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Media Brand Management
(2022)
The management of media brands faces challenges. In order to be able to point out possible solutions, this article first explains the concept and the nature of “media brands.” Subsequently, various theoretical approaches to the explanation of media brands and their management are presented. Regardless of theoretical preferences, it is important to keep in mind the brand-strategic complexity of media management that is subsequently described. Due to their specificity, special attention is paid to the basic strategic positioning options and to the communication management of media brands. In this way, the special features of media brand management become clear in comparison with other products and services.
Nowadays, robots are found in a growing number of areas where they collaborate closely with humans. Enabled by lightweight materials and safety sensors, these cobots are gaining increasing popularity in domestic care, where they support people with physical impairments in their everyday lives. However, when cobots perform actions autonomously, it remains challenging for human collaborators to understand and predict their behavior, which is crucial for achieving trust and user acceptance. One significant aspect of predicting cobot behavior is understanding their perception and comprehending how they “see” the world. To tackle this challenge, we compared three different visualization techniques for Spatial Augmented Reality. All of these communicate cobot perception by visually indicating which objects in the cobot’s surrounding have been identified by their sensors. We compared the well-established visualizations Wedge and Halo against our proposed visualization Line in a remote user experiment with participants suffering from physical impairments. In a second remote experiment, we validated these findings with a broader non-specific user base. Our findings show that Line, a lower complexity visualization, results in significantly faster reaction times compared to Halo, and lower task load compared to both Wedge and Halo. Overall, users prefer Line as a more straightforward visualization. In Spatial Augmented Reality, with its known disadvantage of limited projection area size, established off-screen visualizations are not effective in communicating cobot perception and Line presents an easy-to-understand alternative.
This chapter describes a new concept and experiences of a distributed interdisciplinary learning program for students across continents. The aim is to provide students with a truly Global Intercultural Project Experience (GIPE) by working together with peers from around the world and solving real-life client’s problems. We have received seed-funding for four annual projects to engage students from Germany (Europe), Namibia (Africa), Indonesia (Asia), and Peru (South America). In 2020 and 2021, 28 and 44 students from four continents engaged in a one-semester distributed interdisciplinary project for a Namibian and Indonesian client, respectively. Despite Covid-19 they successfully completed the project expressing deep appreciation for the learning opportunities overcoming challenges of working across widespread time zones, cultures, changing requirements, and various technical difficulties. Considering the vast learning benefits, we suggest incorporating such projects in all tertiary education curricula across the globe, while streamlining organizational efforts based on lessons learned.
Fruits (follicles) of Hakea salicifolia and Hakea sericea (Proteaceae) are characterised by pronounced lignification and open via a ventral suture and the dorsal side. The opening along both sides is unique within the Proteaceae. Both serotinous species are obligate seeders, whose spreading benefits from bush fire events. The different tissues and the course of the vascular bundles must allow the opening mechanism. While their 2D-arrangements are known to some extent from light-microscopy images of cross-sections, this work presents their three-dimensional structures and discusses their contribution to the opening of Hakea fruits. For this purpose, 3D greyscale images, reconstructed from µCT-projection data of both fruits are segmented, assisted by a deep learning algorithm (AI algorithm). 3D renderings from these segmentations show strongly interconnected vascular bundles that build a double-dome shaped network in each valve of H. salicifolia and a dome shaped honeycomb-structure in each valve of H. sericea. However, the vascular bundles of both species show no interconnection between the two lateral valves of the fruit but leave gaps for predetermined fracture tissues on the ventral and dorsal side. The opening of the fruits after a fire or after separation from the mother plant can be explained by the anisotropic shrinkage in the two valves of the fruit.
We investigated the formation of Artemia franciscana swarms of freshly hatched instar I nauplii larvae. Nauplii were released into light gradients but then interrupted by light-direction changes, small obstacles, or long barriers. All experiments were carried out horizontally. Each experiment used independent replicates. Freshly produced Artemia broods were harvested from independent incubators thus providing true replicate cohorts of Artemia subjected as replicates to the experimental treatments.
We discovered that Artemia nauplii swarms can: 1. repeatedly react to non-obstructed light gradients that undergo repeated direction-changes and do so in a consistent way, 2. find their way to a light source within maze-like arrangements made from small transparent obstacles, 3. move as a swarm around extended transparent barriers, following a light gradient. This paper focuses on the recognition of whole-swarm behaviors, the description thereof and the recognition of differences in whole-swarm movements comparing non-obstructed swarming with swarms encountering obstacles. Investigations of the within-swarm behaviors of individual Artemia nauplii and their interactions with neighboring nauplii are in progress, e.g. in order to discover the underlying swarming algorithms and differences
thereof comparing non-obstructed vs. obstructed pathways.
The concept of molecular scaffolds as defining core structures of organic molecules is utilised in many areas of chemistry and cheminformatics, e.g. drug design, chemical classification, or the analysis of high-throughput screening data. Here, we present Scaffold Generator, a comprehensive open library for the generation, handling, and display of molecular scaffolds, scaffold trees and networks. The new library is based on the Chemistry Development Kit (CDK) and highly customisable through multiple settings, e.g. five different structural framework definitions are available. For display of scaffold hierarchies, the open GraphStream Java library is utilised. Performance snapshots with natural products (NP) from the COCONUT (COlleCtion of Open Natural prodUcTs) database and drug molecules from DrugBank are reported. The generation of a scaffold network from more than 450,000 NP can be achieved within a single day.
The development of deep learning-based optical chemical structure recognition (OCSR) systems has led to a need for datasets of chemical structure depictions. The diversity of the features in the training data is an important factor for the generation of deep learning systems that generalise well and are not overfit to a specific type of input. In the case of chemical structure depictions, these features are defined by the depiction parameters such as bond length, line thickness, label font style and many others. Here we present RanDepict, a toolkit for the creation of diverse sets of chemical structure depictions. The diversity of the image features is generated by making use of all available depiction parameters in the depiction functionalities of the CDK, RDKit, and Indigo. Furthermore, there is the option to enhance and augment the image with features such as curved arrows, chemical labels around the structure, or other kinds of distortions. Using depiction feature fingerprints, RanDepict ensures diversely picked image features. Here, the depiction and augmentation features are summarised in binary vectors and the MaxMin algorithm is used to pick diverse samples out of all valid options. By making all resources described herein publicly available, we hope to contribute to the development of deep learning-based OCSR systems.
We study the dynamics of a quantum two-state system driven through an avoided crossing under the influence of a super-Ohmic environment. We determine the Landau–Zener probability employing the numerical exact quasi-adiabatic path integral and a Markovian weak coupling approach. Increasing the driving time in the numerical protocol, we find converged results which shows that super-Ohmic environments only influence the Landau Zener probability within a finite crossing time window. This crossing time is qualitatively determined by the environmental cut-off energy. At weak coupling, we show that the Markovian weak coupling approach provides an accurate description. Since pure dephasing of a super-Ohmic bath is non-Markovian, this highlights that pure dephasing hardly influences the Landau–Zener probability. The finite crossing time window, thus, results from the suppression of relaxation once the energy splitting exceeds the environmental cut-off energy.
A quantum two-level system immersed in a sub-Ohmic bath experiences enhanced low-frequency quantum statistical fluctuations which render the nonequilibrium quantum dynamics highly non-Markovian. Upon using the numerically exact time-evolving matrix product operator approach, we investigate the phase diagram of the polarization dynamics. In addition to the known phases of damped coherent oscillatory dynamics and overdamped decay, we identify a new third region in the phase diagram for strong coupling showing an aperiodic behavior. We determine the corresponding phase boundaries. The dynamics of the quantum two-state system herein is not coherent by itself but slaved to the oscillatory bath dynamics.
We propose a quantum-mechanical model to calculate the nonlinear differential conductance of a single molecular junction immersed in a solvent, either in pure form or as a binary mixture with varying volume fraction. The solvent mixture is captured by a dielectric continuum model for which the resulting spectral density is determined within the Gladstone-Dale approach. The conductance of the molecular junction is calculated by a real-time diagrammatic technique. We find a strong variation of the conductance maximum for varying volume fraction of the solvent mixture. Importantly, the calculated molecular nonlinear conductance shows a very good agreement with experimentally measured data for common molecular junctions in various polar solvent mixtures.
To address the question which neocortical layers and cell types are important for the perception of a sensory stimulus, we performed multielectrode recordings in the barrel cortex of head-fixed mice performing a single-whisker go/no-go detection task with vibrotactile stimuli of differing intensities. We found that behavioral detection probability decreased gradually over the course of each session, which was well explained by a signal detection theory-based model that posits stable psychometric sensitivity and a variable decision criterion updated after each reinforcement, reflecting decreasing motivation. Analysis of multiunit activity demonstrated highest neurometric sensitivity in layer 4, which was achieved within only 30 ms after stimulus onset. At the level of single neurons, we observed substantial heterogeneity of neurometric sensitivity within and across layers, ranging from nonresponsiveness to approaching or even exceeding psychometric sensitivity. In all cortical layers, putative inhibitory interneurons on average proffered higher neurometric sensitivity than putative excitatory neurons. In infragranular layers, neurons increasing firing rate in response to stimulation featured higher sensitivities than neurons decreasing firing rate. Offline machine-learning-based analysis of videos of behavioral sessions showed that mice performed better when not moving, which at the neuronal level, was reflected by increased stimulus-evoked firing rates.
Third-party tracking is a common and broadly used technique on the Web. Different defense mechanisms have emerged to counter these practices (e.g. browser vendors that ban all third-party cookies). However, these countermeasures only target third-party trackers and ignore the first party because the narrative is that such monitoring is mostly used to improve the utilized service (e.g. analytical services). In this paper, we present a large-scale measurement study that analyzes tracking performed by the first party but utilized by a third party to circumvent standard tracking preventing techniques. We visit the top 15,000 websites to analyze first-party cookies used to track users and a technique called “DNS CNAME cloaking”, which can be used by a third party to place first-party cookies. Using this data, we show that 76% of sites effectively utilize such tracking techniques. In a long-running analysis, we show that the usage of such cookies increased by more than 50% over 2021.
Biomimetics is the interdisciplinary co-operation of various scientific disciplines and fields of innovation, and it aims to solve practical problems using biological models. Biomimetic research and its fields of application are manifold, and the community is made up of a wide range of disciplines, from biologists and engineers to designers. Guidelines and standards can build a common ground for understanding of the field, communication across disciplines, present and future projects and implementation of biomimetic knowledge. Since 2015, three international standards have been published and defined terms and definitions, as well as specific applications. The scientific literature and patents in several databases were searched for citations of the published standards. Standards or technical guidelines on biomimetics are represented both in the scientific literature and in patents. However, taking into account the increasing number of publications in biomimetics, the number of publications (52) citing the international standards is low. This shows that the perception of technical rules is still underrepresented in the academic field. Greater awareness and acceptance of the importance of standards for quality assurance even in the academic environment is discussed, and active participation in the corresponding International Organization for Standardization committee on biomimetics is asked for.
Background: Priority during the SARS-CoV2 pandemic is that employees need to be protected from infection risks and business activities need to be ensured. New virus variants with increased infection risks require an evolved risk strategy.
Material and methods: Several standard measures such as testing, isolation and quarantine are com-bined to a novel risk strategy. Epidemiological model calculations and scientific knowledge about the course of SARS-CoV2 infectivity are used to optimize this strategy. The procedure is implemented in an easy-to-use calculator based on Excel.
Layout in practice and results: Alternative combinations of measures and practical aspects are dis-cussed. Example calculations are used to demonstrate the effect of the discussed measures.
Conclusion: That quarantine calculator derived from these principles enables even non-specialists to perform a differentiated risk analysis and to introduce optimized measures. Targeted testing routines and alternative measures ensure staff availability.
The diffusion of hydrogen adsorbed inside layered MoS2 crystals has been studied by means of quasi- elastic neutron scattering, neutron spin-echo spectroscopy, nuclear reaction analysis, and X-ray photoelectron spectroscopy. The neutron time-of-flight and neutron spin-echo measurements demonstrate fast diffusion of hydrogen molecules parallel to the basal planes of the two dimensional crystal planes. At room temperature and above, this intra-layer diffusion is of a similar speed to the surface diffusion that has been observed in earlier studies for hydrogen atoms on Pt surfaces. A significantly slower hydrogen diffusion was observed perpendicular to the basal planes using nuclear reaction analysis.
Recommendations for the Development of a Robotic Drinking and Eating Aid - An Ethnographic Study
(2021)
Being able to live independently and self-determined in one’s own home is a crucial factor or human dignity and preservation of self-worth. For people with severe physical impairments who cannot use their limbs for every day tasks, living in their own home is only possible with assistance from others. The inability to move arms and hands makes it hard to take care of oneself, e.g. drinking and eating independently. In this paper, we investigate how 15 participants with disabilities consume food and drinks. We report on interviews, participatory observations, and analyzed the aids they currently use. Based on our findings, we derive a set of recommendations that supports researchers and practitioners in designing future robotic drinking and eating aids for people with disabilities.
As vaccination campaigns are in progress in most countries, hopes to win back more normality are rising. However, the exact path from a pandemic to an endemic virus remains uncertain. While in the pre-vaccination phase many critical indoor situations were avoided by strict control measures, for the transition phase a certain mitigation of the effect of indoor situations seems advisable.
To better understand the mechanisms of indoor airborne transmissions, we present a new time-discrete model to calculate the level of exposure towards infectious SARS-CoV-2 aerosol and carry out a sensitivity analysis for the level of SARS-CoV-2 aerosol exposure in indoor settings. Time limitations and the use of any kind of masks were found to be strong mitigation measures, while how far the effort for a strict use of professional face pieces instead of simple masks can be justified by the additional reduction of the exposure dose remains unclear. Very good ventilation of indoor spaces is mandatory. The definition of sufficient ventilation in regard to airborne SARS-CoV-2 transmission follows other rules than the standards in ventilation design. This means that especially smaller rooms most likely require a significantly greater fresh air supply than usual. Further research on 50% group models in schools is suggested. The benefits of a model in which the students come to school every day, but for a limited time, should be investigated. In terms of window ventilation, it has been found that many short opening periods are not only thermally beneficial, they also reduce the exposure dose. The fresh air supply is driven by the temperature gradient and wind speed. However, the sensitivity towards these parameters is not very high and in times of low wind and temperature gradients, there are no arguments against keep windows open in order to make up for the reduced air flow rate. Long total opening periods and large window surfaces will strongly reduce the exposure. Additionally, the results underline the expectable fact that exposure doses will increase when hygiene and control measures are reduced. It seems advisable to investigate what this means for the infection rate and the fatality of infections in populations with partial immunity. Very basic considerations suggest that the value of aerosol reduction measures may be reduced with very infectious variants such as delta.
This Article introduces two research projects towards assistive robotic arms for people with severe body impairments. Both projects aim to develop new control and interaction designs to promote accessibility and a better performance for people with functional losses in all four extremities, e.g. due to quadriplegic or multiple sclerosis. The project MobILe concentrates on using a robotic arm as drinking aid and controlling it with smart glasses, eye-tracking and augmented reality. A user oriented development process with participatory methods were pursued which brought new knowledge about the life and care situation of the future target group and the requirements a robotic drinking aid needs to meet. As a consequence the new project DoF-Adaptiv follows an even more participatory approach, including the future target group, their family and professional caregivers from the beginning into decision making and development processes within the project. DoF-Adaptiv aims to simplify the control modalities of assistive robotic arms to enhance the usability of the robotic arm for activities of daily living. lo decide on exemplary activities, like eating or open a door, the future target group, their family and professional caregivers are included in the decision making process. Furthermore all relevant stakeholders will be included in the investigation of ethical, legal and social implications as well as the identification of potential risks. This article will show the importance of the participatory design for the development and research process in MobILe and DoF-Adaptiv.
Description and Analysis of Glycosidic Residues in the Largest Open Natural Products Database
(2021)
This introduction to a special issue about concepts and facets of entrepreneurial diversity serves as a starting point for further discussion and research in this field. For this purpose, we provide information about the roots of the study of diversity and current trends in entrepreneurship research and present a frame for (researching) entrepreneurial diversity. Additionally, we briefly summarize the three papers selected for inclusion in this special issue. Together, they offer insights into the intersections of different diversity dimensions, personality as a deep dimension of team composition, and a general critical reflection on the conceptualization of entrepreneurial diversity. Taken together, the papers in this special issue present new findings and contribute to further advancing the long overdue research on and discussion about diversity in the field of entrepreneurship.
Cardiac and liver computed tomography (CT) perfusion has not been routinely implemented in the clinic and requires high radiation doses. The purpose of this study is to examine the radiation exposure and technical settings for cardiac and liver CT perfusion scans at different CT scanners. Two cardiac and three liver CT perfusion protocols were examined with the N1 LUNGMAN phantom at three multi-slice CT scanners: a single-source (I) and second- (II) and third-generation (III) dual-source CT scanners. Radiation doses were reported for the CT dose index (CTDIvol) and dose–length product (DLP) and a standardised DLP (DLP10cm) for cardiac and liver perfusion. The effective dose (ED10cm) for a standardised scan length of 10 cm was estimated using conversion factors based on the International Commission on Radiological Protection (ICRP) 110 phantoms and tissue-weighting factors from ICRP 103. The proposed total lifetime attributable risk of developing cancer was determined as a function of organ, age and sex for adults. Radiation exposure for CTDIvol, DLP/DLP10 cm and ED10 cm during CT perfusion was distributed as follows: for cardiac perfusion (II) 144 mGy, 1036 mGy·cm/1440 mGy·cm and 39 mSv, and (III) 28 mGy, 295 mGy·cm/279 mGy·cm and 8 mSv; for liver perfusion (I) 225 mGy, 3360 mGy·cm/2249 mGy·cm and 54 mSv, (II) 94 mGy, 1451 mGy·cm/937 mGy·cm and 22 mSv, and (III) 74 mGy, 1096 mGy·cm/739 mGy·cm and 18 mSv. The third-generation dual-source CT scanner applied the lowest doses. Proposed total lifetime attributable risk increased with decreasing age. Even though CT perfusion is a high-dose examination, we observed that new-generation CT scanners could achieve lower doses. There is a strong impact of organ, age and sex on lifetime attributable risk. Further investigations of the feasibility of these perfusion scans are required for clinical implementation.
Bone morphogenetic protein 2 (BMP21) is a highly interesting therapeutic growth factor due to its strong osteogenic/osteoinductive potential. However, its pronounced aggregation tendency renders recombinant and soluble production troublesome and complex. While prokaryotic expression systems can provide BMP2 in large amounts, the typically insoluble protein requires complex denaturation-renaturation procedures with medically hazardous reagents to obtain natively folded homodimeric BMP2. Based on a detailed aggregation analysis of wildtype BMP2, we designed a hydrophilic variant of BMP2 additionally containing an improved heparin binding site (BMP2-2Hep-7M). Consecutive optimization of BMP2-2Hep-7M expression and purification enabled production of soluble dimeric BMP2-2Hep-7M in high yield in E. coli. This was achieved by a) increasing protein hydrophilicity via introducing seven point mutations within aggregation hot spots of wildtype BMP2 and a longer N-terminus resulting in higher affinity for heparin, b) by employing E. coli strain SHuffle® T7, which enables the structurally essential disulfide-bond formation in BMP2 in the cytoplasm, c) by using BMP2 variant characteristic soluble expression conditions and application of L-arginine as solubility enhancer. The BMP2 variant BMP2-2Hep-7M shows strongly attenuated although not completely eliminated aggregation tendency.
Background: By reviewing image quality and diagnostic perception, the suitability of a statistical model-based iterative reconstruction algorithm in conjunction with low-dose computed tomography for lung cancer screening is investigated.
Methods: Artificial lung nodules shaped as spheres and spiculated spheres made from material with calibrated Hounsfield units were attached on marked positions in the lung structure of anthropomorphic phantoms. The phantoms were scanned using standard high contrast, and two low-dose computed tomography protocols: low-dose and ultra-low-dose. For the reconstruction, the filtered back projection and the iterative reconstruction algorithm ADMIRE at different strength levels (S1–S5) and the kernels Bl57, Br32, Br69 were used. Expert radiologists assessed image quality by performing 4-field-ranking tests and reading all image series to examine the aptitude for the detectability of lung nodules. Signal-to-noise ratio was investigated as objective image quality parameter.
Results: In ranking tests for lung foci detection expert radiologists prefer medium to high iterative reconstruction strength levels. For the standard clinical kernel Bl57 and varying phantom diameter, a noticeable preference for S4 was detected. Experienced radiologists graded filtered back projection reconstructed images with the highest perceptibility. Less experienced readers assessed filtered back projection and iterative reconstruction equally with the highest grades for the Bl57 kernel. Independently of the dose protocol, the signal-to-noise ratio increases with the iterative reconstruction strength level, specifically for Br69 and Bl57.
Conclusions: Subjective image perception does not significantly correlate with the experience of the radiologist, which presumably mirrors reader’s training and accustomed reading adjustments. Regarding signal-to-noise ratio, iterative reconstruction outperforms filtered back projection for spheres and spiculated spheres. Iterative reconstruction matters. It promises to be an alternative to filtered back projection allowing for lung-cancer screening at markedly decreased radiation exposure but comparable or even improved image quality.
The aim of this phantom study is to examine radiation doses of dual- and single-energy computed tomography (DECT and SECT) in the chest and upper abdomen for three different multi-slice CT scanners. A total of 34 CT protocols were examined with the phantom N1 LUNGMAN. Four different CT examination types of different anatomic regions were performed both in single- and dual-energy technique: chest, aorta, pulmonary arteries for suspected pulmonary embolism and liver. Radiation doses were examined for the CT dose index CTDIvol and dose-length product (DLP). Radiation doses of DECT were significantly higher than doses for SECT. In terms of CTDIvol, radiation doses were 1.1–3.2 times higher, and in terms of DLP, these were 1.1–3.8 times higher for DECT compared with SECT. The third-generation dual-source CT applied the lowest dose in 7 of 15 different examination types of different anatomic regions.
This technical report is about the mission and the experience gained during the reconnaissance of an industrial hall with hazardous substances after a major fire in Berlin. During this operation, only UAVs and cameras were used to obtain information about the site and the building. First, a geo-referenced 3D model of the building was created in order to plan the entry into the hall. Subsequently, the UAVs were used to fly in the heavily damaged interior and take pictures from inside of the hall. A 360° camera mounted under the UAV was used to collect images of the surrounding area especially from sections that were difficult to fly into. Since the collected data set contained similar images as well as blurred images, it was cleaned from non-optimal images using visual SLAM, bundle adjustment and blur detection so that a 3D model and overviews could be calculated. It was shown that the emergency services were not able to extract the necessary information from the 3D model. Therefore, an interactive panorama viewer with links to other 360° images was implemented where the links to the other images depends on the semi dense point cloud and located camera positions of the visual SLAM algorithm so that the emergency forces could view the surroundings.
Flying insects employ elegant optical-flow-based strategies to solve complex tasks such as landing or obstacle avoidance. Roboticists have mimicked these strategies on flying robots with only limited success, because optical flow (1) cannot disentangle distance from velocity and (2) is less informative in the highly important flight direction. Here, we propose a solution to these fundamental shortcomings by having robots learn to estimate distances to objects by their visual appearance. The learning process obtains supervised targets from a stability-based distance estimation approach. We have successfully implemented the process on a small flying robot. For the task of landing, it results in faster, smooth landings. For the task of obstacle avoidance, it results in higher success rates at higher flight speeds. Our results yield improved robotic visual navigation capabilities and lead to a novel hypothesis on insect intelligence: behaviours that were described as optical-flow-based and hardwired actually benefit from learning processes.
Cone-Beam computed tomography (CBCT) has become the most important component of modern radiotherapy for positioning tumor patients directly before treatment. In this work we investigate alternations to standard acquisition protocol, called preset, for patients with a tumor in the thoracic region. The effects of the changed acquisition parameters on the image quality are evaluated using the Catphan Phantom and the image analysis software Smári. The weighted CT dose index (CTDIW) is determined in each case and the effects of the different acquisition protocols on the patient dose are classified accordingly. Additionally, the clinical suitability of alternative presets is tested by investigating correctness of image registration using the CIRS thorax phantom. The results show that a significant dose reduction can be achieved. It can be reduced by 51% for a full rotation by adjusting the gantry speed.
Welding and joining of components processed by additive manufacturing (AM) to other AMas well as conventionally produced components is of high importance for industry as thisallows to combine advantages of either technique and to produce large-scale structures,respectively. One of the key influencing factors with respect to weldability and mechanicalproperties of AM components was found to be the inherent microstructural anisotropy ofthese components. In present work, the precipitation-hardenable AleSi10Mg was fabri-cated in different build orientations using selective laser melting (SLM) and subsequentlyjoined by friction stir welding (FSW) in different combinations. Microstructural analysisshowed considerable grain refinement in the friction stir zone, however, pronouncedsoftening occurred in this area. The latter can be mainly attributed to changes in themorphology and size of Si particles. Upon combination of different build orientations aremarkable influence on the tensile strength of FSW joints was seen. Cyclic deformationresponses of SLM and FSW samples were examined in depth. Fatigue properties of thisalloy in the low-cycle fatigue (LCF) regime imply that SLM samples with the building di-rection parallel to the loading direction show superior performance under cyclic loading ascompared to the other conditions and the FSW joints. From results presented solid process-microstructure-property relationships are drawn.
This technical report is about the architecture and integration of very small commercial UAVs (< 40 cm diagonal) in indoor Search and Rescue missions. One UAV is manually controlled by only one single human operator delivering live video streams and image series for later 3D scene modelling and inspection. In order to assist the operator who has to simultaneously observe the environment and navigate through it we use multiple deep neural networks to provide guided autonomy, automatic object detection and classification and local 3D scene modelling. Our methods help to reduce the cognitive load of the operator. We describe a framework for quick integration of new methods from the field of Deep Learning, enabling for rapid evaluation in real scenarios, including the interaction of methods.