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A method for the integrated extraction and separation of fatty acids from algae using supercritical CO2 is presented. Desmodesmus obliquus and Chlorella sorokiniana were used as algae. First, a method for chromatographic separation of fatty acids of different degrees of saturation was established and optimized. Then, an integrated method for supercritical extraction was developed for both algal species. It was also verified whether prior cell disruption was beneficial for extraction. In developing the method for chromatographic separation, statistical experimental design was used to determine the optimal parameter settings. The methanol content in the mobile phase proved to be the most important parameter for successful separation of the three unsaturated fatty acids oleic acid, linoleic acid, and linolenic acid. Supercritical extraction with dried algae showed that about four times more fatty acids can be extracted from C. sorokiniana relative to the dry mass used.
Physical layer specification of the L-band Digital Aeronautical Communications System (L-DACS1)
(2009)
This paper presents the latest prototype of the integrated emitter turn-off thyristor concept, which potentially ranks among thyristor high-power devices like the gate turn-off thyristor and the integrated gate-commutated thyristor (IGCT). Due to modifications of the external driver stage and mechanical press-pack design optimization, this prototype allows for full device characterization. The turn-off capability was increased to 1600 A with an active silicon area of 823mm2 . This leads to a transient peak power of 672.1kW/cm² . Within this paper, measurements and concept assessment are presented and a comparison to state-of-the-art IGCT devices is provided.
The continuously growing amount of renewable sources starts compromising the stability of electrical grids. Contradictory to fossil fuel power plants, energy production of wind and photovoltaic (PV) energy is fluctuating. Although predictions have significantly improved, an outage of multi-MW offshore wind farms poses a challenging problem. One solution could be the integration of storage systems in the grid. After a short overview, this paper focuses on two exemplary battery storage systems, including the required power electronics. The grid integration, as well as the optimal usage of volatile energy reserves, is presented for a 5- kW PV system for home application, as well as for a 100- MW medium-voltage system, intended for wind farm usage. The efficiency and cost of topologies are investigated as a key parameter for large-scale integration of renewable power at medium- and low-voltage.
Motivation-based Learning: Teaching Fundamentals of Electrical Engineering with an LED Spinning Top
(2018)
This thesis introduces the Integrated Emitter Turn-Off (IETO) Thyristor as a new high-power device. Known state-of-the-art research activities like the Dual GCT, the ETO thyristor and the ICT were presented and critically reviewed. A comparison with commercialized solutions identifies the pros and cons of each type of device family. Based on this analysis, the IETO structure is proposed, covering most benefits of each device class. In particular the combination of a MOS-assisted turn-off with a thyristor-based device allows a voltage-controlled MOS switching and the low on-state voltage of the thyristors. The following synthesis of an IETO device stands on a three-dimensional field of optimization spanned by electric, mechanical and thermal aspects. From an electric point of view, the lowest possible parasitic inductance and resistance within the commutation path are optimization criteria. The mechanical construction has to withstand the required contact pressure of multiple kilo Newtons. Finally, thermal borders limit the maximum average current of the device. FEM simulations covering these three aspects are performed for several design proposals. An IETO prototype is constructed and measurements on various test benches attest thermal, mechanical and electric performance. A local decoupling of the external driver stage and the presspack housing is presented by a cable connection. This separation enables a thermal and mechanical independence, which is advantageous in terms of vibrations and thermal cycles including increased reliability. The electric pulse performance of the prototype device is a factor of 3.1 above today''s solutions. In single-pulse measurements, a current up to 1600 A was successfully turned off at 115°C with an active silicon area of 823 mm². One reason for this increased turn-off capability is the extremely low-inductive construction. Additional functionality of the IETO thyristor like over-current self-protection and defined short-circuit failure state are successfully verified.
[{ReN(PMe2Ph)3}{ReO3N}]2 – Structural Evidence for the Nitridotrioxorhenate(VII) Anion, [ReO3N]2−
(2005)
A High-Throughput Functional Complementation Assay for Classification of BRCA1 Missense Variants
(2013)
Lightning safety guidelines
(2010)
This paper introduces lightning to the layman, noting the right behaviour in front of thunderstorms as well as protective measures against lightning. It also contributes to the prevention of lightning injuries and damages. This report was prepared by the authors inside the AHG1 Group for IEC TC81 (Lightning Protection).
The growing body of political texts opens up new opportunities for rich insights into political dynamics and ideologies but also increases the workload for manual analysis. Automated speaker attribution, which detects who said what to whom in a speech event and is closely related to semantic role labeling, is an important processing step for computational text analysis. We study the potential of the large language model family Llama 2 to automate speaker attribution in German parliamentary debates from 2017-2021. We fine-tune Llama 2 with QLoRA, an efficient training strategy, and observe our approach to achieve competitive performance in the GermEval 2023 Shared Task On Speaker Attribution in German News Articles and Parliamentary Debates. Our results shed light on the capabilities of large language models in automating speaker attribution, revealing a promising avenue for computational analysis of political discourse and the development of semantic role labeling systems.
Disruption experiments targeted at the Bacillus licheniformis degSU operon and GFP-reporter analysis provided evidence for promoter activity immediately upstream of degU. pMutin mediated concomitant introduction of the degU32 allele – known to cause hypersecretion in Bacillus subtilis – resulted in a marked increase in protease activity. Application of 5-fluorouracil based counterselection through establishment of a phosphoribosyltransferase deficient Δupp strain eventually facilitated the marker-free introduction of degU32 leading to further protease enhancement achieving levels as for hypersecreting wild strains in which degU was overexpressed. Surprisingly, deletion of rapG – known to interfere with DegU DNA-binding in B. subtilis – did not enhance protease production neither in the wild type nor in the degU32 strain. The combination of degU32 and Δupp counterselection in the type strain is not only equally effective as in hypersecreting wild strains with respect to protease production but furthermore facilitates genetic strain improvement aiming at biological containment and effectiveness of biotechnological processes.
Solar sails provide ignificant advantages over other low-thrust propulsion systems because they produce thrust by the momentum exchange from solar radiation pressure (SRP) and thus do not consume any propellant.The force exerted on a very thin sail foil basically depends on the light incidence angle. Several analytical SRP force models that describe the SRP force acting on the sail have been established since the 1970s. All the widely used models use constant optical force coefficients of the reflecting sail material. In 2006,MENGALI et al. proposed a refined SRP force model that takes into account the dependancy of the force coefficients on the light incident angle,the sail’s distance from the sun (and thus the sail emperature) and the surface roughness of the sail material [1]. In this paper, the refined SRP force model is compared to the previous ones in order to identify the potential impact of the new model on the predicted capabilities of solar sails in performing low-cost interplanetary space missions. All force models have been implemented within InTrance, a global low-thrust trajectory optimization software utilizing evolutionary neurocontrol [2]. Two interplanetary rendezvous missions, to Mercury and the near-Earth asteroid 1996FG3, are investigated. Two solar sail performances in terms of characteristic acceleration are examined for both scenarios, 0.2 mm/s2 and 0.5 mm/s2, termed “low” and “medium” sail performance. In case of the refined SRP model, three different values of surface roughness are chosen, h = 0 nm, 10 nm and 25 nm. The results show that the refined SRP force model yields shorter transfer times than the standard model.
We present a new approach to the problem of optimal control of solar sails for low-thrust trajectory optimization. The objective was to find the required control torque magnitudes in order to steer a solar sail in interplanetary space. A new steering strategy, controlling the solar sail with generic torques applied about the spacecraft body axes, is integrated into the existing low-thrust trajectory optimization software InTrance. This software combines artificial neural networks and evolutionary algorithms to find steering strategies close to the global optimum without an initial guess. Furthermore, we implement a three rotational degree-of-freedom rigid-body attitude dynamics model to represent the solar sail in space. Two interplanetary transfers to Mars and Neptune are chosen to represent typical future solar sail mission scenarios. The results found with the new steering strategy are compared to the existing reference trajectories without attitude dynamics. The resulting control torques required to accomplish the missions are investigated, as they pose the primary requirements to a real on-board attitude control system.
Using a cell-based gas biosensor for investigation of adverse effects of acetone vapors in vitro
(2013)
In this contribution, we focus on the detection of toxic gases with living eukaryotic cells. A cell-based gas sensor system, able to measure the effects of direct exposure of gases to cells in real-time, was set up. Impedance data as well as oxygen consumption of Chinese hamster lung fibroblast cells (V79) were analysed upon exposure to carbon monoxide (CO). The CO (diluted in wet synthetic air) affects the cell respiration as indicated by an attenuated respiration signal after the CO exposure as well as an instant increase of the capacitive part of the impedance signal during the gas exposure.
Cell-based sensors for the detection of gases have long been underrepresented, due to the cellular requirement of being cultured in a liquid environment. In this work we established a cell-based gas biosensor for the detection of toxic substances in air, by adapting a commercial sensor chip (Bionas®), previously used for the measurement of pollutants in liquids. Cells of the respiratory tract (A549, RPMI 2650, V79), which survive at a gas phase in a natural context, are used as biological receptors. The physiological cell parameters acidification, respiration and morphology are continuously monitored in parallel. Ammonia was used as a highly water-soluble model gas to test the feasibility of the sensor system. Infrared measurements confirmed the sufficiency of the medium draining method. This sensor system provides a basis for many sensor applications such as environmental monitoring, building technology and public security.
How different diversity factors affect the perception of first-year requirements in higher education
(2021)
In the light of growing university entry rates, higher education institutions not only serve larger numbers of students, but also seek to meet first-year students’ ever more diverse needs. Yet to inform universities how to support the transition to higher education, research only offers limited insights. Current studies tend to either focus on the individual factors that affect student success or they highlight students’ social background and their educational biography in order to examine the achievement of selected, non-traditional groups of students. Both lines of research appear to lack integration and often fail to take organisational diversity into account, such as different types of higher education institutions or degree programmes. For a more comprehensive understanding of student diversity, the present study includes individual, social and organisational factors. To gain insights into their role for the transition to higher education, we examine how the different factors affect the students’ perception of the formal and informal requirements of the first year as more or less difficult to cope with. As the perceived requirements result from both the characteristics of the students and the institutional context, they allow to investigate transition at the interface of the micro and the meso level of higher education. Latent profile analyses revealed that there are no profiles with complex patterns of perception of the first-year requirements, but the identified groups rather differ in the overall level of perceived challenges. Moreover, SEM indicates that the differences in the perception largely depend on the individual factors self-efficacy and volition.
In this study we observed courses of micturition symptoms and differentiated degrees of symptoms for each point in time while also considering the impact of bothersomeness. Our data show that not only significantly more patients who have undergone BT suffer from OAB than those who have undergone RP, but also that those affected show significantly higher values for severity of OAB symptoms throughout the whole observation period of 36 months. Our data analysis further shows that variability of OAB symptoms as well as fluctuation of severity of OAB symptoms vary to a significantly higher degree after BT than after RP. Looking only at mean figures at a given point in time clearly underestimates the underlying problem. This fact is not reflected in the literature.
The transgeneticist's toolbox: novel methods for the targeted modification of eukaryotic genomes
(2000)
Transcription-promoting genomic sites in mammalia: their elucidation and architectural principles
(1998)
Clearance of blood components and fluid drainage play a crucial role in subarachnoid hemorrhage (SAH) and post hemorrhagic hydrocephalus (PHH). With the involvement of interstitial fluid (ISF) and cerebrospinal fluid (CSF), two pathways for the clearance of fluid and solutes in the brain are proposed. Starting at the level of capillaries, flow of ISF follows along the basement membranes in the walls of cerebral arteries out of the parenchyma to drain into the lymphatics and CSF [1]–[3]. Conversely, it is shown that CSF enters the parenchyma between glial and pial basement membranes of penetrating arteries [4]–[6]. Nevertheless, the involved structures and the contribution of either flow pathway to fluid balance between the subarachnoid space and interstitial space remains controversial. Low frequency oscillations in vascular tone are referred to as vasomotion and corresponding vasomotion waves are modeled as the driving force for flow of ISF out of the parenchyma [7]. Retinal vessel analysis (RVA) allows non-invasive measurement of retinal vessel vasomotion with respect to diameter changes [8]. Thus, the aim of the study is to investigate vasomotion in RVA signals of SAH and PHH patients.
The MYOTONES experiment is the first to monitor changes in the basic biomechanical properties (tone, elasticity and stiffness) of the resting human myofascial system due to microgravity with a oninvasive, portable device on board the ISS. The MyotonPRO device applies several brief mechanical stimuli to the surface of the skin, and the natural oscillation signals of the tissue beneath are detected and computed by the MyotonPRO. Thus, an objective, quick and easy determination of the state of the underlying tissue is possible.
Two preflight, four inflight and four post flight measurements were performed on a male astronaut using the same 10 measurement points (MP) for each session. MPs were located on the plantar fascia, Achilles tendon, M. soleus, M. gastrocnemius, M. multifidus, M. splenius capitis, M. deltoideus anterior, M. rectus femoris, infrapatellar tendon, M. tibialis anterior. Subcutaneous tissues thickness above the MPs was measured using ultrasound imaging. Magnetic resonance images (MRI) of lower limb muscles and functional tests were also performed pre- and postflight.
Our first measurements on board the ISS confirmed increased tone and stiffness of the lumbar multifidus muscle, an important trunk stabilizer, dysfunction of which is known to be associated with back pain. Furthermore, reduced tone and stiffness of Achilles tendon and plantar fascia were observed inflight vs. preflight, confirming previous findings from terrestrial analog studies and parabolic
flights. Unexpectedly, the deltoid showed negative inflight changes in tone and stiffness, and increased elasticity, suggesting a potential risk of muscle atrophy in longer spaceflight that should be addressed by adequate inflight countermeasure protocols. Most values from limb and back MPS showed deflected patterns (in either directions) from inflight shortly after the re-entry phase on the landing day and one week later. Most parameter values then normalized to baseline after 3 weeks likely due to 1G re-adaptation and possible outcome of the reconditioning protocol. No major changes in subcutaneous tissues thickness above the MPs were found inflight vs preflight, suggesting no bias (i.e., fluid shift, extreme tissue thickening or loss). Pre- and postflight MRI and functional tests showed negligible changes in calf muscle size, power and force, which is likely due to training effects from current inflight exercise protocols.
The MYOTONES experiment is currently ongoing to collect data from further crew members. The potential impact of this research is to better understand the effects of microgravity and countermeasures over the time course of an ISS mission cycle. This will enable exercise countermeasures to be tailored
The entangled Universe
(2004)
Nonlocal Cosmology
(1996)
The Newtonian regime of a recent nonlocal extension of general relativity is investigated. Nonlocality is introduced via a scalar “constitutive” kernel in a special case of the translational gauge theory of gravitation, namely, the teleparallel equivalent of general relativity. In this theory, the nonlocal aspect of gravity simulates dark matter. A nonlocal and nonlinear generalization of Poisson’s equation of Newtonian gravitation is presented. The implications of nonlocality for the gravitational physics in the solar system are briefly studied.
Direct air capture (DAC) combined with subsequent storage (DACCS) is discussed as one promising carbon dioxide removal option. The aim of this paper is to analyse and comparatively classify the resource consumption (land use, renewable energy and water) and costs of possible DAC implementation pathways for Germany. The paths are based on a selected, existing climate neutrality scenario that requires the removal of 20 Mt of carbon dioxide (CO2) per year by DACCS from 2045. The analysis focuses on the so-called “low-temperature” DAC process, which might be more advantageous for Germany than the “high-temperature” one. In four case studies, we examine potential sites in northern, central and southern Germany, thereby using the most suitable renewable energies for electricity and heat generation. We show that the deployment of DAC results in large-scale land use and high energy needs. The land use in the range of 167–353 km2 results mainly from the area required for renewable energy generation. The total electrical energy demand of 14.4 TWh per year, of which 46% is needed to operate heat pumps to supply the heat demand of the DAC process, corresponds to around 1.4% of Germany's envisaged electricity demand in 2045. 20 Mt of water are provided yearly, corresponding to 40% of the city of Cologne‘s water demand (1.1 million inhabitants). The capture of CO2 (DAC) incurs levelised costs of 125–138 EUR per tonne of CO2, whereby the provision of the required energy via photovoltaics in southern Germany represents the lowest value of the four case studies. This does not include the costs associated with balancing its volatility. Taking into account transporting the CO2 via pipeline to the port of Wilhelmshaven, followed by transporting and sequestering the CO2 in geological storage sites in the Norwegian North Sea (DACCS), the levelised costs increase to 161–176 EUR/tCO2. Due to the longer transport distances from southern and central Germany, a northern German site using wind turbines would be the most favourable.
Using optimization to design a renewable energy system has become a computationally demanding task as the high temporal fluctuations of demand and supply arise within the considered time series. The aggregation of typical operation periods has become a popular method to reduce effort. These operation periods are modelled independently and cannot interact in most cases. Consequently, seasonal storage is not reproducible. This inability can lead to a significant error, especially for energy systems with a high share of fluctuating renewable energy. The previous paper, “Time series aggregation for energy system design: Modeling seasonal storage”, has developed a seasonal storage model to address this issue. Simultaneously, the paper “Optimal design of multi-energy systems with seasonal storage” has developed a different approach. This paper aims to review these models and extend the first model. The extension is a mathematical reformulation to decrease the number of variables and constraints. Furthermore, it aims to reduce the calculation time while achieving the same results.
Reliable methods for automatic readability assessment have the potential to impact a variety of fields, ranging from machine translation to self-informed learning. Recently, large language models for the German language (such as GBERT and GPT-2-Wechsel) have become available, allowing to develop Deep Learning based approaches that promise to further improve automatic readability assessment. In this contribution, we studied the ability of ensembles of fine-tuned GBERT and GPT-2-Wechsel models to reliably predict the readability of German sentences. We combined these models with linguistic features and investigated the dependence of prediction performance on ensemble size and composition. Mixed ensembles of GBERT and GPT-2-Wechsel performed better than ensembles of the same size consisting of only GBERT or GPT-2-Wechsel models. Our models were evaluated in the GermEval 2022 Shared Task on Text Complexity Assessment on data of German sentences. On out-of-sample data, our best ensemble achieved a root mean squared error of 0:435.