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Scientific or statistical research has long been the domain of dedicated programming languages such as R, SPSS or SAS. A few years other competitors entered the arena, among them Python with its powerful SciPy package. The following article introduces SciPy by applying a small subset of its functionality to a well-known dataset.
The increasing complexity of tasks that are required to be executed by robots demands higher reliability of robotic platforms. For this, it is crucial for robot developers to consider fault diagnosis. In this study, a general non-intrusive fault diagnosis system for robotic platforms is proposed. A mini-PC is non-intrusively attached to a robot that is used to detect and diagnose faults. The health data and diagnosis produced by the mini-PC is then standardized and transmitted to a remote-PC. A storage device is also attached to the mini-PC for data logging of health data in case of loss of communication with the remote-PC. In this study, a hybrid fault diagnosis method is compared to consistency-based diagnosis (CBD), and CBD is selected to be deployed on the system. The proposed system is modular and can be deployed on different robotic platforms with minimum setup.
Renewable resources are gaining increasing interest as a source for environmentally benign biomaterials, such as drug encapsulation/release compounds, and scaffolds for tissue engineering in regenerative medicine. Being the second largest naturally abundant polymer, the interest in lignin valorization for biomedical utilization is rapidly growing. Depending on its resource and isolation procedure, lignin shows specific antioxidant and antimicrobial activity. Today, efforts in research and industry are directed toward lignin utilization as a renewable macromolecular building block for the preparation of polymeric drug encapsulation and scaffold materials. Within the last five years, remarkable progress has been made in isolation, functionalization and modification of lignin and lignin-derived compounds. However, the literature so far mainly focuses lignin-derived fuels, lubricants and resins. The purpose of this review is to summarize the current state of the art and to highlight the most important results in the field of lignin-based materials for potential use in biomedicine (reported in 2014⁻2018). Special focus is placed on lignin-derived nanomaterials for drug encapsulation and release as well as lignin hybrid materials used as scaffolds for guided bone regeneration in stem cell-based therapies.
Möglichkeiten und Grenzen der Baustoffanalytik und anwendungstechnische Prüfungen an Objekten
(2018)
Untersuchungen zum Einfluss von chemischen Aktivatoren und Templaten auf die Zementhydratation
(2018)
Bei der Übertragung und Speicherung von Daten ist es eine wesentliche Frage, inwieweit die Daten komprimiert werden können, ohne dass deren Informationsgehalt verloren geht.
Ein Maß für den Informationsgehalt von Daten ist also von grundlegender Bedeutung. Vor etwa siebzig Jahren hat C. E. Shannon ein solches Maß eingeführt und damit das Lehr- und Forschungsgebiet der Informationstheorie begründet, welches seit dem bis heute hin wesentlich zur Konzeption und Realisierung von Informationsund Kommunikationstechnologien beigetragen hat. Etwa zwanzig Jahre später hat A. N. Kolmogorov ein anderes Maß für den Informationsgehalt von Daten eingeführt. Während die Shannonsche Informationstheorie zum Curriculum von mathematischen, informatischen und elektrotechnischen Studiengängen gehört, ist die Algorithmische Informationstheorie von Kolmogorov weit weniger bekannt und eher Gegenstand von speziellen Lehrveranstaltungen.
Seit einigen Jahren nimmt allerdings die Beschäftigung mit dieser Theorie zu, zumal in der einschlägigen Literatur von erfolgreichen praktischen Anwendungen der Theorie berichtet wird. Die vorliegende Arbeit gibt eine Einführung in grundlegende Ideen dieser Theorie und beschreibt deren Anwendungsmöglichkeiten bei einigen ausgewählten Problemstellungen der Theoretischen Informatik.
Die Ausarbeitung kann als Skript für einführende Lehrveranstaltungen in die Algorithmische Informationstheorie sowie als Lektüre zur Einarbeitung in die Thematik als Ausgangspunkt für Forschungs- und Entwicklungsarbeiten verwendet werden.
Seit 2012 wird an der Hochschule Bonn-Rhein-Sieg die Studieneingangsphase im Qualitätspakt Lehre gefördert. Ein wesentliches Anliegen im Projekt „Pro-MINT-us“ ist die Einbeziehung der gesamten Hochschule, um keine isolierten Maßnahmen anzubieten, sondern die im Projekt entwickelten Lehrideen nachhaltig zu verankern.
Organisationen wollen Produkte mit guter User Experience herstellen. Durch die Evaluation der organisationalen UX-Gestaltungskompetenz können Organisationen erkennen, wie stark ihre momentane UX-Gestaltungskompetenz ausgeprägt ist und wie die Kompetenz gezielt gesteigert werden kann. Für die Abbildung der aktuellen Kompetenz werden ein Fragebogen zur theoretischen Kompetenz und ein Fragebogen für die Produktevaluation kombiniert. Durch diese Kombination wird die Kompetenz der Organisation aus der Handlungs- und der Ergebnisperspektive betrachtet. Für die Erarbeitung von Handlungsfeldern zur Verbesserung der Kompetenz werden qualitative Interviews durchgeführt und mit den Ergebnissen der quantitativen Erhebungen verknüpft. Durch einen anschließenden Ergebnisworkshop erarbeiten sich die Mitglieder der Organisation einen effizienten Weg zur Steigerung der organisationalen UX-Kompetenz.
After replanting apple (Malus domestica Borkh.) on the same site severe growth suppressions, and a decline in yield and fruit quality are observed in all apple producing areas worldwide. The causes of this complex phenomenon, called apple replant disease (ARD), are only poorly understood up to now which is in part due to inconsistencies in terms and methodologies. Therefore we suggest the following definition for ARD: ARD describes a harmfully disturbed physiological and morphological reaction of apple plants to soils that faced alterations in their (micro-) biome due to the previous apple cultures. The underlying interactions likely have multiple causes that extend beyond common analytical tools in microbial ecology. They are influenced by soil properties, faunal vectors, and trophic cascades, with genotype-specific effects on plant secondary metabolism, particularly phytoalexin biosynthesis. Yet, emerging tools allow to unravel the soil and rhizosphere (micro-) biome, to characterize alterations of habitat quality, and to decipher the plant reactions. Thereby, deep insights into the reactions taking place at the root rhizosphere interface will be gained. Counteractions are suggested, taking into account that culture management should emphasize on improving soil microbial and faunal diversity as well as habitat quality rather than focus on soil disinfection.
Gegenstand dieser Arbeit sind Untersuchungen zur Detektion von verpackten Gefahrstoffen wie beispielsweise Explosivstoffen. Hierzu wird in einem ersten Schritt die Verpackung mittels Laserbohrens durchdrungen, um anschließend den nun freiliegenden Gefahrstoff nachweisen zu können. Dies geschieht einerseits durch eine lasergestützte Probenahme und anschließende Detektion mit gängigen chemisch-analytischen Verfahren sowie direkt bei der Wechselwirkung zwischen Laser und Gefahrstoff mittels Ramanspektroskopie. Zudem werden schnelle in situ-Techniken im Hinblick auf ihre Eignung zur Überwachung des Laserbohrprozesses untersucht. Hier werden kostengünstige und kompakte Sensortechniken (Messung der Prozessgase durch Halbleitergassensoren, Messung des Luftschalls mittels Kondensatormikrofon) mit aufwendigeren und komplexeren spektroskopischen Verfahren (Plasma- und Ramanspektroskopie) bewertend verglichen. Anhand ausgewählter Modellsysteme in verkleinertem Maßstab werden die unterschiedlichen Verfahren unter Verwendung gängiger Verpackungs- und Hüllenmaterialien sowie anhand ausgewählter Explosivstoffe charakterisiert. Für das Laserverfahren kommen gepulste Nd:YAG Laser mit unterschiedlichen Emissionswellenlängen zum Einsatz.
Die vorliegende Forschungsarbeit setzt sich mit nachhaltigem Verhalten in Bezug auf die Nutzung von Kaffeebehältern an der HBRS auseinander. Anlass dafür ist, dass Pappbecher aufgrund einer Plastikbeschichtung nur schwer recycelbar sind und somit die Umwelt erheblich beeinträchtigen. In diesem Zusammenhang nahmen 204 Studierende an einer Online-Befragung teil. Den Ergebnissen zufolge kommen derzeit vor allem Einweg-Pappbecher zum Einsatz. Zur Modifizierung dieses umweltschädlichen Verhaltens bedarf es an geeigneten Interventionsstrategien. Basierend auf den Ergebnissen sind Maßnahmen zu implementieren, die dem Defizit an Handlungswissen und dem hohen Aufwand entgegenwirken, welcher mit der Verwendung eigens mitgebrachter Becher und den vorhandenen Porzellantassen assoziiert wird. Nach Sicherstellung der ökologischen Vorteile und finanziellen Umsetzbarkeit sollte das bestehende Pfandsystem um praktischere Becher sowie flexible Rückgabemöglichkeiten erweitert werden. Unterstützend ist eine Belohnung in Form von Freigetränken oder einem geringen finanziellen Rabatt sinnvoll, um den automatischen Verbrauch von Pappbechern zu unterbinden.
The epithelial sodium channel (ENaC) is a critical regulator of vertebrate electrolyte homeostasis. ENaC is the only constitutively open ion channel in the degenerin/ENaC protein family, and its expression, membrane abundance, and open probability therefore are tightly controlled. The canonical ENaC is composed of three subunits (, , and ), but a fourth -subunit may replace and form atypical -ENaCs. Using Xenopus laevis as a model, here we found that mRNAs of the - and -subunits are differentially expressed in different tissues and that -ENaC predominantly is present in the urogenital tract. Using whole-cell and single-channel electrophysiology of oocytes expressing Xenopus - or -ENaC, we demonstrate that the presence of the -subunit enhances the amount of current generated by ENaC due to an increased open probability, but also changes current into a transient form. Activity of canonical ENaCs is critically dependent on proteolytic processing of the - and -subunits, and immunoblotting with epitope-tagged ENaC subunits indicated that, unlike -ENaC, the -subunit does not undergo proteolytic maturation by the endogenous protease furin. Furthermore, currents generated by -ENaC were insensitive to activation by extracellular chymotrypsin, and presence of the -subunit prevented cleavage of -ENaC at the cell surface. Our findings suggest that subunit composition constitutes an additional level of ENaC regulation, and we propose that the Xenopus -ENaC subunit represents a functional example that demonstrates the importance of proteolytic maturation during ENaC evolution.
Der globalisierte Kapitalismus, Umweltkatastrophen, Überbevölkerung sowie zunehmende politisch und religiös motivierte Konflikte fordern ein Umdenken ökonomischer Konzepte. Allein mit den herkömmlichen Sozial- und Wirtschaftssystemen lassen sich existenzbedrohende Probleme wie Armut, Hunger, Krankheit, mangelnde Bildung und Betreuung nicht lösen. Es gilt dringend, neue, zukunftsweisende unternehmerische Konzepte zu entwickeln und zu fördern. Seit geraumer Zeit hat sich unter dem Begriff „Social Entrepreneurship“ eine Bewegung etabliert, die versucht, unter Beachtung klassischer Ökonomiegrundsätze gesellschaftliche Herausforderungen nachhaltig zu lösen.
Mit dem Anspruch, die Qualität in der medizinischen Rehabilitation weiterzuentwickeln, haben sich im Jahr 2007 13 Kliniken von acht Trägern zusammengeschlossen. Heute, ein gutes Jahrzehnt später, vereint der Qualitätsverbund Gesundheit rund 30 Reha-Kliniken von elf Trägern, darunter kommunale und kirchliche Institutionen, Privatunternehmen und die Rehazentren der Deutschen Rentenversicherung Baden-Württemberg.
Towards explaining deep learning networks to distinguish facial expressions of pain and emotions
(2018)
Deep learning networks are successfully used for object and face recognition in images and videos. In order to be able to apply such networks in practice, for example in hospitals as a pain recognition tool, the current procedures are only suitable to a limited extent. The advantage of deep learning methods is that they can learn complex non-linear relationships between raw data and target classes without limiting themselves to a set of hand-crafted features provided by humans. However, the disadvantage is that due to the complexity of these networks, it is not possible to interpret the knowledge that is stored inside the network. It is a black-box learning procedure. Explainable Artificial Intelligence (AI) approaches mitigate this problem by extracting explanations for decisions and representing them in a human-interpretable form. The aim of this paper is to investigate the explainable AI method Layer-wise Relevance Propagation (LRP) and apply it to explain how a deep learning network distinguishes facial expressions of pain from facial expressions of emotions such as happiness and disgust.
Background: Local injection of autologous conditioned serum (ACS) is a well-known therapy for inflammatory diseases (IDs). While patients’ blood is incubated to generate ACS (with subsequent centrifugation), immune cells produce high amounts of growth factors and cytokines. This include, amongst others, interleukin-1 receptor antagonist (IL-1ra), interleukins 6 and 10, tumour necrosis factor alpha (TNF-α) and transforming growth factor beta 1 (TGF-β1). The aim of this study was to analyse exosomes release into ACS as well as their cytokine cargo.