A three-dimensional model for stage I-crack propagation

The propagation of short fatigue cracks is simulated by means of a three-dimensional model. Under loading conditions in the high cycle fatigue regime the growth of these cracks can determine up to 90% of the lifetime of a component. Stage I-cracks often grow on slip bands and exhibit strong interactions with microstructural features such as grain boundaries. Experimental investigations have shown that the crack propagation rate decreases significantly when the crack tip approaches a grain boundary and even a complete stop of crack propagation is possible. In order to consider the real three-dimensional orientation of a slip plane an existing two-dimensional mechanism-based model (Künkler el al., 2008) is extended to simulate the propagation of a three-dimensional surface crack. The crack geometry is modelled using dislocation loops (Hills et al., 1996), which represent the relative displacement between the crack flanks. To describe the propagation of stage Icracks elastic-plastic material behaviour is considered by allowing a plastic deformation due to slip on the active slip plane. The extension of the plastic zone is blocked by the grain boundary. The crack propagation law is based on the range of the crack tip slide displacement, which is obtained from the plastic solution. Behind the grain boundary the shear stress field is evaluated. Results show that a high twist angle between the slip planes causes a significant decrease in the stresses, which can yield a crack stop

Preference rules for label ranking: Mining patterns in multi-target relations

In this paper, we investigate two variants of association rules for preference data, Label Ranking Association Rules and Pairwise Association Rules. Label Ranking Association Rules (LRAR) are the equivalent of Class Association Rules (CAR) for the Label Ranking task. In CAR, the consequent is a single class, to which the example is expected to belong to. In LRAR, the consequent is a ranking of the labels. The generation of LRAR requires special support and confidence measures to assess the similarity of rankings. In this work, we carry out a sensitivity analysis of these similarity-based measures. We want to understand which datasets benefit more from such measures and which parameters have more influence in the accuracy of the model. Furthermore, we propose an alternative type of rules, the Pairwise Association Rules (PAR), which are defined as association rules with a set of pairwise preferences in the consequent. While PAR can be used both as descriptive and predictive models, they are essentially descriptive models. Experimental results show the potential of both approaches.This research has received funding from the ECSEL Joint Undertaking, the framework programme for research and innovation horizon 2020 (2014-2020) under grant agreement number 662189-MANTIS-2014-1, and by National Funds through the FCT — Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) as part of project UID/EEA/50014/2013

Smartspectrometer—embedded optical spectroscopy for applications in agriculture and industry

The ongoing digitization of industry and agriculture can benefit significantly from optical spectroscopy. In many cases, optical spectroscopy enables the estimation of properties such as substance concentrations and compositions. Spectral data can be acquired and evaluated in real time, and the results can be integrated directly into process and automation units, saving resources and costs. Multivariate data analysis is needed to integrate optical spectrometers as sensors. Therefore, a spectrometer with integrated artificial intelligence (AI) called SmartSpectrometer and its interface is presented. The advantages of the SmartSpectrometer are exemplified by its integration into a harvesting vehicle, where quality is determined by predicting sugar and acid in grapes in the field

Plasma Thallium Concentration, Kidney Function, Nephrotoxicity and Graft Failure in Kidney Transplant Recipients

The nephrotoxic effects of heavy metals have gained increasing scientific attention in the past years. Recent studies suggest that heavy metals, including cadmium, lead, and arsenic, are detrimental to kidney transplant recipients (KTR) even at circulating concentrations within the normal range, posing an increased risk for graft failure. Thallium is another highly toxic heavy metal, yet the potential consequences of the circulating thallium concentrations in KTR are unclear. We measured plasma thallium concentrations in 672 stable KTR enrolled in the prospective TransplantLines Food and Nutrition Biobank and Cohort Study using inductively coupled plasma mass spectrometry. In cross-sectional analyses, plasma thallium concentrations were positively associated with kidney function measures and hemoglobin. We observed no associations of thallium concentration with proteinuria or markers of tubular damage. In prospective analyses, we observed no association of plasma thallium with graft failure and mortality during a median follow-up of 5.4 [interquartile range: 4.8 to 6.1] years. In conclusion, in contrast with other heavy metals such as lead, cadmium, and arsenic, there is no evidence of tubular damage or thallium nephrotoxicity for the range of circulating thallium concentrations observed in this study. This is further evidenced by the absence of associations of plasma thallium with graft failure and mortality in KTR

Controllable transport mean free path of light in xerogel matrixes embedded with polystyrene spheres

Xerogel matrices, made by sol-gel techniques, are embedded with polystyrene spheres to promote multiple scattering of light. Varying the concentration of the spheres inside the matrix allows one to adjust the transport mean free path of light inside the material. Coherent backscattering measurements show that a range of transport mean free paths from 90 to 600 nm is easily achieved. The determination of the matrix refractive index permits a direct comparison to multiple scattering and Mie theory. Such tunable diffusive sol-gel derived samples can be further optimized as random laser materials.Comment: Updated figures and correcting typos. 5 pages, 3 figure

A Joint Pharmacokinetic Model for the Simultaneous Description of Plasma and Whole Blood Tacrolimus Concentrations in Kidney and Lung Transplant Recipients

BACKGROUND AND OBJECTIVE: Historically, dosing of tacrolimus is guided by therapeutic drug monitoring (TDM) of the whole blood concentration, which is strongly influenced by haematocrit. The therapeutic and adverse effects are however expected to be driven by the unbound exposure, which could be better represented by measuring plasma concentrations.OBJECTIVE: We aimed to establish plasma concentration ranges reflecting whole blood concentrations within currently used target ranges.METHODS: Plasma and whole blood tacrolimus concentrations were determined in samples of transplant recipients included in the TransplantLines Biobank and Cohort Study. Targeted whole blood trough concentrations are 4-6 ng/mL and 7-10 ng/mL for kidney and lung transplant recipients, respectively. A population pharmacokinetic model was developed using non-linear mixed-effects modelling. Simulations were performed to infer plasma concentration ranges corresponding to whole blood target ranges.RESULTS: Plasma (n = 1973) and whole blood (n = 1961) tacrolimus concentrations were determined in 1060 transplant recipients. A one-compartment model with fixed first-order absorption and estimated first-order elimination characterised observed plasma concentrations. Plasma was linked to whole blood using a saturable binding equation (maximum binding 35.7 ng/mL, 95% confidence interval (CI) 31.0-40.4 ng/mL; dissociation constant 0.24 ng/mL, 95% CI 0.19-0.29 ng/mL). Model simulations indicate that patients within the whole blood target range are expected to have plasma concentrations (95% prediction interval) of 0.06-0.26 ng/mL and 0.10-0.93 ng/mL for kidney and lung transplant recipients, respectively.CONCLUSION: Whole blood tacrolimus target ranges, currently used to guide TDM, were translated to plasma concentration ranges of 0.06-0.26 ng/mL and 0.10-0.93 ng/mL for kidney and lung transplant recipients, respectively.</p

Assessing the Potential of Untargeted SWATH Mass Spectrometry-Based Metabolomics to Differentiate Closely Related Exposures in Observational Studies

Mass spectrometry (MS) is increasingly used in clinical studies to obtain molecular evidence of chemical exposures, such as tobacco smoke, alcohol, and drugs. This evidence can help verify clinical data retrieved through anamnesis or questionnaires and may provide insights into unreported exposures, for example those classified as the same despite small but possibly relevant chemical differences or due to contaminants in reported exposure compounds. Here, we aimed to explore the potential of untargeted SWATH metabolomics to differentiate such closely related exposures. This data-independent acquisition MS-based profiling technique was applied to urine samples of 316 liver and 570 kidney transplant recipients from the TransplantLines Biobank and Cohort Study (NCT03272841), where we focused on the immunosuppressive drug mycophenolate, which is either supplied as a morpholino-ester prodrug or as an enteric-coated product, the illicit drug cocaine, which is usually supplied as an adulterated product, and the proton pump inhibitors omeprazole and esomeprazole. Based on these examples, we found that untargeted SWATH metabolomics has considerable potential to identify different (unreported) exposure or co-exposure metabolites and may determine variations in their abundances. We also found that these signals alone may sometimes be unable to distinguish closely related exposures, and enhancement of differentiation, for example by integration with pharmacogenomics data, is needed