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Background: Coniferous woods (Abies nordmanniana (Stev.) Spach, Abies procera Rehd, Picea abies (L.) H.Karst, and Picea pungens Engelm.) could contain useful secondary metabolites to produce sustainable packaging materials, e.g., by substitution of harmful petrol-based additives in plastic packaging. This study aims to characterise the antioxidant and light-absorbing properties and ingredients of different coniferous wood extracts with regard to different plant fragments and drying conditions. Furthermore, the valorisation of used Christmas trees is evaluated. Methods: Different drying and extraction techniques were applied with the extracts being characterised by determining the total phenolic content (TPC), total antioxidant capacity (TAC), and absorbance in the ultraviolet range (UV). Gas chromatography coupled with mass spectrometry (GC-MS) and an acid–butanol assay (ABA) were used to characterise the extract constituents. Results: All the extracts show a considerably high UV absorbance while interspecies differences did occur. All the fresh and some of the dried biomass extracts reached utilisable TAC and TPC values. A simplified extraction setup for industrial application is evaluated; comparable TAC results could be reached with modifications. Conclusion: Coniferous woods are a promising renewable resource for preparation of sustainable antioxidants and photostabilisers. This particularly applies to Christmas trees used for up to 12 days. After extraction, the biomass can be fully valorised by incorporation in paper packaging.
Unsachgemäß entsorgte Zigarettenkippen stellen aufgrund der in ihnen enthaltenen Giftstoffe ein relevantes, ökologisches Problem dar. Diese Forschungsarbeit untersucht den Einsatz von Nudging zur Bekämpfung der Problematik. In einer quantiativen Online-Befragung wurden zunächst die Gründe für das umweltschädliche Verhalten untersucht (N = 96). Hierbei konnte die Gegenwartstendenz von Personen als statistisch signifikanter Hauptgrund ermittelt werden. Viele Personen gaben an, die langfristigen ökologischen Kosten einer unsachgemäßen Entsorgung aufgrund des kurzfristigen persönlichen Nutzens zu ignorieren. Dieser entsteht durch die Gemütlichkeit des „Wegschnipsens“ einer Zigarettenkippe. Im Anschluss wurde ein auf die Gegenwartstendenz von Personen fokussierter Nudge entwickelt und in einem Feldexperiment auf seine Wirksamkeit überprüft, indem die Relation von unsachgemäß zu sachgemäß entsorgten Zigarettenkippen vor und nach dem Einsatz des Nudges dokumentiert wurde. Ohne Einsatz des Nudges (N = 92) wurden am Erhebungsort 64.1 Prozent und mit Einsatz des Nudges (N = 142) lediglich 38.0 Prozent der Zigarettenkippen unsachgemäß entsorgt. In dem Feldexperiment konnte der Nudge effektiv zur Förderung von nachhaltigem Verhalten eingesetzt werden.
This volume of the series Springer Briefs in Space Life Sciences explains the physics and biology of radiation in space, defines various forms of cosmic radiation and their dosimetry, and presents a range of exposure scenarios. It also discusses the effects of radiation on human health and describes the molecular mechanisms of heavy charged particles’ deleterious effects in the body. Lastly, it discusses countermeasures and addresses the vital question: Are we ready for launch?
Written for researchers in the space life sciences and space biomedicine, and for master’s students in biology, physics, and medicine, the book will also benefit all non-experts endeavoring to understand and enter space.
Space exposure experiments from the last 15 years have unexpectedly shown that several terrestrial organisms, including some multi-cellular species, are able to survive in open space without protection. The robustness of bdelloid rotifers suggests that these tiny creatures can possibly be added to the still restricted list of animals that can deal with the exposure to harsh condition of space. Bdelloids are one of the smallest animals on Earth. Living all over the world, mostly in semi-terrestrial environments, they appear to be extremely stress tolerant. Their desiccation tolerance at any stage of their life cycle is known to confer tolerance to a variety of stresses including high doses of radiation and freezing. In addition, they constitute a major scandal in evolutionary biology due to the putative absence of sexual reproduction for at least 60 million years. Adineta vaga, with its unique characteristics and a draft genome available, was selected by ESA (European Space Agency) as a model system to study extreme resistance of organisms exposed to space environment. In this manuscript, we documented the resistance of desiccated A. vaga individuals exposed to increasing doses of X-ray, protons and Fe ions. Consequences of exposure to different sources of radiation were investigated in regard to the cellular type including somatic (survival assay) and germinal cells (fertility assay). Then, the capacity of A. vaga individuals to repair DNA DSB induced by different source of radiation was investigated. Bdelloid rotifers represent a promising model in order to investigate damage induced by high or low LET radiation. The possibility of exposure both on hydrated or desiccated specimens may help to decipher contribution of direct and indirect radiation damage on biological processes. Results achieved through this study consolidate our knowledge about the radioresistance of A. vaga and improve our capacity to compare extreme resistance against radiation among living organisms including metazoan.
Im Rahmen dieser Arbeit wurden Resorcinol-Formaldehyd-Aerogele zur Anwendung in Kreislaufwärmerohren (LHP) als Dochtmaterial entwickelt. Aerogele als Dochtmaterial bilden aufgrund der hohen Porosität und der effektiven Kapillarwirkung eine gute Grundvoraussetzung für Stoff- und Wärmetransport. Diese Eigenschaften können zu einer Verbesserung der Kühlleistung einer Wärmepumpe beitragen. Dazu wurden Aerogele in Dochtform synthetisiert und anschließend erfolgte die Bestimmung der skelettalen Dichte, umhüllenden Dichte, Porosität und Gaspermeabilität. Zusätzlich wurde ein Test zum Schwellverhalten entwickelt. Außerdem wurden die Proben zur Fa. Allatherm gesendet, um die Anforderungen an die entwickelten RFAerogele in Dochtform zu prüfen. Die mechanische Bearbeitbarkeit der Aerogele konnte verbessert werden. Die Porosität und die Gaspermeabilität der untersuchten Aerogele lagen in einem optimalen Bereich. Nur die Durchgangsporengröße der Aerogele, die mittels Gasblasendruck-Analyse bestimmt wurde, benötigt weitere Rezeptentwicklungen und Messungen, um die größte Durchgangspore in Richtung 1 µm einzugrenzen.
Foreword to the Special Section on the Symposium on Virtual and Augmented Reality 2019 (SVR 2019)
(2020)
Die Internationalisierung von Hochschulen muss mit passenden Angeboten für internationale Studierende einhergehen. Ein systemisches und kultursensitives Peer-Coaching kann internationale Studierende unterstützen, sich zu orientieren, zu integrieren und berufliche Ziele zu verwirklichen. Gleichzeitig entwickeln die zu Peer-Coaches ausgebildeten Studierenden Sensibilität für Diversität. Insgesamt wird ein kultursensitives Miteinander an der Hochschule gefördert.
Discrimination and classification of eight strains related to meat spoilage microorganisms commonly found in poultry meat were successfully carried out using two dispersive Raman spectrometers (Microscope and Portable Fiber-Optic systems) in combination with chemometric methods. Principal Components Analysis (PCA) and Multi-Class Support Vector Machines (MC-SVM) were applied to develop discrimination and classification models. These models were certified using validation data sets which were successfully assigned to the correct bacterial genera and even to the right strain. The discrimination of bacteria down to the strain level was performed for the pre-processed spectral data using a 3-stage model based on PCA. The spectral features and differences among the species on which the discrimination was based were clarified through PCA loadings. In MC-SVM the pre-processed spectral data was subjected to PCA and utilized to build a classification model. When using the first two components, the accuracy of the MC-SVM model was 97.64% and 93.23% for the validation data collected by the Raman Microscope and the Portable Fiber-Optic Raman system, respectively. The accuracy reached 100% for the validation data by using the first eight and ten PC’s from the data collected by Raman Microscope and by Portable Fiber-Optic Raman system, respectively. The results reflect the strong discriminative power and the high performance of the developed models, the suitability of the pre-processing method used in this study and that the low accuracy of the Portable Fiber-Optic Raman system does not adversely affect the discriminative power of the developed models.
In recent years, a plethora of observations with high spectral resolution of sub-millimetre and far-infrared transitions of methylidene (CH), conducted with Herschel and SOFIA, have demonstrated this radical to be a valuable proxy for molecular hydrogen that can be used for characterising molecular gas within the interstellar medium on a Galactic scale, including the CO-dark component. We report the discovery of the 13CH isotopologue in the interstellar medium using the upGREAT receiver on board SOFIA. We have detected the three hyperfine structure components of the ≈2 THz frequency transition from its X2Π1∕2 ground-state towards the high-mass star-forming regions Sgr B2(M), G34.26+0.15, W49(N), and W51E and determined 13CH column densities. The ubiquity of molecules containing carbon in the interstellar medium has turned the determination of the ratio between the abundances of the two stable isotopes of carbon, 12C/13C, into a cornerstone for Galactic chemical evolution studies. Whilst displaying a rising gradient with galactocentric distance, this ratio, when measured using observations of different molecules (CO, H2CO, and others), shows systematic variations depending on the tracer used. These observed inconsistencies may arise from optical depth effects, chemical fractionation, or isotope-selective photo-dissociation. Formed from C+ either through UV-driven or turbulence-driven chemistry, CH reflects the fractionation of C+, and does not show any significant fractionation effects, unlike other molecules that were previously used to determine the 12C/13C isotopic ratio. This makes it an ideal tracer for the 12C/13C ratio throughout the Galaxy. By comparing the derived column densities of 13CH with previously obtained SOFIA data of the corresponding transitions of the main isotopologue 12CH, we therefore derive 12C/13C isotopic ratios toward Sgr B2(M), G34.26+0.15, W49(N) and W51E. Adding our values derived from 12∕13CH to previous calculations of the Galactic isotopic gradient, we derive a revised value of 12C/13C = 5.87(0.45)RGC + 13.25(2.94).
Due to the popularity of the Internet and the networked services that it facilitates, networked devices have become increasingly common in both the workplace and everyday life in recent years—following the trail blazed by smartphones. The data provided by these devices allow for the creation of rich user profiles. As a result, the collection, processing and exchange of such personal data have become drivers of economic growth. History shows that the adoption of new technologies is likely to influence both individual and societal concepts of privacy. Research into privacy has therefore been confronted with continuously changing concepts due to technological progress. From a legal perspective, privacy laws that reflect social values are sought. Privacy enhancing technologies are developed or adapted to take account of technological development. Organizations must also identify protective measures that are effective in terms of scalability and automation. Similarly, research is being conducted from the perspective of Human-Computer Interaction (HCI) to explore design spaces that empower individuals to manage their protection needs with regard to novel data, which they may perceive as sensitive. Taking such an HCI perspective with regard to understanding privacy management on the Internet of Things (IoT), this research mainly focuses on three interrelated goals across the fields of application: 1. Exploring and analyzing how people make sense of data, especially when managing privacy and data disclosure; 2. Identifying, framing and evaluating potential resources for designing sense-making processes; and 3. Exploring the fitness of the identified concepts for inclusion in legal and technical perspectives on supporting decisions regarding privacy on the IoT. Although this work's point of departure is the HCI perspective, it emphasizes the importance of the interrelationships among seemingly independent perspectives. Their interdependence is therefore also emphasized and taken into account by subscribing to a user-centered design process throughout this study. More specifically, this thesis adopts a design case study approach. This approach makes it possible to conduct full user-centered design lifecycles in a concrete application case with participants in the context of everyday life. Based on this approach, it was possible to investigate several domains of the IoT that are currently relevant, namely smart metering, smartphones, smart homes and connected cars. The results show that the participants were less concerned about (raw) data than about the information that could potentially be derived from it. Against the background of the constant collection of highly technical and abstract data, the content of which only becomes visible through the application of complex algorithms, this study indicates that people should learn to explore and understand these data flexibly, and provides insights in how to design for supporting this aim. From the point of view of design for usable privacy protection measures, the information that is provided to users about data disclosure should be focused on the consequences thereof for users' environments and life. A related concept from law is “informed consent,” which I propose should be further developed in order to implement usable mechanisms for individual privacy protection in the era of the IoT. Finally, this thesis demonstrates how research on HCI can be methodologically embedded in a regulative process that will inform both the development of technology and the drafting of legislation.
Solving differential-algebraic equations (DAEs) efficiently by means of appropriate numerical schemes for time-integration is an ongoing topic in applied mathematics. In this context, especially when considering large systems that occur with respect to many fields of practical application effective computation becomes relevant. In particular, corresponding examples are given when having to simulate network structures that consider transport of fluid and gas or electrical circuits. Due to the stiffness properties of DAEs, time-integration of such problems generally demands for implicit strategies. Among the schemes that prove to be an adequate choice are linearly implicit Rung-Kutta methods in the form of Rosenbrock-Wanner (ROW) schemes. Compared to fully implicit methods, they are easy to implement and avoid the solution of non-linear equations by including Jacobian information within their formulation. However, Jacobian calculations are a costly operation. Hence, necessity of having to compute the exact Jacobian with every successful time-step proves to be a considerable drawback. To overcome this drawback, a ROW-type method is introduced that allows for non-exact Jacobian entries when solving semi-explicit DAEs of index one. The resulting scheme thus enables to exploit several strategies for saving computational effort. Examples include using partial explicit integration of non-stiff components, utilizing more advantageous sparse Jacobian structures or making use of time-lagged Jacobian information. In fact, due to the property of allowing for non-exact Jacobian expressions, the given scheme can be interpreted as a generalized ROW-type method for DAEs. This is because it covers many different ROW-type schemes known from literature. To derive the order conditions of the ROW-type method introduced, a theory is developed that allows to identify occurring differentials and coefficients graphically by means of rooted trees. Rooted trees for describing numerical methods were originally introduced by J.C. Butcher. They significantly simplify the determination and definition of relevant characteristics because they allow for applying straightforward procedures. In fact, the theory presented combines strategies used to represent ROW-type methods with exact Jacobian for DAEs and ROW-type methods with non-exact Jacobian for ODEs. For this purpose, new types of vertices are considered in order to describe occurring non-exact elementary differentials completely. The resulting theory thus automatically comprises relevant approaches known from literature. As a consequence, it allows to recognize order conditions of familiar methods covered and to identify new conditions. With the theory developed, new sets of coefficients are derived that allow to realize the ROW-type method introduced up to orders two and three. Some of them are constructed based on methods known from literature that satisfy additional conditions for the purpose of avoiding effects of order reduction. It is shown that these methods can be improved by means of the new order conditions derived without having to increase the number of internal stages. Convergence of the resulting methods is analyzed with respect to several academic test problems. Results verify the theory determined and the order conditions found as only schemes satisfying the order conditions predicted preserve their order when using non-exact Jacobian expressions.
Network aggregation
(2020)
Until recently, studies regarding e-banking transactions have focused more on motivational factors that trigger the intention to accept and use the e-banking transaction, rather than the de-motivational factors that propel the action. However, in the developing countries like Sub-Sahara economies, the factors associated with the former have not been explored and are still rudimentary in the literature. Drawing from the Technology Threat Avoidance Theory (TTAT), the study seeks to examine the impact of online identity theft on customers’ willingness to engage in e-banking transactions in Ghana. A quantitative survey of 393 valid responses from retail bank customers amongst two leading commercial banks in Ghana for the analyses. Results from the PLS-SEM showed that the research constructs; perceived online identity theft’ positively and significantly predict “fear of financial loss”, “fear of reputational damage”, and “security and privacy concern” whilst the former has a negative mediated-relationship between perceived online identity theft and the intention to engage in e-banking transaction. This study is the first of its kind that has extended the application of the TTAT framework into the study of e-banking transactions. The study serves as a practical tool that will enable the banks in their quest to assess customers’ restriction/aversion towards the use of Fintech while ensuring sustainable growth of e-banking transactions in an emerging economy context. The study is limited to only banking institutions in Ghana without considering other players in the financial sub-sector. Future research direction has been suggested in the concluding part of the paper.
Do socio-economic factors impede the engagement in online banking transactions? Evidence from Ghana
(2020)
Researchers have long pondered on the online banking transaction adoption. Some of these studies focus primarily on the motivating factors that affect customers’ intention to adopt/accept these services (technologies). However, research into the constraining factors, in particular socio-economic factors, barely exist in the literature, especially in the context of sub-Saharan Africa. Against this background, the paper seeks to fill in this gap by: (1) assessing the socio-economic factors impeding the engagement of e-banking transactions among retail bank customers in Ghana, and (2) examining the moderating effect of ‘customer experience of Internet’ on the identified factors that inhibit the engagement in online banking in Ghana. The paper used a quantitative research approach to obtain data from two leading Ghanaian banks. Out of the 450 questionnaires distributed, 393 were valid for analysis. Data were analyzed with the aid of PLS-SEM (partial least squares and structural equation modeling). Findings revealed that perceived knowledge gap and the price of digital devices were directly important to the intention to disembark on e-banking transactions among Ghanaian bank customers. Whilst customer experience (frequent use of the Internet), as a moderator variable, has a significant effect on the interaction between perceived knowledge gap and the intent to disembark on e-banking transactions; and finance charges and the intent to disembark on e-banking transactions. Study implications and directions for future research are discussed in the paper.
Telepresence robots allow people to participate in remote spaces, yet they can be difficult to manoeuvre with people and obstacles around. We designed a haptic-feedback system called “FeetBack," which users place their feet in when driving a telepresence robot. When the robot approaches people or obstacles, haptic proximity and collision feedback are provided on the respective sides of the feet, helping inform users about events that are hard to notice through the robot’s camera views. We conducted two studies: one to explore the usage of FeetBack in virtual environments, another focused on real environments.We found that FeetBack can increase spatial presence in simple virtual environments. Users valued the feedback to adjust their behaviour in both types of environments, though it was sometimes too frequent or unneeded for certain situations after a period of time. These results point to the value of foot-based haptic feedback for telepresence robot systems, while also the need to design context-sensitive haptic feedback.
Deep learning models are extensively used in various safety critical applications. Hence these models along with being accurate need to be highly reliable. One way of achieving this is by quantifying uncertainty. Bayesian methods for UQ have been extensively studied for Deep Learning models applied on images but have been less explored for 3D modalities such as point clouds often used for Robots and Autonomous Systems. In this work, we evaluate three uncertainty quantification methods namely Deep Ensembles, MC-Dropout and MC-DropConnect on the DarkNet21Seg 3D semantic segmentation model and comprehensively analyze the impact of various parameters such as number of models in ensembles or forward passes, and drop probability values, on task performance and uncertainty estimate quality. We find that Deep Ensembles outperforms other methods in both performance and uncertainty metrics. Deep ensembles outperform other methods by a margin of 2.4% in terms of mIOU, 1.3% in terms of accuracy, while providing reliable uncertainty for decision making.
This work provides a short but technical introduction to the main building blocks of a blockchain. It argues that a blockchain is not a revolutionary technology but rather a clever combination of three fields: cryptography, decentralization and game theory. In addition, it summaries the differences between a public, private and federate blockchain model and the two prominent consensus mechanism Proof-of-Work (POW) and Proof-of-Stake (POS).