Nicotine Affects Murine Aortic Stiffness and Fatigue Response During Supraphysiological Cycling

Nicotine exposure is a major risk factor for several cardiovascular diseases. Although the deleterious effects of nicotine on aortic remodeling processes have been studied to some extent, the biophysical consequences are not fully elucidated. In this investigation, we applied quasi-static and dynamic loading to quantify ways in which exposure to nicotine affects mechanical behavior of murine arterial tissue. Segments of thoracic aortas from C57BL/6 mice exposed to 25 mg/kg/day of subcutaneous nicotine for 28 days were subjected to uniaxial tensile loading in an open-circumferential configuration. Comparing aorta segments from nicotine-treated mice relative to an equal number of control counterparts, stiffness in the circumferential direction was nearly two-fold higher (377 kPa ± 165 kPa vs. 191 kPa ± 65 kPa, n = 5, p = 0.03) at 50% strain. Using a degradative power-law fit to fatigue data at supraphysiological loading, we observed that nicotine-treated aortas exhibited significantly higher peak stress, greater loss of tension, and wider oscillation band than control aortas (p = 0.01 for all three variables). Compared to simple stress relaxation tests, fatigue cycling is shown to be more sensitive and versatile in discerning nicotine-induced changes in mechanical behavior over many cycles. Supraphysiological fatigue cycling thus may have broader potential to reveal subtle changes in vascular mechanics caused by other exogenous toxins or pathological conditions.

Is Coulomb Stress the Best Choice for Aftershock Forecasting?

<p>The Coulomb failure stress (CFS) criterion is the most commonly used method for predicting spatial distributions of aftershocks following large earthquakes. However, large uncertainties are always associated with the calculation of Coulomb stress change. The uncertainties mainly arise due to nonunique slip inversions and unknown receiver faults; especially for the latter, results are highly dependent on the choice of the assumed receiver mechanism. Based on binary tests (aftershocks yes/no), recent studies suggest that alternative stress quantities, a distance‐slip probabilistic model as well as deep neural network (DNN) approaches, all are superior to CFS with predefined receiver mechanism. To challenge this conclusion, which might have large implications, we use 289 slip inversions from SRCMOD database to calculate more realistic CFS values for a layered half‐space and variable receiver mechanisms. We also analyze the effect of the magnitude cutoff, grid size variation, and aftershock duration to verify the use of receiver operating characteristic (ROC) analysis for the ranking of stress metrics. The observations suggest that introducing a layered half‐space does not improve the stress maps and ROC curves. However, results significantly improve for larger aftershocks and shorter time periods but without changing the ranking. We also go beyond binary testing and apply alternative statistics to test the ability to estimate aftershock numbers, which confirm that simple stress metrics perform better than the classic Coulomb failure stress calculations and are also better than the distance‐slip probabilistic model.</p>

Tahapan Desain dan Implementasi Model Machine Learning untuk Sistem Tertanam

machine learning and edge computing currently becomes popular technology used in any discipline. Flexibility and adapt to the problem are the main advantages of its technology. In this paper, we explain step-by-step way to make a lightweight machine learning model especially intended for embedded system application. We use open source machine learning tool called as Weka to design the model. Moreover, we performed a simple stress recognition experiment to make our own dataset for evaluation. We evaluate algorithm complexity and accuracy for different well-known classifier such as support vector machine, simple logistic and hoeffding tree.

Behavior of the Abaqus CDP model in simple stress states

In order to use the Abaqus Concrete Damaged Plasticity (CDP) material model in simulations of reinforced concrete structures, one has to understand the effect of various parameters of the material model. Although most of the material parameters can be determined from standard concrete tests, some parameters need more advanced tests to be determined. In impact simulations, one often has only limited material data available, and it makes therefore sense to study the parameter sensitivity of the material model in order to fix realistic parameter values. In this paper, the sensitivity of the simulation response with respect to two modelparameters is studied: the dilation angle and the tensile to compressive meridian ratio. The sensitivity study is performed in three simple but representative stress states: the uniaxial tension state, the confined uniaxial compressive state and the pure shear state. Finally, it is discussed how these simple stress states relate to the element removal criteria, which is necessary in simulations involving fragmentation.