PRELIMINARY FINDINGS OF A POTENZIATED PIEZOSURGERGICAL DEVICE AT THE RABBIT SKULL

The number of available ultrasonic osteotomes has remarkably increased. In vitro and in vivo studies have revealed differences between conventional osteotomes, such as rotating or sawing devices, and ultrasound-supported osteotomes (Piezosurgery®) regarding the micromorphology and roughness values of osteotomized bone surfaces. Objective: the present study compares the micro-morphologies and roughness values of osteotomized bone surfaces after the application of rotating and sawing devices, Piezosurgery Medical® and Piezosurgery Medical New Generation Powerful Handpiece. Methods: Fresh, standard-sized bony samples were taken from a rabbit skull using the following osteotomes: rotating and sawing devices, Piezosurgery Medical® and a Piezosurgery Medical New Generation Powerful Handpiece. The required duration of time for each osteotomy was recorded. Micromorphologies and roughness values to characterize the bone surfaces following the different osteotomy methods were described. The prepared surfaces were examined via light microscopy, environmental surface electron microscopy (ESEM), transmission electron microscopy (TEM), confocal laser scanning microscopy (CLSM) and atomic force microscopy. The selective cutting of mineralized tissues while preserving adjacent soft tissue (dura mater and nervous tissue) was studied. Bone necrosis of the osteotomy sites and the vitality of the osteocytes near the sectional plane were investigated, as well as the proportion of apoptosis or cell degeneration. Results and Conclusions: The potential positive effects on bone healing and reossification associated with different devices were evaluated and the comparative analysis among the different devices used was performed, in order to determine the best osteotomes to be employed during cranio-facial surgery

The Use of Maxillary Sinus Imaging as a Tool in Human Identification

The presented research performs evaluations of maxillary sinus morphologies for human identification purpose. Due to the durability of maxillary sinuses, morphological analyses of the structure can prove to be extremely valuable and informative, even when parts of the skull are destroyed and dental records cannot be applied. This research is comprised of 4 studies evaluating maxillary sinus morphologies in order to build a comprehensive outlook on the methodological potentials. In total the used sample is comprised of right and left maxillary sinuses from 988 individuals divided into 12 populations. The morphologies are assessed by extracting the maxillary sinuses from radiographic and CT images and applying elliptic Fourier analyses on the structures. Morphological variability is investigated by converting the maxillary sinus morphology into multiple closed curves, and embedding them into a cartesian system. Principal component analyses on four components further simplifies the processing. The first two studies of this research are concerned with morphological uniqueness testing both in a simulated and real-life scenario to lay a comprehensive foundation for method applicability. Uniqueness testing is executed as a morphological ante- and postmortem comparison by calculating Euclidean and Mahalanobis distances. Euclidean correlation values from 0.000 in the simulated sample up to 0.002 in the real-life sample indicate maxillary sinus morphological uniqueness for each ante- and postmortem sinus morphology pair. Mahalanobis distances are used for visualisation. The third study is assessing the reproducibility of maxillary sinus morphological extraction by applying Cohen’s kappa values. The high kappa values in intra- and inter-observer reliability testing indicate high quality extraction and interpretation of morphologies, increasing the methodological confidence level. Finally, the last study is dedicated to understanding age-related changes in maxillary sinuses by calculating growth rates by population and by sex on Euclidean distances. All evaluations reveal quasi-linear and monotonously rising distances with growth rates varying among left and right sinuses and population. This research advances the potential of maxillary sinus morphologies for human identification and demonstrates its advantages over other paranasal identification methodologies. Therefore, this research acts as an essential first step toward using the proposed methodological framework in future forensic casework

Recent Advances in Forensic Anthropological Methods and Research

Forensic anthropology, while still relatively in its infancy compared to other forensic science disciplines, adopts a wide array of methods from many disciplines for human skeletal identification in medico-legal and humanitarian contexts. The human skeleton is a dynamic tissue that can withstand the ravages of time given the right environment and may be the only remaining evidence left in a forensic case whether a week or decades old. Improved understanding of the intrinsic and extrinsic factors that modulate skeletal tissues allows researchers and practitioners to improve the accuracy and precision of identification methods ranging from establishing a biological profile such as estimating age-at-death, and population affinity, estimating time-since-death, using isotopes for geolocation of unidentified decedents, radiology for personal identification, histology to assess a live birth, to assessing traumatic injuries and so much more

Towards a Conceptual Design of an Intelligent Material Transport Based on Machine Learning and Axiomatic Design Theory

Reliable and efficient material transport is one of the basic requirements that affect productivity in sheet metal industry. This paper presents a methodology for conceptual design of intelligent material transport using mobile robot, based on axiomatic design theory, graph theory and artificial intelligence. Developed control algorithm was implemented and tested on the mobile robot system Khepera II within the laboratory model of manufacturing environment. Matlab© software package was used for manufacturing process simulation, implementation of search algorithms and neural network training. Experimental results clearly show that intelligent mobile robot can learn and predict optimal material transport flows thanks to the use of artificial neural networks. Achieved positioning error of mobile robot indicates that conceptual design approach can be used for material transport and handling tasks in intelligent manufacturing systems