Usability of the ECAP-Conform process for the production of dental implants material.

This study addresses the applicability of the ECAP-Conform process for the production of strengthened titanium to produce dental implants. For this purpose, the commercially pure titanium (CP-Ti) grade 2 was subjected to the ECAP-Conform process with a square cross-section die (at a temperature of 240 °C). This process improved the mechanical properties of CP-Ti grade 2 after one pass, such that both strength and hardness have increased by 35%. The functional properties of dental implants produced from the strengthened titanium and the as-received CP-Ti were compared. It was found that the average grain was reduced from 8.35 µm to 2.35 µm after one pass ECAP-Conform process (i.e. about 72% reduction in grain size). Also, the strength and energy absorption of CP-Ti dental implants made after one pass ECAP-Conform increased by 53% and 139%, respectively.

Correction to: The Capacity of Generic Musculoskeletal Simulations to Predict Knee Joint Loading Using the CAMS-Knee Datasets.

The article The Capacity of Generic Musculoskeletal Simulations to Predict Knee Joint Loading Using the CAMS-Knee Datasets, written by Zohreh Imani Nejad et al., was originally published electronically on the publisher's internet portal on January 30, 2020 without open access. With the author(s)' decision to opt for Open Choice the copyright of the article changed on February 18, 2020 to © The Author(s) 2020 and the article is forthwith distributed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.

The Capacity of Generic Musculoskeletal Simulations to Predict Knee Joint Loading Using the CAMS-Knee Datasets.

Musculoskeletal models enable non-invasive estimation of knee contact forces (KCFs) during functional movements. However, the redundant nature of the musculoskeletal system and uncertainty in model parameters necessitates that model predictions are critically evaluated. This study compared KCF and muscle activation patterns predicted using a scaled generic model and OpenSim static optimization tool against in vivo measurements from six patients in the CAMS-knee datasets during level walking and squatting. Generally, the total KCFs were under-predicted (RMS: 47.55%BW, R2: 0.92) throughout the gait cycle, but substiantially over-predicted (RMS: 105.7%BW, R2: 0.81) during squatting. To understand the underlying etiology of the errors, muscle activations were compared to electromyography (EMG) signals, and showed good agreement during level walking. For squatting, however, the muscle activations showed large descrepancies especially for the biceps femoris long head. Errors in the predicted KCF and muscle activation patterns were greatest during deep squat. Hence suggesting that the errors mainly originate from muscle represented at the hip and an associated muscle co-contraction at the knee. Furthermore, there were substaintial differences in the ranking of subjects and activities based on peak KCFs in the simulations versus measurements. Thus, future simulation study designs must account for subject-specific uncertainties in musculoskeletal predictions.

A Fast and Low-Cost Human Body 3D Scanner Using 100 Cameras.

The human body is one of the most complicated objects to model because of its complex features, non-rigidity, and the time required to take body measurements. Basic technologies available in this field range from small and low-cost scanners that must be moved around the body to large and high-cost scanners that can capture all sides of the body simultaneously. This paper presents an image-based scanning system which employs the structure-from-motion method. The design and development process of the scanner includes its physical structure, electronic components, and the algorithms used for extracting 3D data. In addition to the accuracy, which is one of the main parameters to consider when choosing a 3D scanner, the time and cost of the system are among the most important parameters for evaluating a scanner system in the field of human scanning. Because of the non-static nature of the human body, the scanning time is particularly important. On the other hand, a high-cost system may lead to limited use of such systems. The design developed in this paper, which utilizes 100 cameras, facilitates the acquisition of geometric data in a fraction of a second (0.001 s) and provides the capabilities of large, freestanding scanners at a price akin to that of smaller, mobile ones.