High speed fracture fixation: assessing resulting fixation stability and fastener withdrawal strength.

A new method of bone fracture fixation has been developed in which fixation darts (small diameter nails/pins) are driven across a fracture site at high velocity with a pneumatically powered gun. When fixation darts are inserted oblique to one another, kinematic constraints prevent fragment motion and allow bone healing to progress. The primary aim of this study is to determine if fixation darts can provide reasonable fixation stability compared to bone screws, which were used as a benchmark since they represent a simple, yet well-established, surgical technique. The first objective was to evaluate macro-level stability using different numbers of darts inserted parallel and oblique to each other; experimental comparisons were undertaken in a bone analog model. Experimental results showed fixation darts could not be substituted for screws on a one-to-one basis, but that a plurality of fixation darts provided comparable fixation to two bone screws while allowing for faster insertion and damaging less bone. A second objective was to evaluate micro-level stability; a finite element model was created in order to provide a detailed look at the stress state surrounding the fixation darts and the evolution of the fracture gap. Even with relatively weak fixation dart configurations, the fracture gap was maintained below physiological thresholds for bone healing. Most failures of the fixed fractures were attributed to fixation dart pullout from the cancellous structure. The final objective of the study was to characterize this mode of failure with separate fixation dart and screw pullout tests conducted in Sawbones® cancellous foam and fresh porcine cancellous bone. The results showed that the cancellous foam was an acceptable substitute for real bone and provided a conservative estimate of the fixation darts' performance relative to bone screws. A final comparison between experimental and numerically predicted pullout strengths provided confirmation that the model and experiments were consistent.

Use of a Novel Polymer-Coated Steel as an Alternative to Traditional Can Manufacturing in the Food Industry.

Metal containers (both food and beverage cans) are made from huge steel or aluminum coils that are transformed into two- or three-piece products. During the manufacturing process, the metal is sprayed on both sides and the aerosol acts as insulation, but unfortunately produces volatile organic compounds (VOCs). The present work presents a different way to manufacture these containers using a novel prelaminated two-layer polymer steel. It was experimentally possible to verify that the material survives all the involved manufacturing processes. Thus tests were carried out in an ironing simulator to measure roughness, friction coefficient and surface quality. In addition, two theoretical ironing models were developed: upper bound model and artificial neural network. These models are useful for packaging designers and manufacturers.

An Efficient COVID-19 Prediction Model Validated with the Cases of China, Italy and Spain: Total or Partial Lockdowns?

The present work develops an accurate prediction model of the COVID-19 pandemic, capable not only of fitting data with a high regression coefficient but also to predict the overall infections and the infection peak day as well. The model is based on the Verhulst equation, which has been used to fit the data of the COVID-19 spread in China, Italy, and Spain. This model has been used to predict both the infection peak day, and the total infected people in Italy and Spain. With this prediction model, the overall infections, the infection peak, and date can accurately be predicted one week before they occur. According to the study, the infection peak took place on 23 March in Italy, and on 29 March in Spain. Moreover, the influence of the total and partial lockdowns has been studied, without finding any meaningful difference in the disease spread. However, the infected population, and the rate of new infections at the start of the lockdown, seem to play an important role in the infection spread. The developed model is not only an important tool to predict the disease spread, but also gives some significant clues about the main factors that affect to the COVID-19 spread, and quantifies the effects of partial and total lockdowns as well.