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Im Rahmen des Technologiescreenings sind zunächst relevante Technologien, die Einfluss auf das Energienachfrageverhalten für Haushalte besitzen, identifiziert worden. Dabei ist ausschließlich eine technologische Betrachtung erfolgt, das individuelle Nutzerverhalten von Haushaltsbewohnern wurde dabei nicht betrachtet. Die Einordnung der Technologien sind in Standard Energietechnologien: Erzeuger, Umwandler, Verbraucher und Speicher kategorisiert. Zudem zeigt die in die Kategorien Messsysteme, Gebäudeautomation und Energiemanagementsysteme. Dabei handelt es sich um, digitale Technologien mit Aspekten und Anwendungen von Energietransparenz und -management. Zeitraum des kontinuierlichen Technologie-Screenings war von 2017-2020.
Das interdisziplinäre Forschungsprojekt “Smarte Technologien für Unternehmen” untersuchte im Zeitraum von Juli 2017 bis Dezember 2020 Anwendungs- und Akzeptanzprobleme zum Einsatz smarter Technologien in KMU und entwickelte darauf aufbauend Lösungsansätze zur Steigerung der Energieeffizienz sowie zum Energie- und Lastmanagement. Dazu wurden smarte Technologien zunächst im Zuge eines Screenings identifiziert, kategorisiert und bewertet. In den qualitativen und quantitativen Nutzeranalysen wurden Unternehmer*innen in den Fokus der Analyse gestellt, um den Wissensstand sowie Chancen und Barrieren zum Einsatz smarter Technologien in KMU darzulegen. Mit der Durchführung transdisziplinärer Anwendungstests wurde ein zentraler Lösungsansatz entwickelt: Die Effizienzanalyse von KMU mittels mobiler Messtechnik und Visualisierungstools als potenzielle Strategie zur Reduktion von Energieverbräuchen.
Die Ergebnisse dieses anwendungsorientierten Forschungsprojektes zeigen die Anwendungs- und Akzeptanzprobleme zum Einsatz smarter Technologien in KMU auf und geben Handlungsoptionen zur Steigerung der Energieeffizienz mit Hilfe ausgewählter smarter Produkte und Tools.
In this paper we describe traffic sign recognition with neural networks in the frequency domain. Traffic signs exist in all countries to regulate the traffic of vehicles and pedestrians. Each country has its own set of traffic signs that are more or less similar. They consist of a set of abstract forms, symbols, numbers and letters, which are combined into different signs. Automatic traffic sign recognition is important for driver assistance systems and for autonomous driving. Traffic sign recognition is a subtype of image recognition. The traffic signs are usually recorded by a camera and must be recognized in real time, i.e. assigned to a class. We use neural networks for traffic sign recognition. The special feature of our method is that the traffic sign recognition does not take place in the spatial domain but in the frequency domain. This has advantages because it is possible to significantly reduce the number of neurons and thus the computing effort of the neural network compared to a conventional neural network.
The development and adoption of digital twins (DT) for Quality-by-Design (QbD)-based processes with flexible operating points within a proven acceptable range (PAR) and automation through Advanced Process Control (APC) with Process Analytical Technology (PAT) instead of conventional process execution based on offline analytics and inflexible process set points is one of the great challenges in modern biotechnology. Virus-like particles (VLPs) are part of a line of innovative drug substances (DS). VLPs, especially those based on human immunodeficiency virus (HIV), HIV-1 Gag VLPs, have very high potential as a versatile vaccination platform, allowing for pseudotyping with heterologous envelope proteins, e.g., the S protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As enveloped VLPs, optimal process control with minimal hold times is essential. This study demonstrates, for the first time, the use of a digital twin for the overall production process of HIV-1 Gag VLPs from cultivation, clarification, and purification to lyophilization. The accuracy of the digital twins is in the range of 0.8 to 1.4% in depth filtration (DF) and 4.6 to 5.2% in ultrafiltration/diafiltration (UFDF). The uncertainty due to variability in the model parameter determination is less than 4.5% (DF) and less than 3.8% (UFDF). In the DF, a prediction of the final filter capacity was demonstrated from as low as 5.8% (9mbar) of the final transmembrane pressure (TMP). The scale-up based on DT in chromatography shows optimization potential in productivity up to a factor of 2. The schedule based on DT and PAT for APC has been compared to conventional process control, and hold-time and process duration reductions by a factor of 2 have been achieved. This work lays the foundation for the short-term validation of the DT and PAT for APC in an automated S7 process environment and the conversion from batch to continuous production.
Different mechanisms mediate the toxicity of RNA. Genomic retroviral mRNA hijacks infected host cell factors to enable virus replication. The viral genomic RNA of the human immunodeficiency virus (HIV) encompasses nine genes encoding in less than 10 kb all proteins needed for replication in susceptible host cells. To do so, the genomic RNA undergoes complex alternative splicing to facilitate the synthesis of the structural, accessory, and regulatory proteins. However, HIV strongly relies on the host cell machinery recruiting cellular factors to complete its replication cycle. Antiretroviral therapy (ART) targets different steps in the cycle, preventing disease progression to the acquired immunodeficiency syndrome (AIDS). The comprehension of the host immune system interaction with the virus has fostered the development of a variety of vaccine platforms. Despite encouraging provisional results in vaccine trials, no effective vaccine has been developed, yet. However, novel promising vaccine platforms are currently under investigation.
Despite great efforts to develop a vaccine against human immunodeficiency virus (HIV), which causes AIDS if untreated, no approved HIV vaccine is available to date. A promising class of vaccines are virus-like particles (VLPs), which were shown to be very effective for the prevention of other diseases. In this study, production of HI-VLPs using different 293F cell lines, followed by a three-step purification of HI-VLPs, was conducted. The quality-by-design-based process development was supported by process analytical technology (PAT). The HI-VLP concentration increased 12.5-fold while >80% purity was achieved. This article reports on the first general process development and optimization up to purification. Further research will focus on process development for polishing and formulation up to lyophilization. In addition, process analytical technology and process modeling for process automation and optimization by digital twins in the context of quality-by-design framework will be developed.
Resilience in the urban context can be described as a continuum of absorptive, adaptive, and transformative capacities. The need to move toward a sustainable future and bounce forward after any disruption has led recent urban resilience initiatives to engage with the concept of transformative resilience when and where conventional and top-down resilience initiatives are less likely to deliver effective strategies, plans, and implementable actions. Transformative resilience pathways emphasize the importance of reflexive governance, inclusive co-creation of knowledge, innovative and collaborative learning, and self-organizing processes. To support these transformative pathways, considering techno-social co-evolution and digital transformation, using new data sources such as Volunteered Geographic Information (VGI) and crowdsourcing are being promoted. However, a literature review on VGI and transformative resilience reveals that a comprehensive understanding of the complexities and capacities of utilizing VGI for transformative resilience is lacking. Therefore, based on a qualitative content analysis of available resources, this paper explores the key aspects of using VGI for transformative resilience and proposes a comprehensive framework structured around the identified legal, institutional, social, economic, and technical aspects to formalize the process of adopting VGI in transformative resilience initiatives.
This paper documents the design, implementation and evaluation of the Unfolding Space Glove—an open source sensory substitution device. It transmits the relative position and distance of nearby objects as vibratory stimuli to the back of the hand and thus enables blind people to haptically explore the depth of their surrounding space, assisting with navigation tasks such as object recognition and wayfinding. The prototype requires no external hardware, is highly portable, operates in all lighting conditions, and provides continuous and immediate feedback—all while being visually unobtrusive. Both blind (n = 8) and blindfolded sighted participants (n = 6) completed structured training and obstacle courses with both the prototype and a white long cane to allow performance comparisons to be drawn between them. The subjects quickly learned how to use the glove and successfully completed all of the trials, though still being slower with it than with the cane. Qualitative interviews revealed a high level of usability and user experience. Overall, the results indicate the general processability of spatial information through sensory substitution using haptic, vibrotactile interfaces. Further research would be required to evaluate the prototype’s capabilities after extensive training and to derive a fully functional navigation aid from its features.
Pressure injuries remain a serious health complication for patients and nursing staff. Evidence from the past decade has not been analysed through narrative synthesis yet. PubMed, Embase, CINAHL Complete, Web of Science, Cochrane Library, and other reviews/sources were screened. Risk of bias was evaluated using a slightly modified QUIPS tool. Risk factor domains were used to assign (non)statistically independent risk factors. Hence, 67 studies with 679,660 patients were included. In low to moderate risk of bias studies, non-blanchable erythema reliably predicted pressure injury stage 2. Factors influencing mechanical boundary conditions, e.g., higher interface pressure or BMI < 18.5, as well as factors affecting interindividual susceptibility (male sex, older age, anemia, hypoalbuminemia, diabetes, hypotension, low physical activity, existing pressure injuries) and treatment-related aspects, such as length of stay in intensive care units, were identified as possible risk factors for pressure injury development. Health care professionals’ evidence-based knowledge of above-mentioned risk factors is vital to ensure optimal prevention and/or treatment. Openly accessible risk factors, e.g., sex, age, BMI, pre-existing diabetes, and non-blanchable erythema, can serve as yellow flags for pressure injury development. Close communication concerning further risk factors, e.g., anemia, hypoalbuminemia, or low physical activity, may optimize prevention and/or treatment. Further high-quality evidence is warranted.
Im Rahmen des Technologie-Screenings wurden smarte Technologien für den Einsatz in mittelständischen Unternehmen (vorzugsweise KMU) im Zeitraum von 2017-2020 in einem kontinuierlichen Monitoringprozess betrachtet. Dadurch konnte mit dem Screening ein umfassender Überblick über die Angebotsseite und den Markt smarter Technologien geschaffen werden. Ebenso wurden potenzielle Technologien für den Einsatz im Anwendungstest des Forschungsprojekts VISE-U identifiziert. Insgesamt umfasst das Technologie-Screening sechs spezifische Technologie-Kategorien, denen wiederum einzelne Systeme auf Herstellerebene zugeordnet wurden. So konnten in Summe 20 Systeme unterschiedlicher Hersteller hinsichtlich des Aufbaus sowie der Funktionsweise samt Technologie-Steckbrief beschrieben werden. Die Steckbriefe zeigen dazu die technische Beschreibung, Komponenten sowie Schnittstellen der Systeme auf und referenzieren auf weiterführende Informationen auf den Webseiten der Hersteller.