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One of the major challenges impeding the energy transition is the intermittency of solar and wind electricity generation due to their dependency on weather changes. The demand-side energy flexibility contributes considerably to mitigate the energy supply/demand imbalances resulting from external influences such as the weather. As one of the largest electricity consumers, the industrial enterprises present a high demand-side flexibility potential from their production processes and on-site energy assets. In this direction, methods are needed with a focus on enabling the energy flexibility and ensure an active participation of such enterprises in the electricity markets especially with variable prices of electricity. This paper presents a generic model library for an industrial enterprise implemented with optimal control for energy flexibility purposes. The components in the model library represent the typical technical units of an industrial enterprise on material, media, and energy flow levels with their operative constraints. A case study of a plastic manufacturing plant using the generic model library is also presented, in which the results of two simulation with different electricity prices are compared and the behavior of the model can be assessed. The results show that the model provides an optimal scheduling of the manufacturing system according to the variations in the electricity prices, and ensures an optimal control for utilities and energy systems needed for the production.
Solar energy plays a central role in the energy transition. Clouds generate locally large fluctuations in the generation output of photovoltaic systems, which is a major problem for energy systems such as microgrids, among others. For an optimal design of a power system, this work analyzed the variability using a spatially distributed sensor network at Stuttgart Airport. It has been shown that the spatial distribution partially reduces the variability of solar radiation. A tool was also developed to estimate the output power of photovoltaic systems using irradiation time series and assumptions about the photovoltaic sites. For days with high fluctuations of the estimated photovoltaic power, different energy system scenarios were investigated. It was found the approach can be used to have a more realistic representation of aggregated PV power taking spatial smoothing into account and that the resulting PV power generation profiles provide a good basis for energy system design considerations like battery sizing.
The desire to connect more and more devices and to make them more intelligent and more reliable, is driving the needs for the Internet of Things more than ever. Such IoT edge systems require sound security measures against cyber-attacks, since they are interconnected, spatially distributed, and operational for an extended period of time. One of the most important requirements for the security in many industrial IoT applications is the authentication of the devices. In this paper, we present a mutual authentication protocol based on Physical Unclonable Functions, where challenge-response pairs are used for both device and server authentication. Moreover, a session key can be derived by the protocol in order to secure the communication channel. We show that our protocol is secure against machine learning, replay, man-in-the-middle, cloning, and physical attacks. Moreover, it is shown that the protocol benefits from a smaller computational, communication, storage, and hardware overhead, compared to similar works.
In recent years, Physical Unclonable Functions (PUFs) have gained significant attraction in the Internet of Things (IoT) for security applications such as cryptographic key generation and entity authentication. PUFs extract the uncontrollable production characteristics of physical devices to generate unique fingerprints for security applications. One common approach for designing PUFs is exploiting the intrinsic features of sensors and actuators such as MEMS elements, which typically exist in IoT devices. This work presents the Cantilever-PUF, a PUF based on a specific MEMS device – Aluminum Nitride (AlN) piezoelectric cantilever. We show the variations of electrical parameters of AlN cantilevers such as resonance frequency, electrical conductivity, and quality factor, as a result of uncontrollable manufacturing process variations. These variations, along with high thermal and chemical stability, and compatibility with silicon technology, makes AlN cantilever a decent candidate for PUF design. We present a cantilever design, which magnifies the effect of manufacturing process variations on electrical parameters. In order to verify our findings, the simulation results of the Monte Carlo method are provided. The results verify the eligibility of AlN cantilever to be used as a basic PUF device for security applications. We present an architecture, in which the designed Cantilever-PUF is used as a security anchor for PUF-enabled device authentication as well as communication encryption.
To deal with frequent power outages in developing countries, people turn to solutions like uninterruptible power supply (UPS), which stores electric energy during normal operating hours and use it to meet energy needs during rolling blackout intervals. Locally produced UPSs of poorer power quality are widely accessible in the marketplaces, and they have a negative impact on power quality. The charging and discharging of the batteries in these UPSs generate significant amount of power losses in weak grid environments. The Smart-UPS is our proposed smart energy metering (SEM) solution for low voltage consumers that is provided by the distribution company. It does not require batteries, therefore there is no power loss or harmonic distortion due to corresponding charging and discharging. Through load flow and harmonic analysis of both traditional UPS and Smart-UPS systems on ETAP, this paper examines their impact on the harmonics and stability of the distribution grid. The simulation results demonstrate that Smart-UPS can assist fixing power quality issues in a developing country like Pakistan by providing cleaner energy than the battery-operated traditional UPSs.
Due to its potential in improving the efficiency of energy supply, smart energy metering (SEM) has become an area of interest with the surge in Internet of Things (IoT). SEM entails remote monitoring and control of the sensors and actuators associated with the energy supply system. This provides a flexible platform to conceive and implement new data driven Demand Side Management (DSM) mechanisms. The IoT enablement allows the data to be gathered and analyzed at requisite granularity. In addition to efficient use of energy resources and provisioning of power, developing countries face an additional challenge of temporal mismatch in generation capacity and load factors. This leads to widespread deployment of inefficient and expensive Uninterruptible Power Supply (UPS) solutions for limited power provisioning during resulting blackouts. Our proposed “Soft-UPS” allows dynamic matching of load and generation through a combination of managed curtailment. This eliminates inefficiencies in the energy and power value chain and allows a data-driven approach to solving a widespread problem in developing countries, simultaneously reducing both upfront and running costs of conventional UPS and storage. A scalable and modular platform is proposed and implemented in this paper. The architecture employs “WiMODino” using LoRaWAN with a “Lite Gateway” and SQLite repository for data storage. Role based access to the system through an android application has also been demonstrated for monitoring and control.
BACKGROUND
Various neutral and alkaline peptidases are commercially available for use in protein hydrolysis under neutral to alkaline conditions. However, the hydrolysis of proteins under acidic conditions by applying fungal aspartic peptidases (FAPs) has not been investigated in depth so far. The aim of this study, thus, was to purify a FAP from the commercial enzyme preparation, ROHALASE® BXL, determine its biochemical characteristics, and investigate its application for the hydrolysis of food and animal feed proteins under acidic conditions.
RESULTS
A Trichoderma reesei derived FAP, with an apparent molecular mass of 45.8 kDa (sodium dodecyl sulfate–polyacrylamide gel electrophoresis; SDS-PAGE) was purified 13.8-fold with a yield of 37% from ROHALASE® BXL. The FAP was identified as an aspartate protease (UniProt ID: G0R8T0) by inhibition and nano-LC-ESI-MS/MS studies. The FAP showed the highest activity at 50°C and pH 4.0. Monovalent cations, organic solvents, and reducing agents were tolerated well by the FAP. The FAP underwent an apparent competitive product inhibition by soy protein hydrolysate and whey protein hydrolysate with apparent Ki-values of 1.75 and 30.2 mg*mL−1, respectively. The FAP showed promising results in food (soy protein isolate and whey protein isolate) and animal feed protein hydrolyses. For the latter, an increase in the soluble protein content of 109% was noted after 30 min.
CONCLUSION
Our results demonstrate the applicability of fungal aspartic endopeptidases in the food and animal feed industry. Efficient protein hydrolysis of industrially relevant substrates such as acidic whey or animal feed proteins could be conducted by applying fungal aspartic peptidases. © 2022 Society of Chemical Industry.
Linear acceleration is a key performance determinant and major training component of many sports. Although extensive research about lower limb kinetics and kinematics is available, consistent definitions of distinctive key body positions, the underlying mechanisms and their related movement strategies are lacking. The aim of this ‘Method and Theoretical Perspective’ article is to introduce a conceptual framework which classifies the sagittal plane ‘shin roll’ motion during accelerated sprinting. By emphasising the importance of the shin segment’s orientation in space, four distinctive key positions are presented (‘shin block’, ‘touchdown’, ‘heel lock’ and ‘propulsion pose’), which are linked by a progressive ‘shin roll’ motion during swing-stance transition. The shin’s downward tilt is driven by three different movement strategies (‘shin alignment’, ‘horizontal ankle rocker’ and ‘shin drop’). The tilt’s optimal amount and timing will contribute to a mechanically efficient acceleration via timely staggered proximal-to-distal power output. Empirical data obtained from athletes of different performance levels and sporting backgrounds are required to verify the feasibility of this concept. The framework presented here should facilitate future biomechanical analyses and may enable coaches and practitioners to develop specific training programs and feedback strategies to provide athletes with a more efficient acceleration technique.
Synthesizing voice with the help of machine learning techniques has made rapid progress over the last years. Given the current increase in using conferencing tools for online teaching, we question just how easy (i.e. needed data, hardware, skill set) it would be to create a convincing voice fake. We analyse how much training data a participant (e.g. a student) would actually need to fake another participants voice (e.g. a professor). We provide an analysis of the existing state of the art in creating voice deep fakes and align the identified as well as our own optimization techniques in the context of two different voice data sets. A user study with more than 100 participants shows how difficult it is to identify real and fake voice (on avg. only 37% can recognize a professor’s fake voice). From a longer-term societal perspective such voice deep fakes may lead to a disbelief by default.
Modelbasierte Zustandsschätzung elektrischer Betriebsmittel der Mittel- und Niederspannungsebenen
(2022)
Im Projekt MOBCOM wird ein neues Verfahren zur Zustandsüberwachung von elektrischen Betriebsmitteln in Niederspannungsnetzen und Anlagen entwickelt. Mittels PLC (power line communication) Technologie werden hochfrequente transiente Vorgänge auf dem Stromkanal und dessen Übertragungseigenschaften erfasst und bewertet.
In dem Abschlussbericht wird ein Prototyp für Powerline-Kommunikation zur Netzüberwachung beschrieben. Der Prototyp basiert auf einem PLC-Empfänger, welcher den Kanal misst, um so Informationen über den PLC-Kanal und den aktuellen Zustand des Stromnetzes zu erhaltet. Der PLC-Empfänger verwendet das Kommunikationssignal, um eine genaue Schätzung des Stromkanals zu erhalten und liefert Informationen zur Erkennung von Teilentladungen und anderen Anomalien im Netz. Diese Überwachung des Stromnetzes macht sich die bestehende PLC-Infrastruktur zunutze und verwendet die ohnehin übertragenen Datensignale, um eine Echtzeitmessung der Kanalübertragungsfunktion und des empfangenen Rauschsignals zu erhalten. Da dieses Signal im Vergleich zu einfacheren Messsensoren mit einer hohen Abtastrate abgetastet wird, enthält es wertvolle Informationen über mögliche Beeinträchtigungen im Netz, die behoben werden müssen. Während die Kanalmessungen auf einem empfangenen PLC-Signal beruhen, können Informationen über Teilentladungen oder andere Störquellen allein durch einen PLC-Empfänger gesammelt werden, d. h. ohne eine PLC-Übertragung. Es wurde ein Prototyp auf Basis von Software Defined Radio entwickelt, der die gleichzeitige Kommunikation und Erfassung für ein Stromnetz implementiert.
Dort, wo Modelle der operativen Energiesystemanalyse untereinander Überschneidungen aufweisen, stellt sich zunächst die Frage, ob sie bei gleichgearteten Fragestellungen auch die gleichen Antworten liefern. Dies zu beantworten war erstes Ziel des hier beschriebenen Vorhabens. Das zweite Ziel war, im Falle von Differenzen zu ermitteln, worin diese begründet liegen. Es waren nicht nur die Modelle selbst, sondern auch das methodische Vorgehen zur Modellerstellung und Simulation in Betracht zu ziehen. Die darauf aufbauende Identifikation von individuellen Optimierungspotenzialen war das dritte Ziel. Da die operative Energiesystemanalyse noch ein recht junger Forschungsbereich ist, existiert darüber hinaus Klärungsbedarf, welches Modell sich für welche Untersuchungen besonders eignet und welches methodische Vorgehen sich empfiehlt. Die Beantwortung dieser Fragen stellte das vierte Ziel des Vorhabens dar.
Das duale Krankenversicherungssystem, mit der Gesetzlichen und Privaten Krankenversicherung (GKV und PKV), ist sehr heterogen, und beide agieren in einem unterschiedlichen komplexen rechtlichen und strukturellen Rahmen. In der GKV sind rund 90 % der Bevölkerung versichert. Der folgende Beitrag zum Kundenmanagement in Krankenversicherungen fokussiert daher die GKV. Viele Maßnahmen des Kundenmanagements, insbesondere bezüglich der Services, haben jedoch trotz der unterschiedlichen Rahmenbedingungen sowohl in der GKV als auch in der PKV Relevanz und werden von Marktteilnehmern beider Systeme ergriffen.
The majority of anterior cruciate ligament (ACL) injuries in team sports are non-contact injuries, with cutting maneuvers identified as high-risk tasks. Young female handball players have been shown to be at greater risk for ACL injuries than males. One risk factor for ACL injuries is the magnitude of the knee abduction moment (KAM). Cutting technique variables on foot placement, overall approach and knee kinematics have been shown to influence the KAM. Since injury risk is believed to increase with increasing task complexity, the purpose of the study was to test the effect of task complexity on technique variables that influence the KAM in female handball players during fake-and-cut tasks.
The purpose of this study was to 1) compare knee joint kinematics and kinetics of fake-and-cut tasks of varying complexity in 51 female handball players and 2) present a case study of one athlete who ruptured her ACL three weeks post data collection. External knee joint moments and knee joint angles in all planes at the instance of the peak external knee abduction moment (KAM) as well as moment and angle time curves were analyzed. Peak KAMs and knee internal rotation moments were substantially higher than published values obtained during simple change-of-direction tasks and, along with flexion angles, differed significantly between the tasks. Introducing a ball reception and a static defender increased joint loads while they partially decreased again when anticipation was lacking. Our results suggest to use game-specific assessments of injury risk while complexity levels do not directly increase knee loading. Extreme values of several risk factors for a post-test injured athlete highlight the need and usefulness of appropriate screenings.
Die Musik-, Kunst- und Kulturszene ist vielfältig und lebt von Individualität. An der Diskussionsrunde zum Thema „Überlebensstrategien während der Pandemie“ nehmen die Musiker*innen Lindy Huppertsberg, Pat Appleton, Martin Verdonk, Tommy Baldu und Markus Birkle am 10.05.2021 teil. Die Teilnehmer*innen der Diskussionsrunde erwirtschaften ihr Einkommen primär über Konzertgagen und sind als freischaffende Musiker*innen etabliert und erfolgreich in der Musikwelt tätig. Trotz großer Übereinstimmungen werden Strategien während der Krise bemerkenswert individuell gewählt. Ebenso vielschichtig ist der Fokus bei der Karriereplanung und Auswahl der musikalischen Projekte. Zwei essenzielle Themenbereiche kristallisieren sich im Verlauf der Unterhaltung heraus: Zum einen die persönlichen singulären Strategien für ein wirtschaftliches Überleben, zum anderen die Auseinandersetzung mit dem Verlust der Möglichkeit auf Resonanz und Empathie mit Mitmusiker*innen und dem Publikum. Die Frage wird aufgeworfen, ob Kulturschaffende einer Gesellschaft eine emotionale Stimme geben.