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- Abdominal appendages (1)
- Additive manufacturing (AM) (1)
- Adult insects (1)
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Organisationseinheit der BAM
Despite their enormous diversity, the bauplan of adult winged insects (pterygotes) is remarkably conservative since the Lower Devonian: a five-segmented head, a three-segmented thorax with three pairs of walking legs and an eleven-segmented abdomen without any non-sexual appendages 1 and 2. The only known exceptions are the abdominal appendages of adult male sepsid flies on the fourth segment; however, these are also used as copulatory organs and are supposedly maintained through sexual selection [3]. Here, we report a rod-like paired appendage from the third and fourth abdominal segments in adults of the Southeast-Asian Hemiptera taxon Bennini (Figure 1A,B; Supplemental information). These are fully musculated, innervated, and movable and bear highly organized sensory and secretory units. The appendages, termed LASSO (lateral abdominal sensory and secretory organs), are consistent in topology and structure in all species studied and not sexually dimorphic. The existence of these non-sexual abdominal appendages reveals the potential of the 300 million year old conserved bauplan of insects.
During the last decades, X-ray (micro-)computed tomography has gained increasing attention for the description of porous skeletal and shell structures of various organism groups. However, their quantitative analysis is often hampered by the difficulty to discriminate cavities and pores within the object from the surrounding region. Herein, we test the ambient occlusion (AO) algorithm and newly implemented optimisations for the segmentation of cavities (implemented in the software Amira). The segmentation accuracy is evaluated as a function of (i) changes in the ray length input variable, and (ii) the usage of AO (scalar) field and other AO-derived (scalar) fields. The results clearly indicate that the AO field itself outperforms all other AO-derived fields in terms of segmentation accuracy and robustness against variations in the ray length input variable. The newly implemented optimisations improved the AO field-based segmentation only slightly, while the segmentations based on the AOderived fields improved considerably.
Additionally, we evaluated the potential of the AO field and AO-derived fields for the separation and classification of cavities as well as skeletal structures by comparing them with commonly used distance-map-based segmentations. For this, we tested the zooid separation within a bryozoan colony, the stereom classification of an ophiuroid tooth, the separation of bioerosion traces within a marble block and the calice (central cavity)-pore separation within a dendrophyllid coral. The obtained results clearly indicate that the ideal input field depends on the three-dimensional morphology of the object of interest. The segmentations based on the AO-derived fields often provided cavity separations and skeleton classifications that were superior to or impossible to obtain with commonly used distance-map-based segmentations. The combined usage of various AO-derived fields by supervised or unsupervised segmentation algorithms might provide a promising target for future research to further improve the results for this kind of high-end data segmentation and classification. Furthermore, the application of the developed segmentation algorithm is not restricted to X-ray (micro-)computed tomographic data but may potentially be useful for the segmentation of 3D volume data from other sources.
Objectives. There is concern that the integrity of fiberglass dental posts may be affected by chairside trimming during treatment. We hypothesize that hard X-ray methods of phase contrast-enhanced micro-CT (PCE-CT) and synchrotron based X-ray refraction (SXRR) can reliably identify and help characterize the extent of damage.
Methods. Fiberglass posts were imaged both as manufactured and following trimming with a diamond bur. Each of the posts was imaged by SXRR and by PCE-CT. Datasets from PCE-CT were used to visualize and quantify 2D and 3D morphological characteristics of intact and of damage-affected regions caused by trimming. Results. The SXRR images revealed fiber inhomogeneities from manufacturing with a significant increase in internal surfaces in sample regions corresponding to damage from trimming. PCE-CT volumes unveiled the micromorphology of single fibers in the posts and some damage in the trimmed area (e.g. fractures, splinters and cracks). Area, perimeter, circularity, roundness, volume and thickness of the glass fibers in the trimmed area were statistically different from the control (p < 0.01).
Significance. The integrity of single fibers in the post is critical for bending resistance and for long-term adhesion to the cement in the root canals. Damage to the fibers causes substantial structural weakening across the post diameter. Glass fragments produced due to contact with the dental bur may separate from the post and may significantly reduce bond capacity. The above mentioned synchrotron-based imaging techniques can further facilitate assessment of the structural integrity and the appearance of defects in posts (e.g. after mechanical load).
Among additive manufacturing (AM) technologies, the laser powder bed fusion (L-PBF) is one of the most important technologies to produce metallic components. The layer-wise build-up of components and the complex process conditions increase the probability of the occurrence of defects. However, due to the iterative nature of its manufacturing process and in contrast to conventional manufacturing technologies such as casting, L-PBF offers unique opportunities for in-situ monitoring. In this study, two cameras were successfully tested simultaneously as a machine manufacturer independent process monitoring setup: a high-frequency infrared camera and a camera for long time exposure, working in the visible and infrared spectrum and equipped with a near infrared filter. An AISI 316L stainless steel specimen with integrated artificial defects has been monitored during the build. The acquired camera data was compared to data obtained by computed tomography. A promising and easy to use examination method for data analysis was developed and correlations between measured signals and defects were identified. Moreover, sources of possible data misinterpretation were specified. Lastly, attempts for automatic data analysis by data Integration are presented.