Influence of the tensile static preload dependency on the dynamic lifetime prediction for an HNBR elastomer

A correlated lifetime prediction concept for load cases without static preload, which argues with crack growth and particle size distribution from 3D computer tomography, has been shown by Ludwig et al. (2015). This method is extended to non-relaxing load cases i.e. with a static preload dependency. A force controlled dynamic fatigue test for a dumbbell specimen is performed to investigate the service life. In addition, a crack growth investigation is carried out using single edge notched tensile (SENT) specimens in displacement control mode to characterize the tearing energy and crack growth rate. The study with carbon black reinforced HNBR rubber shows a correlation between the Wöhler curve and the Paris-Erdogan plot. An extension of the empirical Paris-Erdogan equation considering static preload dependency allows the prediction of uniaxial lifetime statistics by means of particle size distribution. The calculated lifetime values are in reasonable concordance with the experimental findings.

Prediction of individual life-years gained without cardiovascular events from lipid, blood pressure, glucose, and aspirin treatment based on data of more than 500 000 patients with Type 2 diabetes mellitus

AIMS

Although group-level effectiveness of lipid, blood pressure, glucose, and aspirin treatment for prevention of cardiovascular disease (CVD) has been proven by trials, important differences in absolute effectiveness exist between individuals. We aim to develop and validate a prediction tool for individualizing lifelong CVD prevention in people with Type 2 diabetes mellitus (T2DM) predicting life-years gained without myocardial infarction or stroke.

METHODS AND RESULTS

We developed and validated the Diabetes Lifetime-perspective prediction (DIAL) model, consisting of two complementary competing risk adjusted Cox proportional hazards functions using data from people with T2DM registered in the Swedish National Diabetes Registry (n = 389 366). Competing outcomes were (i) CVD events (vascular mortality, myocardial infarction, or stroke) and (ii) non-vascular mortality. Predictors were age, sex, smoking, systolic blood pressure, body mass index, haemoglobin A1c, estimated glomerular filtration rate, non- high-density lipoprotein cholesterol, albuminuria, T2DM duration, insulin treatment, and history of CVD. External validation was performed using data from the ADVANCE, ACCORD, ASCOT and ALLHAT-LLT-trials, the SMART and EPIC-NL cohorts, and the Scottish diabetes register (total n = 197 785). Predicted and observed CVD-free survival showed good agreement in all validation sets. C-statistics for prediction of CVD were 0.83 (95% confidence interval: 0.83-0.84) and 0.64-0.65 for internal and external validation, respectively. We provide an interactive calculator at www.U-Prevent.com that combines model predictions with relative treatment effects from trials to predict individual benefit from preventive treatment.

CONCLUSION

Cardiovascular disease-free life expectancy and effects of lifelong prevention in terms of CVD-free life-years gained can be estimated for people with T2DM using readily available clinical characteristics. Predictions of individual-level treatment effects facilitate translation of trial results to individual patients.

Kinetics of thermal degradation and lifetime study of poly(vinylidene fluoride) (PVDF) subjected to bioethanol fuel accelerated aging

PVDF was prepared by compression molding, and its phase content/structure was assessed by WAXD, DSC, and FTIR-ATR spectroscopy. Next, PVDF samples were aged in bioethanol fuel at 60 °C or annealed in the same temperature by 30 ─ 180 days. Then, the influence of aging/annealing on thermal stability, thermal degradation kinetics, and lifetime of the PVDF was investigated by thermogravimetric analysis (TGA/DTG), as well as the structure was again examined. The crystallinity of ~41% (from WAXD) or ~49% (from DSC) were identified for unaged PVDF, without significant changes after aging or annealing. This PVDF presented not only one phase, but a mixture of α-, β- and γ-phases, α- and β-phases with more highlighted vibrational bands. Thermal degradation kinetics was evaluated using the non-isothermal Ozawa-Flynn-Wall method. The activation energy (E _a ) of thermal degradation was calculated for conversion levels of α = 5 ─ 50% at constant heating rates (5, 10, 20, and 40 °C min^─1), α = 10% was fixed for lifetime estimation. The results indicated that temperature alone does not affect the material, but its combination with bioethanol reduced the onset temperature and E _a of primary thermal degradation. Additionally, the material lifetime decreased until about five decades (T _f = 25 °C and 90 days of exposition) due to the fluid effect after aging.

Prediction of individualized lifetime benefit from cholesterol lowering, blood pressure lowering, antithrombotic therapy, and smoking cessation in apparently healthy people

AIMS

The benefit an individual can expect from preventive therapy varies based on risk-factor burden, competing risks, and treatment duration. We developed and validated the LIFEtime-perspective CardioVascular Disease (LIFE-CVD) model for the estimation of individual-level 10 years and lifetime treatment-effects of cholesterol lowering, blood pressure lowering, antithrombotic therapy, and smoking cessation in apparently healthy people.

METHODS AND RESULTS

Model development was conducted in the Multi-Ethnic Study of Atherosclerosis (n = 6715) using clinical predictors. The model consists of two complementary Fine and Gray competing-risk adjusted left-truncated subdistribution hazard functions: one for hard cardiovascular disease (CVD)-events, and one for non-CVD mortality. Therapy-effects were estimated by combining the functions with hazard ratios from preventive therapy trials. External validation was performed in the Atherosclerosis Risk in Communities (n = 9250), Heinz Nixdorf Recall (n = 4177), and the European Prospective Investigation into Cancer and Nutrition-Netherlands (n = 25 833), and Norfolk (n = 23 548) studies. Calibration of the LIFE-CVD model was good and c-statistics were 0.67-0.76. The output enables the comparison of short-term vs. long-term therapy-benefit. In two people aged 45 and 70 with otherwise identical risk-factors, the older patient has a greater 10-year absolute risk reduction (11.3% vs. 1.0%) but a smaller gain in life-years free of CVD (3.4 vs. 4.5 years) from the same therapy. The model was developed into an interactive online calculator available via www.U-Prevent.com.

CONCLUSION

The model can accurately estimate individual-level prognosis and treatment-effects in terms of improved 10-year risk, lifetime risk, and life-expectancy free of CVD. The model is easily accessible and can be used to facilitate personalized-medicine and doctor-patient communication.

A regression-tree multilayer-perceptron hybrid strategy for the prediction of ore crushing-plate lifetimes

Highly tensile manganese steel is in great demand owing to its high tensile strength under shock loads. All workpieces are produced through casting, because it is highly difficult to machine. The probabilistic aspects of its casting, its variable composition, and the different casting techniques must all be considered for the optimisation of its mechanical properties. A hybrid strategy is therefore proposed which combines decision trees and artificial neural networks (ANNs) for accurate and reliable prediction models for ore crushing plate lifetimes. The strategic blend of these two high-accuracy prediction models is used to generate simple decision trees which can reveal the main dataset features, thereby facilitating decision-making. Following a complexity analysis of a dataset with 450 different plates, the best model consisted of 9 different multilayer perceptrons, the inputs of which were only the Fe and Mn plate compositions. The model recorded a low root mean square error (RMSE) of only 0.0614 h for the lifetime of the plate: a very accurate result considering their varied lifetimes of between 746 and 6902 h in the dataset. Finally, the use of these models under real industrial conditions is presented in a heat map, namely a 2D representation of the main manufacturing process inputs with a colour scale which shows the predicted output, i.e. the expected lifetime of the manufactured plates. Thus, the hybrid strategy extracts core training dataset information in high-accuracy prediction models. This novel strategy merges the different capabilities of two families of machine-learning algorithms. It provides a high-accuracy industrial tool for the prediction of the full lifetime of highly tensile manganese steel plates. The results yielded a precision prediction of (RMSE of 0.061 h) for the full lifetime of (light, medium, and heavy) crusher plates manufactured with the three (experimental, classic, and highly efficient (new)) casting methods.