Corrosion Fatigue Behaviour of Laser-welded Shape Memory NiTi Wires in a Simulated Body Fluid

Corrosion fatigue is a fracture process as a consequence of synergistic interactions between the material structure, corrosive environment and cyclic loads/strains. It is difficult to be detected and can cause unexpected failure of engineering components in use. This study reveals a comparison of corrosion fatigue behaviour of laser-welded and bare NiTi wires using bending rotation fatigue (BRF) test coupled with a specifically-designed corrosion cell. The testing medium was Hanks’ solution (simulated body fluid) at 37.5 oC. Electrochemical impedance spectroscopic (EIS) measurement was carried out to monitor the change of corrosion resistance of sample during the BRF test at different periods of time. Experiments indicate that the laser-welded NiTi wire would be more susceptible to the corrosion fatigue attack than the bare NiTi wire. This study can serve as a benchmark for the product designers and engineers to understand the corrosion fatigue behaviour of the NiTi laser weld joint and determine the fatigue life safety factor for NiTi medical devices/implants involving laser welding in the fabrication process.

Measuring the shape of degree distributions

Degree distribution is a fundamental property of networks. While mean degree provides a standard measure of scale, there are several commonly used shape measures. Widespread use of a single shape measure would enable comparisons between networks and facilitate investigations about the relationship between degree distribution properties and other network features. This paper describes five candidate measures of heterogeneity and recommends the Gini coefficient. It has theoretical advantages over many of the previously proposed measures, is meaningful for the broad range of distribution shapes seen in different types of networks, and has several accessible interpretations. While this paper focusses on degree, the distribution of other node based network properties could also be described with Gini coefficients.

Nonsteroidal Anti-Inflammatory Drug Use is Not Associated With Reduced Risk of Barrett’s Esophagus

OBJECTIVES: Regular use of nonsteroidal anti-inflammatory drugs (NSAIDs) is associated with a reduced risk of esophageal adenocarcinoma. Epidemiological studies examining the association between NSAID use and the risk of the precursor lesion, Barrett’s esophagus, have been inconclusive.

METHODS: We analyzed pooled individual-level participant data from six case-control studies of Barrett’s esophagus in the Barrett’s and Esophageal Adenocarcinoma Consortium (BEACON). We compared medication use from 1474 patients with Barrett’s esophagus separately with two control groups: 2256 population-based controls and 2018 gastroesophageal reflux disease (GERD) controls. Study-specific odds ratios (OR) and 95% confidence intervals (CI) were estimated using multivariable logistic regression models and were combined using a random effects meta-analytic model.

RESULTS: Regular (at least once weekly) use of any NSAIDs was not associated with the risk of Barrett’s esophagus (vs. population-based controls, adjusted OR = 1.00, 95% CI = 0.76–1.32; I2=61%; vs. GERD controls, adjusted OR = 0.99, 95% CI = 0.82–1.19; I2=19%). Similar null findings were observed among individuals who took aspirin or non-aspirin NSAIDs. We also found no association with highest levels of frequency (at least daily use) and duration (≥5 years) of NSAID use. There was evidence of moderate between-study heterogeneity; however, associations with NSAID use remained non-significant in “leave-one-out” sensitivity analyses.

CONCLUSIONS: Use of NSAIDs was not associated with the risk of Barrett’s esophagus. The previously reported inverse association between NSAID use and esophageal adenocarcinoma may be through reducing the risk of neoplastic progression in patients with Barrett’s esophagus.

Parametric CAD model based shape optimization using adjoint functions

Adjoint methods have proven to be an efficient way of calculating the gradient of an objective function with respect to a shape parameter for optimisation, with a computational cost nearly independent of the number of the design variables [1]. The approach in this paper links the adjoint surface sensitivities (gradient of objective function with respect to the surface movement) with the parametric design velocities (movement of the surface due to a CAD parameter perturbation) in order to compute the gradient of the objective function with respect to CAD variables.
For a successful implementation of shape optimization strategies in practical industrial cases, the choice of design variables or parameterisation scheme used for the model to be optimized plays a vital role. Where the goal is to base the optimization on a CAD model the choices are to use a NURBS geometry generated from CAD modelling software, where the position of the NURBS control points are the optimisation variables [2] or to use the feature based CAD model with all of the construction history to preserve the design intent [3]. The main advantage of using the feature based model is that the optimized model produced can be directly used for the downstream applications including manufacturing and process planning.
This paper presents an approach for optimization based on the feature based CAD model, which uses CAD parameters defining the features in the model geometry as the design variables. In order to capture the CAD surface movement with respect to the change in design variable, the “Parametric Design Velocity” is calculated, which is defined as the movement of the CAD model boundary in the normal direction due to a change in the parameter value.
The approach presented here for calculating the design velocities represents an advancement in terms of capability and robustness of that described by Robinson et al. [3]. The process can be easily integrated to most industrial optimisation workflows and is immune to the topology and labelling issues highlighted by other CAD based optimisation processes. It considers every continuous (“real value”) parameter type as an optimisation variable, and it can be adapted to work with any CAD modelling software, as long as it has an API which provides access to the values of the parameters which control the model shape and allows the model geometry to be exported. To calculate the movement of the boundary the methodology employs finite differences on the shape of the 3D CAD models before and after the parameter perturbation. The implementation procedure includes calculating the geometrical movement along a normal direction between two discrete representations of the original and perturbed geometry respectively. Parametric design velocities can then be directly linked with adjoint surface sensitivities to extract the gradients to use in a gradient-based optimization algorithm.
The optimisation of a flow optimisation problem is presented, in which the power dissipation of the flow in an automotive air duct is to be reduced by changing the parameters of the CAD geometry created in CATIA V5. The flow sensitivities are computed with the continuous adjoint method for a laminar and turbulent flow [4] and are combined with the parametric design velocities to compute the cost function gradients. A line-search algorithm is then used to update the design variables and proceed further with optimisation process.

Calcium Channel Blocker Use and Risk of Prostate Cancer by TMPRSS2:ERG Gene Fusion Status

BACKGROUND: Calcium channel blockers (CCBs) may affect prostate cancer (PCa) growth by various mechanisms including those related to androgens. The fusion of the androgen-regulated gene TMPRSS2 and the oncogene ERG (TMPRSS2:ERG or T2E) is common in PCa, and prostate tumors that harbor the gene fusion are believed to represent a distinct disease subtype. We studied the association of CCB use with the risk of PCa, and molecular subtypes of PCa defined by T2E status.

METHODS: Participants were residents of King County, Washington, recruited for population-based case-control studies (1993-1996 or 2002-2005). Tumor T2E status was determined by fluorescence in situ hybridization using tumor tissue specimens from radical prostatectomy. Detailed information on use of CCBs and other variables was obtained through in-person interviews. Binomial and polytomous logistic regression were used to generate odds ratios (ORs) and 95% confidence intervals (CIs).

RESULTS: The study included 1,747 PCa patients and 1,635 age-matched controls. A subset of 563 patients treated with radical prostatectomy had T2E status determined, of which 295 were T2E positive (52%). Use of CCBs (ever vs. never) was not associated with overall PCa risk. However, among European-American men, users had a reduced risk of higher-grade PCa (Gleason scores ≥7: adjusted OR = 0.64; 95% CI: 0.44-0.95). Further, use of CCBs was associated with a reduced risk of T2E positive PCa (adjusted OR = 0.38; 95% CI: 0.19-0.78), but was not associated with T2E negative PCa.

CONCLUSIONS: This study found suggestive evidence that use of CCBs is associated with reduced relative risks for higher Gleason score and T2E positive PCa. Future studies of PCa etiology should consider etiologic heterogeneity as PCa subtypes may develop through different causal pathways.