3D and 4D printing of polypropylene having different content of copolymer

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Suitability of Recycled PLA Filament Application in Fused Filament Fabrication Process

Fused filament fabrication (FFF) is currently one of the most popular additive manufacturing processes due to its simplicity and low running and material costs. Support structures, which are necessary for overhanging surfaces during production, in most cases need to be manually removed and as such, they become waste material. In this paper, experimental approach is utilised in order to assess suitability of recycling support structures into recycled filament for FFF process. Mechanical properties of standardized specimens made from recycled polylactic acid (PLA) filament as well as influence of layer height and infill density on those properties were investigated. Optimal printing parameters for recycled PLA filaments are determined with Design of Experiment methods (DOE)

Leveraging Diffusion-Based Image Variations for Robust Training on Poisoned Data

Backdoor attacks pose a serious security threat for training neural networks as they surreptitiously introduce hidden functionalities into a model. Such backdoors remain silent during inference on clean inputs, evading detection due to inconspicuous behavior. However, once a specific trigger pattern appears in the input data, the backdoor activates, causing the model to execute its concealed function. Detecting such poisoned samples within vast datasets is virtually impossible through manual inspection. To address this challenge, we propose a novel approach that enables model training on potentially poisoned datasets by utilizing the power of recent diffusion models. Specifically, we create synthetic variations of all training samples, leveraging the inherent resilience of diffusion models to potential trigger patterns in the data. By combining this generative approach with knowledge distillation, we produce student models that maintain their general performance on the task while exhibiting robust resistance to backdoor triggers.Comment: 11 pages, 3 tables, 2 figure

The periodic table of data structures

http://sites.computer.org/debull/A18sept/p64.pdfPublished versio

Trajectory tracing dynamics in anisotropic microcavities

Ray-wave correspondence has proven a powerful tool in mesoscopic optics, in particular in the description of deformed microdisc cavities with a versatile application potential ranging from microlasers to sensors. New material classes such as graphene-based systems have enriched the field by adding Dirac Fermion optics as well as anisotropic material properties as further system parameters. The trigonally warped dispersion relation in bilayer-graphene billiards generalizes the concept of birefringence and opens unconventional ways of trajectory control in the interplay of dispersion relation and the cavity geometry as we illustrate in this contribution

Universality and beyond in Optical Microcavity Billiards with Source-Induced Dynamics

Optical microcavity billiards are a paradigm of a mesoscopic model system for quantum chaos. We demonstrate the action and origin of ray-wave correspondence in real and phase space using far-field emission characteristics and Husimi functions. Whereas universality induced by the invariant-measure dominated far-field emission is known to be a feature shaping the properties of many lasing optical microcavities, the situation changes in the presence of sources that we discuss here. We investigate the source-induced dynamics and the resulting limits of universality while we find ray-picture results to remain a useful tool in order to understand the wave behaviour of optical microcavities with sources. We demonstrate the source-induced dynamics in phase space from the source ignition until a stationary regime is reached comparing results from ray, ray-with-phase, and wave simulations and explore ray–wave correspondence

Influence of the Print Envelope Temperature on the Morphology and Tensile Properties of Thermoplastic Polyolefins Fabricated by Material Extrusion and Material Jetting Additive Manufacturing

Additive manufacturing (AM) nowadays has become a supportive method of traditional manufacturing. In particular, the medical and healthcare industry can profit from these developments in terms of personalized design and batches ranging from one to five specimens overall. In terms of polymers, polyolefins are always an interesting topic due to their low prices, inert chemistry, and crystalline structure resulting in preferable mechanical properties. Their semi-crystalline nature has some advantages but are challenging for AM due to their shrinkage and warping, resulting in geometrical inaccuracies or even layer detaching during the process. To tackle these issues, process parameter optimization is vital, with one important parameter to be studied more in detail, the print envelope temperature. It is well known that higher print envelope temperatures lead to better layer adhesion overall, but this investigation focuses on the mechanical properties and resulting morphology of a semi-crystalline thermoplastic polyolefin. Further, two different AM technologies, namely material jetting (ARBURG plastic freeforming—APF) and filament-based material extrusion, were studied and compared in detail. It was shown that higher print envelope temperatures lead to more isotropic behavior based on an evenly distributed morphology but results in geometrical inaccuracies since the material is kept in a molten state during printing. This phenomenon especially could be seen in the stress and strain values at break at high elongations. Furthermore, a different crystal structure can be achieved by setting a specific temperature and printing time, also resulting in peak values of certain mechanical properties. In comparison, better results could be archived by the APF technology in terms of mechanical properties and homogeneous morphology. Nevertheless, real isotropic part behavior could not be managed which was shown by the specimen printed vertically. Hence, a sweet spot between geometrical and mechanical properties still has to be found

A Systematic Evaluation of the SARS-CoV-2 Vaccine-Induced Anti-S-RBD-Ig Response in a Population of Health Care Workers

In the wake of the COVID-19 pandemic, the novel class of mRNA vaccines has been granted first-time approval for active immunization against SARS-CoV-2 alongside the already established viral vector-based vaccines. In this prospective single-center study, we set out to determine the vaccine-induced humoral immune response in a population of 1512 health care employees after the second and third vaccination, respectively. Anti-SARS-CoV-2 receptor-binding domain (RBD) and nucleocapsid antigen antibody concentrations were assessed using commercially available immunoassays. We could show that, in particular, young study subjects aged below 30 years, as well as those with a prior SARS-CoV-2 infection, developed significantly higher antibody concentrations. Our data further suggest that being in physically close contact with formerly SARS-CoV-2-positive people positively affects the post-vaccination response. Surprisingly, study subjects with a BMI > 30 produced the highest anti-S-RBD Ig antibody levels if they had recently received their third vaccination. Also, heterologous dual vaccine regimens consisting of a BNT162b2 and ChAdOx1 n-CoV-19, a homologous triple combination of BNT162b2, and an application of mRNA-1273 as the third vaccine, were most efficient at eliciting a humoral immune response. Our study substantiates existing evidence, but beyond that, scrutinizes the impact of vaccine agents and their respective combinations, as well as different time intervals on humoral immunogenicity

Sustaining the Musical Competitions Database: a TOSCA-based Approach to Application Preservation in the Digital Humanities

Abstract of paper 0574 presented at the Digital Humanities Conference 2019 (DH2019), Utrecht , the Netherlands 9-12 July, 2019