multivariable analysis, UW was associated with a decreased risk of graft loss at 30 days (HR 0.772, P=0.002) and at 1 year (0.847 (0.757-0.947). When adjusted for risk factors, no differences in long term outcome could be detected. Conclusions Because the use of preservation fluids is clustered geographically, differences in outcome by preservation fluids are strongly affected by regional differences in donor and recipient characteristics. When adjusted for risk factors, no differences in graft survival exist between transplantations performed with livers preserved with either HTK or UW