Refine
Year of publication
Document Type
- Conference Proceeding (1184)
- Article (reviewed) (679)
- Article (unreviewed) (566)
- Part of a Book (460)
- Contribution to a Periodical (287)
- Book (227)
- Other (139)
- Working Paper (105)
- Patent (98)
- Report (76)
Conference Type
- Konferenzartikel (945)
- Konferenz-Abstract (156)
- Sonstiges (42)
- Konferenz-Poster (32)
- Konferenzband (13)
Language
- German (2071)
- English (1857)
- Other language (5)
- Russian (3)
- Multiple languages (2)
- French (1)
- Spanish (1)
Is part of the Bibliography
- yes (3940) (remove)
Keywords
- Digitalisierung (41)
- RoboCup (32)
- Dünnschichtchromatographie (28)
- Social Media (24)
- COVID-19 (23)
- Kommunikation (23)
- Arbeitszeugnis (22)
- Energieversorgung (22)
- E-Learning (21)
- Export (21)
Institute
- Fakultät Maschinenbau und Verfahrenstechnik (M+V) (945)
- Fakultät Medien und Informationswesen (M+I) (bis 21.04.2021) (808)
- Fakultät Elektrotechnik und Informationstechnik (E+I) (bis 03/2019) (779)
- Fakultät Wirtschaft (W) (617)
- Fakultät Elektrotechnik, Medizintechnik und Informatik (EMI) (ab 04/2019) (464)
- INES - Institut für nachhaltige Energiesysteme (239)
- Fakultät Medien (M) (ab 22.04.2021) (219)
- ivESK - Institut für verlässliche Embedded Systems und Kommunikationselektronik (155)
- Zentrale Einrichtungen (81)
- IMLA - Institute for Machine Learning and Analytics (79)
Open Access
- Open Access (1464)
- Closed Access (1245)
- Closed (528)
- Bronze (285)
- Diamond (76)
- Gold (76)
- Hybrid (50)
- Grün (16)
A novel peptidyl-lys metalloendopeptidase (Tc-LysN) from Tramates coccinea was recombinantly expressed in Komagataella phaffii using the native pro-protein sequence. The peptidase was secreted into the culture broth as zymogen (~38 kDa) and mature enzyme (~19.8 kDa) simultaneously. The mature Tc-LysN was purified to homogeneity with a single step anion-exchange chromatography at pH 7.2. N-terminal sequencing using TMTpro Zero and mass spectrometry of the mature Tc-LysN indicated that the pro-peptide was cleaved between the amino acid positions 184 and 185 at the Kex2 cleavage site present in the native pro-protein sequence. The pH optimum of Tc-LysN was determined to be 5.0 while it maintained ≥60% activity between pH values 4.5—7.5 and ≥30% activity between pH values 8.5—10.0, indicating its broad applicability. The temperature maximum of Tc-LysN was determined to be 60 °C. After 18 h of incubation at 80 °C, Tc-LysN still retained ~20% activity. Organic solvents such as methanol and acetonitrile, at concentrations as high as 40% (v/v), were found to enhance Tc-LysN’s activity up to ~100% and ~50%, respectively. Tc-LysN’s thermostability, ability to withstand up to 8 M urea, tolerance to high concentrations of organic solvents, and an acidic pH optimum make it a viable candidate to be employed in proteomics workflows in which alkaline conditions might pose a challenge. The nano-LC-MS/MS analysis revealed bovine serum albumin (BSA)’s sequence coverage of 84% using Tc-LysN which was comparable to the sequence coverage of 90% by trypsin peptides.
Hintergrund
In diesem Artikel wird ein Überblick und Vergleich der am häufigsten verwendeten zementierten Hüftschäfte, gruppiert in die verschiedenen Schafttypen und Zementmanteldicken, gegeben, um zu sehen, welche Kombination gut abschneidet.
Methodik
Aus dem Endoprothesenregister Deutschland wurden die Revisionsraten zementierter Schaftarten kategorisiert und die Revisionsraten von 3 und 5 Jahren erfasst und analysiert. Für die Recherche lag die Konzentration auf den Schäften Exeter, C‑Stem, MS-30, Excia, Bicontact, Charnley, Müller Geradschaft, Twinsys, Corail, Avenir, Quadra und dem Lubinus SP II. Ein wichtiger Aspekt lag darin, welcher Schaft favorisiert implantiert wird und welche Zementiertechnik in Hinblick auf die geplante Zementmanteldicke angewendet wird. Um einen Trend in der zementierten Hüftendoprothetik herauszufinden, wurden zusätzlich die Daten des dänischen, schwedischen, norwegischen, schweizerischen, neuseeländischen, englischen und australischen Endoprothesenregister verglichen.
Ergebnisse und Schlussfolgerung
Die meisten Länder nutzen zementierte Prothesen nach dem Kraftschlussprinzip (Exeter, MS30, C‑Stem etc.) oder dem Formschlussprinzip (Charnley, Excia, Bicontact), welche mit einer Zementmanteldicke von 2–4 mm implantiert werden. Jedoch hat sich in Deutschland und der Schweiz ein Trend zur Line-to-Line-Technik, mit einer geplanten Zementmanteldicke von 1 mm (Twinsys, Corail, Avenir, Quadra) aufgezeigt, dem Prinzip der Müller-Geradschaft-Prothese und der Kerboul-Charnley-Prothese folgend, auch wenn diese an sich als „french paradoxon“ postuliert werden. In den EPRD-5-Jahres-Ergebnissen scheinen die neueren Line-to-Line-Prothesen etwas schlechter abzuschneiden. Die besten Ergebnisse erzielt der „MS 30“ in Deutschland und der „Exeter“ in England. Hierbei handelt es sich um polierte Geradschäfte mit Zentraliser und Subsidence-Raum an der Spitze mit einem 2–4 mm Zementmantel in guter Zementiertechnik.
Analysing and predicting the advance rate of a tunnel boring machine (TBM) in hard rock is integral to tunnelling project planning and execution. It has been applied in the industry for several decades with varying success. Most prediction models are based on or designed for large-diameter TBMs, and much research has been conducted on related tunnelling projects. However, only a few models incorporate information from projects with an outer diameter smaller than 5 m and no penetration prediction model for pipe jacking machines exists to date. In contrast to large TBMs, small-diameter TBMs and their projects have been considered little in research. In general, they are characterised by distinctive features, including insufficient geotechnical information, sometimes rather short drive lengths, special machine designs and partially concurring lining methods like pipe jacking and segment lining. A database which covers most of the parameters mentioned above has been compiled to investigate the performance of small-diameter TBMs in hard rock. In order to provide sufficient geological and technical variance, this database contains 37 projects with 70 geotechnically homogeneous areas. Besides the technical parameters, important geotechnical data like lithological information, unconfined compressive strength, tensile strength and point load index is included and evaluated. The analysis shows that segment lining TBMs have considerably higher penetration rates in similar geological and technical settings mostly due to their design parameters. Different methodologies for predicting TBM penetration, including state-of-the-art models from the literature as well as newly derived regression and machine learning models, are discussed and deployed for backward modelling of the projects contained in the database. New ranges of application for small-diameter tunnelling in several industry-standard penetration models are presented, and new approaches for the penetration prediction of pipe jacking machines in hard rock are proposed.
Der Online-Handel verzeichnet seit Jahren ein stetiges Wachstum. Durch die COVID-19-Pandemie kaufen nun auch Nutzende, die zuvor physische Kanäle bevorzugten, vermehrt online ein. Der Anbietererfolg hängt dabei wesentlich von der Kenntnis über die Kund*innen ab. Allerdings dominieren einige große Anbieter den Markt, während kleinere Online-Shops Schwierigkeiten haben, ihre Angebote zu personalisieren. Eine Lösung bietet der Ansatz selbstbestimmter Identitäten. Dieser ermöglicht Kund*innen, ihre eigenen Shoppingdaten zu kontrollieren und sie selektiv mit Online-Shops zu teilen. Dadurch können individuelle Wünsche und Anforderungen der Kund*innen in Online-Shops berücksichtigt und ein personalisiertes Angebot sowie eine gute Nutzungserfahrung geboten werden. Trotz des großen Potenzials selbstbestimmter Identitäten ist der Ansatz in Deutschland kaum verbreitet. Dieser Beitrag beleuchtet den Einsatz selbstbestimmter Identitäten im Online-Handel. Mithilfe eines menschenzentrierten Gestaltungsprozesses wurden Personas und Ist-Szenarien erstellt, sowie daraus resultierend Anforderungen erhoben und Potenziale identifiziert. Auf Basis dessen konnte ein Daten- und Architekturmodell zur Integration von selbstbestimmten Identitäten im Online-Handel entwickelt werden.
This report examines exporters’ challenges and possible solutions for public intervention to promote foreign trade. Based on fieldwork conducted in Georgia, we explore which policy approaches can help to stimulate Georgian exports further. Our outcomes show that exporters face substantial barriers such as navigating complex trade regulations, lack of knowledge about target markets, trade finance gaps, as well as new export promotion programs (EPPs) in competitor countries. Other upper-middle-income countries can learn from our results that exporters can significantly benefit from a comprehensive export promotion strategy combined with an ecosystem-based “team” approach. EPPs related to awareness and capacity building in Georgia should be part of this strategy, focusing on challenges such as a lack of knowledge about trade practices and international business skills. Other EPPs must help to mitigate related market failures, as information gathering is costly, and firms have no incentive to share this information with competitors. Furthermore, targeted marketing support and customer matchmaking can answer Georgian exporters’ challenges, such as lack of market access and low sector visibility. Our results also show that public intervention through financial support and risk mitigation is essential for firms with an international orientation. The high-quality, rich outcomes provide significant value for other upper-middle-income countries by exploring the example of Georgia’s contemporary circumstances in an in-depth manner based on extensive interviews and document analysis. Limitations include that our work primarily relies on qualitative data and further research could involve a quantitative study with a diverse range of sectors.
Photovoltaic-heat pump (PV-HP) combinations with battery and energy management systems are becoming increasingly popular due to their ability to increase the autarchy and utilization of self-generated PV electricity. This trend is driven by the ongoing electrification of the heating sector and the growing disparity between growing electricity costs and reducing feed-in tariffs in Germany. Smart control strategies can be employed to control and optimize the heat pump operation to achieve higher self-consumption of PV electricity. This work presents the evaluation results of a smart-grid ready controlled PV-HP-battery system in a single-family household in Germany, using 1-minute-high-resolution field measurement data. Within 12 months evaluation period, a self-consumption of 43% was determined. The solar fraction of the HP amounts to 36%, enabled also due to higher set temperatures for space heating and domestic hot water production. Accordingly, the SPF decreases by 4.0% the space heating and by 5.7% in the domestic hot water mode. The combined seasonal performance factor for the heat pump system increases from 4.2 to 6.7, when only considering the electricity taken from the grid and disregarding the locally generated electricity supplied from photovoltaic and battery units.
The last decades have seen the evolution of industrial production into more sophisticated processes. The development of specialized, high-end machines has increased the importance of predictive maintenance of mechanical systems to produce high-quality goods and avoid machine breakdowns. Predictive maintenance has two main objectives: to classify the current status of a machine component and to predict the maintenance interval by estimating its remaining useful life (RUL). Nowadays, both objectives are covered by machine learning and deep learning approaches and require large training datasets that are often not available. One possible solution may be transfer learning, where the knowledge of a larger dataset is transferred to a smaller one. This thesis is primarily concerned with transfer learning for predictive maintenance for fault classification and RUL estimation. The first part presents the state-of-the-art machine learning techniques with a focus on techniques applicable to predictive maintenance tasks (Chapter 2). This is followed by a presentation of the machine tool background and current research that applies the previously explained machine learning techniques to predictive maintenance tasks (Chapter 3). One novelty of this thesis is that it introduces a new intermediate domain that represents data by focusing on the relevant information to allow the data to be used on different domains without losing relevant information (Chapter 4). The proposed solution is optimized for rotating elements. Therefore, the presented intermediate domain creates different layers by focusing on the fault frequencies of the rotating elements. Another novelty of this thesis is its semi and unsupervised transfer learning-based fault classification approach for different component types under different process conditions (Chapter 5). It is based on the intermediate domain utilized by a convolutional neural network (CNN). In addition, a novel unsupervised transfer learning loss function is presented based on the maximum mean discrepancy (MMD), one of the state-of-the-art algorithms. It extends the MMD by considering the intermediate domain layers; therefore, it is called layered maximum mean discrepancy (LMMD). Another novelty is an RUL estimation transfer learning approach for different component types based on the data of accelerometers with low sampling rates (Chapter 6). It applies the feature extraction concepts of the classification approach: the presented intermediate domain and the convolutional layers. The features are then used as input for a long short-term memory (LSTM) network. The transfer learning is based on fixed feature extraction, where the trained convolutional layers are taken over. Only the LSTM network has to be trained again. The intermediate domain supports this transfer learning type, as it should be similar for different component types. In addition, it enables the practical usage of accelerometers with low sampling rates during transfer learning, which is an absolute novelty. All presented novelties are validated in detailed case studies using the example of bearings (Chapter 7). In doing so, their superiority over state-of-the-art approaches is demonstrated.
Physical unclonable functions (PUFs) are increasingly generating attention in the field of hardware-based security for the Internet of Things (IoT). A PUF, as its name implies, is a physical element with a special and unique inherent characteristic and can act as the security anchor for authentication and cryptographic applications. Keeping in mind that the PUF outputs are prone to change in the presence of noise and environmental variations, it is critical to derive reliable keys from the PUF and to use the maximum entropy at the same time. In this work, the PUF output positioning (POP) method is proposed, which is a novel method for grouping the PUF outputs in order to maximize the extracted entropy. To achieve this, an offset data is introduced as helper data, which is used to relax the constraints considered for the grouping of PUF outputs, and deriving more entropy, while reducing the secret key error bits. To implement the method, the key enrollment and key generation algorithms are presented. Based on a theoretical analysis of the achieved entropy, it is proven that POP can maximize the achieved entropy, while respecting the constraints induced to guarantee the reliability of the secret key. Moreover, a detailed security analysis is presented, which shows the resilience of the method against cyber-security attacks. The findings of this work are evaluated by applying the method on a hybrid printed PUF, where it can be practically shown that the proposed method outperforms other existing group-based PUF key generation methods.
Background: Assistive Robotic Arms are designed to assist physically disabled people with daily activities. Existing joysticks and head controls are not applicable for severely disabled people such as people with Locked-in Syndrome. Therefore, eye tracking control is part of ongoing research. The related literature spans many disciplines, creating a heterogeneous field that makes it difficult to gain an overview.
Objectives: This work focuses on ARAs that are controlled by gaze and eye movements. By answering the research questions, this paper provides details on the design of the systems, a comparison of input modalities, methods for measuring the performance of these controls, and an outlook on research areas that gained interest in recent years.
Methods: This review was conducted as outlined in the PRISMA 2020 Statement. After identifying a wide range of approaches in use the authors decided to use the PRISMA-ScR extension for a scoping review to present the results. The identification process was carried out by screening three databases. After the screening process, a snowball search was conducted.
Results: 39 articles and 6 reviews were included in this article. Characteristics related to the system and study design were extracted and presented divided into three groups based on the use of eye tracking.
Conclusion: This paper aims to provide an overview for researchers new to the field by offering insight into eye tracking based robot controllers. We have identified open questions that need to be answered in order to provide people with severe motor function loss with systems that are highly useable and accessible.