A model of polymer degradation and erosion for finite element analysis of bioresorbable implants

Finite element analysis is a powerful tool for the design of bioresorbable medical implants made of aliphatic polyesters such as bioresorbable vascular scaffolds. However polymer erosion has been traditionally modelled using empirical rules rather than differential equations. The rule-based models are difficult to implement in a finite element analysis. Consequently, these models have been limited to simple geometries such as plates or spheres. This paper presents a set of differential equations that govern the hydrolytic chain scission and bulk erosion of bioresorbable implants where polymer erosion is modelled using a differential equation instead of empirical rules. These differential equations can be conveniently solved using a commercial finite element package to calculate the molecular weight and mass loss as functions of time for bioresorbable implant made of aliphatic polyesters. A case study of Absorb bioresorbable vascular scaffolds (BVSs) is presented using data obtained from the literature, where 98 Absorb BVSs were implanted in 40 porcine coronary arteries. It is demonstrated that the finite element model can fit the data of both molecular weight and mass loss as functions of time to an accuracy of approximately 5%. The finite element model and the back-calculated model parameters can be used to design future implants that degrade in a controlled pattern with required mechanical performance

Spatio-temporal attention model for foreground detection in cross-scene surveillance videos

Foreground detection is an important theme in video surveillance. Conventional background modeling approaches build sophisticated temporal statistical model to detect foreground based on low-level features, while modern semantic/instance segmentation approaches generate high-level foreground annotation, but ignore the temporal relevance among consecutive frames. In this paper, we propose a Spatio-Temporal Attention Model (STAM) for cross-scene foreground detection. To fill the semantic gap between low and high level features, appearance and optical flow features are synthesized by attention modules via the feature learning procedure. Experimental results on CDnet 2014 benchmarks validate it and outperformed many state-of-the-art methods in seven evaluation metrics. With the attention modules and optical flow, its F-measure increased 9% and 6% respectively. The model without any tuning showed its cross-scene generalization on Wallflower and PETS datasets. The processing speed was 10.8 fps with the frame size 256 by 256

Characterisation and antibacterial investigation of a novel coating consisting of mushroom microstructures and HFCVD graphite

The resistance of bacteria toward antibacterial drugs is a rising problem. This threat is a major concern for space stations, where antibacterial surfaces would be ideal for materials which also need to be corrosion-resistant, hard and durable. Accordingly, the purpose of this work is to investigate novel coatings that have superhydrophobic mushroom microstructures. The microstructures are made of nickel deposited on a substrate which is composed of a gold layer on top of the silicon. The microstructures were fabricated with UV-light assisted nanoimprint lithography. These superhydrophobic microstructures have a well-defined alignment and shape which does not have any detrimental effect on the plastic deformation of the substrate. Similar structures were coated with carbon by hot-filament chemical vapour deposition (HFCVD) for a duration varying from 30 min to 120 min. Raman spectroscopy shows that the coating is composed of graphite, due to nickel-induced graphitisation during the deposition process. The antibacterial evaluation shows the bare nickel microstructures offer no antibacterial properties despite their superhydrophobic behaviour. On the other hand, the graphitic coated microstructures demonstrate significant antibacterial properties. Especially, 30 min HFCVD coated samples was antibacterial against E. coli and S. aureus with Gram-dependence and dependent on the coating deposition duration

Corrosion fatigue of phosphor bronze reinforcing tapes on underground power transmission cables - Failure analysis

This paper is an investigation on the failure mechanism involved in underground power transmission cables with their life limited by corrosion of phosphor bronze reinforcing tapes. In the present work, a detailed analysis of failed bronze tapes in an ammonium free environment has been undertaken and corrosion fatigue failure mechanism has been identified. A detailed examination of the tape samples is carried out using 2D and 3D optical microscopy and SEM. It follows a mechanical approach that confirms corrosion fatigue as the failure mechanism. SEM images reveal that the pits present on the surface could be the starting point for the crack that eventually leads to failure. Stress calculation shows that the tape could fail only if corrosion pits are present on the tape surface. Presence of corrosion pits, multi cracks and striations on the fractured surface demonstrates corrosion fatigue cracking as the failure mechanism across the tape samples

Mechanical properties of 3-D printed polyvinyl alcohol matrix for detection of respiratory pathogens

Polyvinyl alcohol is used to 3D print (fused deposition modelling) sampling matrices for bacterial detection. A specific configuration was designed using Computer-Aided Design software. The mechanical properties of the printed samples were studied using uniaxial tensile testing, and compared to those of the original Polyvinyl alcohol filament, with and without heat treatment. The effects of different factors such as UV treatment, printing speed, infill density and printing direction on the mechanical properties of the printed samples including strength, strain and modulus of elasticity were studied. The results show that the effect of the fused deposition modelling process on the mechanical properties of the printed Polyvinyl alcohol cannot be explained by its exposure to heat. UV treatment reduced the strength, characteristic strains and Young's modulus. It makes Polyvinyl alcohol samples brittle. The effects of printing speed and the infill density on the mechanical properties of printed samples can be no linear. An unexpected relation between printing direction and mechanical properties was demonstrated by the studied specimens that needs further theoretical understanding. There is a huge scatter in strength of PVA samples compared with typical engineering materials, and in the fracture strain of original PVA filament, the 3D printing process can reduce the scatter but only by a limited extent. To summarise, there is a sophisticated relation between printing parameters and the mechanical properties of the printed Polyvinyl alcohol

Score-specific Non-maximum Suppression and Coexistence Prior for Multi-scale Face Detection

Face detection is an ultimate component to support various visual facial related tasks. However, detecting faces with extremely low resolution or high occlusion is still an open problem. In this paper, we propose a two-step general approach to refine the performance of modern face detectors according to human's high-level context-aware ability. First, we propose Score-specific Non-Maximum Suppression (SNMS) to preserve overlapped faces. Second, we consider the coexistence prior among faces in the scene, which could raise the sensitivity of face detection in the crowd. When integrating our approach to the existing face detectors, most of them have better results on a challenging benchmark (WIDER FACE) and a newly proposed dataset (Faces in Crowd, FIC) made by us. Codes are available on https://github.com/AIoTP/SNMSandCoexistence