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In order to reduce energy consumption of homes, it is important to make transparent which devices consume how much energy. However, power consumption is often only monitored aggregated at the house energy meter. Disaggregating this power consumption into the contributions of individual devices can be achieved using Machine Learning. Our work aims at making state of the art disaggregation algorithms accessibe for users of the open source home automation platform Home Assistant.
Immunosorbent turnip vein clearing virus (TVCV) particles displaying the IgG-binding domains D and E of Staphylococcus aureus protein A (PA) on every coat protein (CP) subunit (TVCVPA) were purified from plants via optimized and new protocols. The latter used polyethylene glycol (PEG) raw precipitates, from which virions were selectively re-solubilized in reverse PEG concentration gradients. This procedure improved the integrity of both TVCVPA and the wild-type subgroup 3 tobamovirus. TVCVPA could be loaded with more than 500 IgGs per virion, which mediated the immunocapture of fluorescent dyes, GFP, and active enzymes. Bi-enzyme ensembles of cooperating glucose oxidase and horseradish peroxidase were tethered together on the TVCVPA carriers via a single antibody type, with one enzyme conjugated chemically to its Fc region, and the other one bound as a target, yielding synthetic multi-enzyme complexes. In microtiter plates, the TVCVPA-displayed sugar-sensing system possessed a considerably increased reusability upon repeated testing, compared to the IgG-bound enzyme pair in the absence of the virus. A high coverage of the viral adapters was also achieved on Ta2O5 sensor chip surfaces coated with a polyelectrolyte interlayer, as a prerequisite for durable TVCVPA-assisted electrochemical biosensing via modularly IgG-assembled sensor enzymes.
Eine Sensorvorrichtung (10;110;210;310;410) zur Erfassung eines Magnetfelds, mit einer Wiegand-Sensoreinheit (12;112;212) umfassend: • - mindestens zwei Wiegand-Drähte (20) und • - eine Spulenanordnung (22;122;222), die die mindestens zwei Wiegand-Drähte (20) radial umschließt und die • • • ein Sensorelement (26;126;226) und • • ein Triggerelement (28;128;228), durch das ein Triggermagnetfeld erzeugbar ist, bildet, ist bekannt. Um ein magnetbasiertes Sensorsystem (300;400) zur Erfassung einer Bewegung eines beweglichen Objekts (301;401) zu ermöglichen, das ohne externe Energieversorgung zuverlässig sowie energieeffizient arbeitet und kostengünstig hergestellt werden kann, ist bei der erfindungsgemäßen Sensorvorrichtung (10;110;210;310;410) eine Wiegand-Triggereinheit (14;14a) vorhanden, umfassend: • - einen Wiegand-Draht (30) und • - eine Trigger-Sensorspule (32), die den Wiegand-Draht (30) radial umschließt, wobei ein erstes Ende der Trigger-Sensorspule (32) der Wiegand-Triggereinheit (14;14a) mit einem ersten Ende des Triggerelements (28;128;228) der Wiegand-Sensoreinheit (12;112;212) elektrisch verbunden ist und ein zweites Ende der Trigger-Sensorspule (32) der Wiegand-Triggereinheit (14;14a) mit einem zweiten Ende des Triggerelements (28;128;228) der Wiegand-Sensoreinheit (12;112;212) elektrisch verbunden ist. Auf diese Weise verstärkt ein in der Trigger-Sensorspule (32) erzeugter Impuls das Gesamtmagnetfeld, das auf die Wiegand-Drähte (20) in der Sensoreinheit einwirkt, derart, dass die Triggefeldstärke aller Wiegand-Drähte (20) überschritten wird und diese im wesentlichen zeitgleich auslösen.
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This study describes the development of a new combined polysaccharide-matrix-based technology for the immobilization of Lactobacillus rhamnosus GG (LGG) bacteria in biofilm form. The new composition allows for delivering the bacteria to the digestive tract in a manner that improves their robustness compared with planktonic cells and released biofilm cells. Granules consisting of a polysaccharide matrix with probiotic biofilms (PMPB) with high cell density (>9 log CFU/g) were obtained by immobilization in the optimized nutrient medium. Successful probiotic loading was confirmed by fluorescence microscopy and scanning electron microscopy. The developed prebiotic polysaccharide matrix significantly enhanced LGG viability under acidic (pH 2.0) and bile salt (0.3%) stress conditions. Enzymatic extract of feces, mimicking colon fluid in terms of cellulase activity, was used to evaluate the intestinal release of probiotics. PMPB granules showed the ability to gradually release a large number of viable LGG cells in the model colon fluid. In vivo, the oral administration of PMPB granules in rats resulted in the successful release of probiotics in the colon environment. The biofilm-forming incubation method of immobilization on a complex polysaccharide matrix tested in this study has shown high efficacy and promising potential for the development of innovative biotechnologies.
Environmental emissions, global warming, and energy-related concerns have accelerated the advancements in conventional vehicles that primarily use internal combustion engines. Among the existing technologies, hydrogen fuel cell electric vehicles and fuel cell hybrid electric vehicles may have minimal contributions to greenhouse gas emissions and thus are the prime choices for environmental concerns. However, energy management in fuel cell electric vehicles and fuel cell hybrid electric vehicles is a major challenge. Appropriate control strategies should be used for effective energy management in these vehicles. On the other hand, there has been significant progress in artificial intelligence, machine learning, and designing data-driven intelligent controllers. These techniques have found much attention within the community, and state-of-the-art energy management technologies have been developed based on them. This manuscript reviews the application of machine learning and intelligent controllers for prediction, control, energy management, and vehicle to everything (V2X) in hydrogen fuel cell vehicles. The effectiveness of data-driven control and optimization systems are investigated to evolve, classify, and compare, and future trends and directions for sustainability are discussed.
Die Auswahl der passenden Geschäftsprozesse für eine Automatisierung mittels Robotic Process Automation (RPA) ist für den Erfolg von RPA-Projekten entscheidend. Das vorliegende Kapitel liefert dafür Selektionskriterien, die aus einer qualitativen Studie mit elf interviewten RPA-Experten aus dem Versicherungsumfeld resultieren. Das Ergebnis umfasst eine gewichtete Liste von sieben Dimensionen und 51 Prozesskriterien, welche die Automatisierung mit Softwarerobotern begünstigen beziehungsweise deren Nichterfüllung eine Umsetzung erschweren oder sogar verhindern. Die drei wichtigsten Kriterien zur Auswahl von Geschäftsprozessen für die Automatisierung mittels RPA umfassen die Entlastung der an dem Prozess mitwirkenden Mitarbeiter (Arbeitnehmerentlastung), die Ausführbarkeit des Prozesses mittels Regeln (Regelbasierte Prozessteuerung) sowie ein positiver Kosten-Nutzen-Vergleich. Auf diesen Ergebnissen aufbauend wird ein Vergleich mit den bereits bekannten Selektionskriterien aus der Literatur erstellt und diskutiert. Praktiker können die Ergebnisse verwenden, um eine systematische Auswahl von RPA-relevanten Prozessen vorzunehmen. Aus wissenschaftlicher Perspektive stellen die Ergebnisse eine Grundlage zur Erklärung des Erfolgs und Misserfolgs von RPA-Projekten dar.
Anti-bias trainings are increasingly demanded and practiced in academia and industry to increase employees’ sensitivity to discrimination, racism, and diversity. Under the heading of “Diversity Management”, anti-bias trainings are mainly offered as one-off workshops intending to raise awareness of unconscious biases, create a diversity-affirming corporate culture, awake awareness of the potential of diversity, and ultimately enable the reflection of diversity in development processes. However, coming from childhood education, research and scientific articles on the sustainable effectiveness of anti-bias in adulthood, especially in academia, are very scarce. In order to fill this research gap, the paper explores how sustainable the effects of individual anti-bias trainings on the behavior of participants are. In order to investigate this, participant observation in a qualitative pre-post setting was conducted, analyzing anti-bias trainings in an academic context. Two observers actively participated in the training sessions and documented the activities and reflection processes of the participants. Overall, the results question the effectiveness of single anti-bias trainings and show that a target-group adaptive approach is mandatory due to the background of the approach in early childhood education. Therefore, it can be concluded that anti-bias work needs to be adapted to the target group’s needs and reality of life. Furthermore, the study reveals that single anti-bias trainings must be embedded in a holistic diversity management approach to stimulate sustainable reflection processes among the target group. This paper is one of the first to scientifically evaluate anti-bias training effectiveness, especially in engineering sciences and the university context.
Software development projects often fail because of insufficient code quality. It is now well documented that the task of testing software, for example, is perceived as uninteresting and rather boring, leading to poor software quality and major challenges to software development companies. One promising approach to increase the motivation for considering software quality is the use of gamification. Initial research works already investigated the effects of gamification on software developers and come to promising. Nevertheless, a lack of results from field experiments exists, which motivates the chapter at hand. By conducting a gamification experiment with five student software projects and by interviewing the project members, the chapter provides insights into the changing programming behavior of information systems students when confronted with a leaderboard. The results reveal a motivational effect as well as a reduction of code smells.