Modeling of titanium alloys by using artificial neural networks

Titanium alloy exhibits an excellent combination of bio-compatibility, corrosion resistance, strength and toughness. The microstructure of an alloy influences the properties. The microstructures depend mainly on alloying elements, method of production, mechanical, and thermal treatments. The relationships between these variables and final properties of the alloy are complex, non-linear in nature, which is the biggest hurdle in developing proper correlations between them by conventional methods. So, we developed artificial neural networks (ANN) models for solving these complex phenomena in titanium alloys.

In the present work, ANN models were used for the analysis and prediction of the correlation between the process parameters, the alloying elements, microstructural features, beta transus temperature and mechanical properties in titanium alloys. Sensitivity analysis of trained neural network models were studied which resulted a better understanding of relationships between inputs and outputs. The model predictions and the analysis are well in agreement with the experimental results. The simulation results show that the average output-prediction error by models are less than 5% of the prediction range in more than 95% of the cases, which is quite acceptable for all metallurgical purposes.

Three-dimensional modeling of the human fallopian tube fimbriae

OBJECTIVE: Ovarian cancer is the most lethal gynecological malignancy that affects women. Recent data suggests that the disease may originate in the fallopian fimbriae; however, the anatomical origin of ovarian carcinogenesis remains unclear. This is largely driven by our lack of knowledge regarding the structure and function of normal fimbriae and the relative paucity of models that accurately recapitulate the in vivo fallopian tube. Therefore, a human three-dimensional (3D) culture system was developed to examine the role of the fallopian fimbriae in serous tumorigenesis.

METHODS: Alginate matrix was utilized to support human fallopian fimbriae ex vivo. Fimbriae were cultured with factors hypothesized to contribute to carcinogenesis, namely; H2O2 (1mM) a mimetic of oxidative stress, insulin (5μg/ml) to stimulate glycolysis, and estradiol (E2, 10nM) which peaks before ovulation. Cultures were evaluated for changes in proliferation and p53 expression, criteria utilized to identify potential precursor lesions. Further, secretory factors were assessed after treatment with E2 to identify if steroid signaling induces a pro-tumorigenic microenvironment.

RESULTS: 3D fimbriae cultures maintained normal tissue architecture up to 7days, retaining both epithelial subtypes. Treatment of cultures with H2O2 or insulin significantly induced proliferation. However, p53 stabilization was unaffected by any particular treatment, although it was induced by ex vivo culturing. Moreover, E2-alone treatment significantly induced its canonical target PR and expression of IL8, a factor linked to poor outcome.

CONCLUSIONS: 3D alginate cultures of human fallopian fimbriae provide an important microphysiological model, which can be further utilized to investigate serous tumorigenesis originating from the fallopian tube.

Microphysiological modeling of the reproductive tract: A fertile endeavor

Preclinical toxicity testing in animal models is a cornerstone of the drug development process, yet it is often unable to predict adverse effects and tolerability issues in human subjects. Species-specific responses to investigational drugs have led researchers to utilize human tissues and cells to better estimate human toxicity. Unfortunately, human cell-derived models are imperfect because toxicity is assessed in isolation, removed from the normal physiologic microenvironment. Microphysiological modeling often referred to as 'organ-on-a-chip' or 'human-on-a-chip' places human tissue into a microfluidic system that mimics the complexity of human in vivo physiology, thereby allowing for toxicity testing on several cell types, tissues, and organs within a more biologically relevant environment. Here we describe important concepts when developing a repro-on-a-chip model. The development of female and male reproductive microfluidic systems is critical to sex-based in vitro toxicity and drug testing. This review addresses the biological and physiological aspects of the male and female reproductive systems in vivo and what should be considered when designing a microphysiological human-on-a-chip model. Additionally, interactions between the reproductive tract and other systems are explored, focusing on the impact of factors and hormones produced by the reproductive tract and disease pathophysiology.

The Type IIP Supernova 2012aw in M95: Hydrodynamical Modeling of the Photospheric Phase from Accurate Spectrophotometric Monitoring

We present an extensive optical and near-infrared photometric and spectroscopic campaign of the Type IIP supernova SN 2012aw. The data set densely covers the evolution of SN 2012aw shortly after the explosion through the end of the photospheric phase, with two additional photometric observations collected during the nebular phase, to fit the radioactive tail and estimate the ⁵⁶Ni mass. Also included in our analysis is the previously published Swift UV data, therefore providing a complete view of the ultraviolet-optical- infrared evolution of the photospheric phase. On the basis of our data set, we estimate all the relevant physical parameters of SN 2012aw with our radiation-hydrodynamics code: envelope mass M _env ∼ 20 M _⊙, progenitor radius R ∼ 3 × 10¹³ cm (∼430 R_⊙), explosion energy E ∼ 1.5 foe, and initial ⁵⁶Ni mass ∼0.06 M_⊙. These mass and radius values are reasonably well supported by independent evolutionary models of the progenitor, and may suggest a progenitor mass higher than the observational limit of 16.5 ± 1.5 M _⊙of the Type IIP events. 

LIAD-fs: A novel method for studies of ultrafast processes in gas phase neutral biomolecules

A new experimental technique for femtosecond (fs) pulse studies of gas phase biomolecules is reported. Using Laser-Induced Acoustic Desorption (LIAD) to produce a plume of neutral molecules, a time-delayed fs pulse is employed for ionisation/fragmentation, with subsequent products extracted and mass analysed electrostatically. By varying critical laser pulse parameters, this technique can be used to implement control over molecular fragmentation for a range of small biomolecules, with specific studies of amino acids demonstrated.

Finite element modeling of debonding failures in FRP-strengthened RC beams: A dynamic approach

This paper is concerned with the finite element simulation of debonding failures in FRP-strengthened concrete beams. A key challenge for such simulations is that common solution techniques such as the Newton-Raphson method and the arc-length method often fail to converge. This paper examines the effectiveness of using a dynamic analysis approach in such FE simulations, in which debonding failure is treated as a dynamic problem and solved using an appropriate time integration method. Numerical results are presented to show that an appropriate dynamic approach effectively overcomes the convergence problem and provides accurate predictions of test results.