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The quest for scientifically advanced and sustainable solutions is driven by growing environmental and economic issues associated with coal mining, processing, and utilization. Consequently, within the coal industry, there is a growing recognition of the potential of microbial applications in fostering innovative technologies. Microbial-based coal solubilization, coal beneficiation, and coal dust suppression are green alternatives to traditional thermochemical and leaching technologies and better meet the need for ecologically sound and economically viable choices. Surfactant-mediated approaches have emerged as powerful tools for modeling, simulation, and optimization of coal-microbial systems and continue to gain prominence in clean coal fuel production, particularly in microbiological co-processing, conversion, and beneficiation. Surfactants (surface-active agents) are amphiphilic compounds that can reduce surface tension and enhance the solubility of hydrophobic molecules. A wide range of surfactant properties can be achieved by either directly influencing microbial growth factors, stimulants, and substrates or indirectly serving as frothers, collectors, and modifiers in the processing and utilization of coal. This review highlights the significant biotechnological potential of surfactants by providing a thorough overview of their involvement in coal biodegradation, bioprocessing, and biobeneficiation, acknowledging their importance as crucial steps in coal consumption.
Several unconnected laboratory experiments are usually offered for students in instrumental analysis lab. To give the students a more rational overview of the most common instrumental techniques, a new laboratory experiment was developed. Marketed pain relief drugs, familiar consumer products with one to three active components, namely, acetaminophen (paracetamol), acetylsalicylic acid (ASA), and caffeine, were selected. Common analytical methods were compared regarding the performance of qualitative and quantitative analysis of unknown tablets: UV–visible (UV–vis), infrared (IR), and nuclear magnetic resonance (NMR) spectroscopies, as well as high-performance liquid chromatography (HPLC). The students successfully uncovered the composition of formulations, which were divided into three difficulty categories. Students were shown that in addition to simple mixtures handled in theoretical classes, the composition of complex drug products can also be uncovered. By comparing the performance of different techniques, students deepen their understanding and compare the efficiency of analytical methods in the context of complex mixtures. The laboratory experiment can be adjusted for graduate level by including extra tasks such as method optimization, validation, and 2D spectroscopic techniques.
Effective government services rely on accurate population numbers to allocate resources. In Colombia and globally, census enumeration is challenging in remote regions and where armed conflict is occurring. During census preparations, the Colombian National Administrative Department of Statistics conducted social cartography workshops, where community representatives estimated numbers of dwellings and people throughout their regions. We repurposed this information, combining it with remotely sensed buildings data and other geospatial data. To estimate building counts and population sizes, we developed hierarchical Bayesian models, trained using nearby full-coverage census enumerations and assessed using 10-fold cross-validation. We compared models to assess the relative contributions of community knowledge, remotely sensed buildings, and their combination to model fit. The Community model was unbiased but imprecise; the Satellite model was more precise but biased; and the Combination model was best for overall accuracy. Results reaffirmed the power of remotely sensed buildings data for population estimation and highlighted the value of incorporating local knowledge.
Perennial ryegrass (Lolium perenne) is an underutilized lignocellulosic biomass that has several benefits such as high availability, renewability, and biomass yield. The grass press-juice obtained from the mechanical pretreatment can be used for the bio-based production of chemicals. Lactic acid is a platform chemical that has attracted consideration due to its broad area of applications. For this reason, the more sustainable production of lactic acid is expected to increase. In this work, lactic acid was produced using complex medium at the bench- and reactor scale, and the results were compared to those obtained using an optimized press-juice medium. Bench-scale fermentations were carried out in a pH-control system and lactic acid production reached approximately 21.84 ± 0.95 g/L in complex medium, and 26.61 ± 1.2 g/L in press-juice medium. In the bioreactor, the production yield was 0.91 ± 0.07 g/g, corresponding to a 1.4-fold increase with respect to the complex medium with fructose. As a comparison to the traditional ensiling process, the ensiling of whole grass fractions of different varieties harvested in summer and autumn was performed. Ensiling showed variations in lactic acid yields, with a yield up to 15.2% dry mass for the late-harvested samples, surpassing typical silage yields of 6–10% dry mass.
Purpose: Impaired paravascular drainage of β-Amyloid (Aβ) has been proposed as a contributing cause for sporadic Alzheimer’s disease (AD), as decreased cerebral blood vessel pulsatility and subsequently reduced propulsion in this pathway could lead to the accumulation and deposition of Aβ in the brain. Therefore, we hypothesized that there is an increased impairment in pulsatility across AD spectrum.
Patients and Methods: Using transcranial color-coded duplex sonography (TCCS) the resistance and pulsatility index (RI; PI) of the middle cerebral artery (MCA) in healthy controls (HC, n=14) and patients with AD dementia (ADD, n=12) were measured. In a second step, we extended the sample by adding patients with mild cognitive impairment (MCI) stratified by the presence (MCI-AD, n=8) or absence of biomarkers (MCI-nonAD, n=8) indicative for underlying AD pathology, and compared RI and PI across the groups. To control for atherosclerosis as a confounder, we measured the arteriolar-venular-ratio of retinal vessels.
Results: Left and right RI (p=0.020; p=0.027) and left PI (p=0.034) differed between HC and ADD controlled for atherosclerosis with AUCs of 0.776, 0.763, and 0.718, respectively. The RI and PI of MCI-AD tended towards ADD, of MCI-nonAD towards HC, respectively. RIs and PIs were associated with disease severity (p=0.010, p=0.023).
Conclusion: Our results strengthen the hypothesis that impaired pulsatility could cause impaired amyloid clearance from the brain and thereby might contribute to the development of AD. However, further studies considering other factors possibly influencing amyloid clearance as well as larger sample sizes are needed.
Purpose: A precise determination of the corneal diameter is essential for the diagnosis of various ocular diseases, cataract and refractive surgery as well as for the selection and fitting of contact lenses. The aim of this study was to investigate the agreement between two automatic and one manual method for corneal diameter determination and to evaluate possible diurnal variations in corneal diameter.
Patients and Methods: Horizontal white-to-white corneal diameter of 20 volunteers was measured at three different fixed times of a day with three methods: Scheimpflug method (Pentacam HR, Oculus), placido based topography (Keratograph 5M, Oculus) and manual method using an image analysis software at a slitlamp (BQ900, Haag-Streit).
Results: The two-factorial analysis of variance could not show a significant effect of the different instruments (p = 0.117), the different time points (p = 0.506) and the interaction between instrument and time point (p = 0.182). Very good repeatability (intraclass correlation coefficient ICC, quartile coefficient of dispersion QCD) was found for all three devices. However, manual slitlamp measurements showed a higher QCD than the automatic measurements with the Keratograph 5M and the Pentacam HR at all measurement times.
Conclusion: The manual and automated methods used in the study to determine corneal diameter showed good agreement and repeatability. No significant diurnal variations of corneal diameter were observed during the period of time studied.
Transgenic plants have the potential to produce recombinant proteins on an agricultural scale, with yields of several tons per year. The cost-effectiveness of transgenic plants increases if simple cultivation facilities such as greenhouses can be used for production. In such a setting, we expressed a novel affinity ligand based on the fluorescent protein DsRed, which we used as a carrier for the linear epitope ELDKWA from the HIV-neutralizing antibody 2F5. The DsRed-2F5-epitope (DFE) fusion protein was produced in 12 consecutive batches of transgenic tobacco (Nicotiana tabacum) plants over the course of 2 years and was purified using a combination of blanching and immobilized metal-ion affinity chromatography (IMAC). The average purity after IMAC was 57 ± 26% (n = 24) in terms of total soluble protein, but the average yield of pure DFE (12 mg kg−1) showed substantial variation (± 97 mg kg−1, n = 24) which correlated with seasonal changes. Specifically, we found that temperature peaks (>28°C) and intense illuminance (>45 klx h−1) were associated with lower DFE yields after purification, reflecting the loss of the epitope-containing C-terminus in up to 90% of the product. Whereas the weather factors were of limited use to predict product yields of individual harvests conducted for each batch (spaced by 1 week), the average batch yields were well approximated by simple linear regression models using two independent variables for prediction (illuminance and plant age). Interestingly, accumulation levels determined by fluorescence analysis were not affected by weather conditions but positively correlated with plant age, suggesting that the product was still expressed at high levels, but the extreme conditions affected its stability, albeit still preserving the fluorophore function. The efficient production of intact recombinant proteins in plants may therefore require adequate climate control and shading in greenhouses or even cultivation in fully controlled indoor farms.
Chromatography is the workhorse of biopharmaceutical downstream processing because it can selectively enrich a target product while removing impurities from complex feed streams. This is achieved by exploiting differences in molecular properties, such as size, charge and hydrophobicity (alone or in different combinations). Accordingly, many parameters must be tested during process development in order to maximize product purity and recovery, including resin and ligand types, conductivity, pH, gradient profiles, and the sequence of separation operations. The number of possible experimental conditions quickly becomes unmanageable. Although the range of suitable conditions can be narrowed based on experience, the time and cost of the work remain high even when using high-throughput laboratory automation. In contrast, chromatography modeling using inexpensive, parallelized computer hardware can provide expert knowledge, predicting conditions that achieve high purity and efficient recovery. The prediction of suitable conditions in silico reduces the number of empirical tests required and provides in-depth process understanding, which is recommended by regulatory authorities. In this article, we discuss the benefits and specific challenges of chromatography modeling. We describe the experimental characterization of chromatography devices and settings prior to modeling, such as the determination of column porosity. We also consider the challenges that must be overcome when models are set up and calibrated, including the cross-validation and verification of data-driven and hybrid (combined data-driven and mechanistic) models. This review will therefore support researchers intending to establish a chromatography modeling workflow in their laboratory.
Proteins are important ingredients in food and feed, they are the active components of many pharmaceutical products, and they are necessary, in the form of enzymes, for the success of many technical processes. However, production can be challenging, especially when using heterologous host cells such as bacteria to express and assemble recombinant mammalian proteins. The manufacturability of proteins can be hindered by low solubility, a tendency to aggregate, or inefficient purification. Tools such as in silico protein engineering and models that predict separation criteria can overcome these issues but usually require the complex shape and surface properties of proteins to be represented by a small number of quantitative numeric values known as descriptors, as similarly used to capture the features of small molecules. Here, we review the current status of protein descriptors, especially for application in quantitative structure activity relationship (QSAR) models. First, we describe the complexity of proteins and the properties that descriptors must accommodate. Then we introduce descriptors of shape and surface properties that quantify the global and local features of proteins. Finally, we highlight the current limitations of protein descriptors and propose strategies for the derivation of novel protein descriptors that are more informative.
Self metathesis of oleochemicals offers a variety of bifunctional compounds, that can be used as monomer for polymer production. Many precursors are in huge scales available, like oleic acid ester (biodiesel), oleyl alcohol (tensides), oleyl amines (tensides, lubricants). We show several ways to produce and separate and purify C18-α,ω-bifunctional compounds, using Grubbs 2nd Generation catalysts, starting from technical grade educts.
Die Bereitstellung von nachhaltig erzeugtem Wasserstoff als Energieträger und Rohstoff ist eine wichtige Schlüsseltechnologie sowohl als Ersatz für fossile Energieträger, aber auch als Produkt im Zusammenhang mit Kreislaufprozessen. In der Abwasserbehandlung bestehen verschiedene Möglichkeiten Wasserstoff herzustellen. Mehrere Wege, mögliche Synergien, aber auch deren Nachteile werden vorgestellt.
Mit der Digitalen Automatischen Kupplung beginnt ein neues Kapitel des Schienengüterverkehrs, in dem zusammengestellte Wagen sich automatisch in wenigen Minuten abfahrbereit machen, ohne dass der Mensch eingreifen muss. Eines des größten Hemmnisse der umweltfreundlichen Schiene wird dann entfallen. Notwendig ist jetzt eine Diskussion über den Umfang und die Systemgrenzen der Automatischen Bremsprobe.
Lokomotiven sind dank modernster Konzepte der Antriebstechnik heute energiesparend und umweltfreundlich. Eine Ausrüstung mit Telematik und Assistenzfunktionen ist Standard. Auf der Strecke zeigt sich moderne Technik in Form elektronischer Stellwerke und Zugsicherungssysteme und in Rangier- und Abstellanlagen als EOW-Technik. Am Güterwagen hingegen ist der technische Fortschritt komplett vorbeigegangen. Auch beim modernsten Wagen (Abb. 1) ist die einzige „Automatik“-Funktion die zentral über die Hauptluftleitung (HL) versorgte und betätigte Luftbremse.
Background: Architectural representation, nurtured by the interaction between design thinking and design action, is inherently multi-layered. However, the representation object cannot always reflect these layers. Therefore, it is claimed that these reflections and layerings can gain visibility through ‘performativity in personal knowledge’, which basically has a performative character. The specific layers of representation produced during the performativity in personal knowledge permit insights about the ‘personal way of designing’ [1]. Therefore, the question, ‘how can these layered drawings be decomposed to understand the personal way of designing’, can be defined as the beginning of the study. On the other hand, performativity in personal knowledge in architectural design is handled through the relationship between explicit and tacit knowledge and representational and non-representational theory. To discuss the practical dimension of these theoretical relations, Zvi Hecker's drawing of the Heinz-Galinski-School is examined as an example. The study aims to understand the relationships between the layers by decomposing a layered drawing analytically in order to exemplify personal ways of designing.
Methods: The study is based on qualitative research methodologies. First, a model has been formed through theoretical readings to discuss the performativity in personal knowledge. This model is used to understand the layered representations and to research the personal way of designing. Thus, one drawing of Hecker’s Heinz-Galinski-School project is chosen. Second, its layers are decomposed to detect and analyze diverse objects, which hint to different types of design tools and their application. Third, Zvi Hecker’s statements of the design process are explained through the interview data [2] and other sources. The obtained data are compared with each other.
Results: By decomposing the drawing, eleven layers are defined. These layers are used to understand the relation between the design idea and its representation. They can also be thought of as a reading system. In other words, a method to discuss Hecker’s performativity in personal knowledge is developed. Furthermore, the layers and their interconnections are described in relation to Zvi Hecker’s personal way of designing.
Conclusions: It can be said that layered representations, which are associated with the multilayered structure of performativity in personal knowledge, form the personal way of designing.
Against the background of growing data in everyday life, data processing tools become more powerful to deal with the increasing complexity in building design. The architectural planning process is offered a variety of new instruments to design, plan and communicate planning decisions. Ideally the access to information serves to secure and document the quality of the building and in the worst case, the increased data absorbs time by collection and processing without any benefit for the building and its user. Process models can illustrate the impact of information on the design- and planning process so that architect and planner can steer the process. This paper provides historic and contemporary models to visualize the architectural planning process and introduces means to describe today’s situation consisting of stakeholders, events and instruments. It explains conceptions during Renaissance in contrast to models used in the second half of the 20th century. Contemporary models are discussed regarding their value against the background of increasing computation in the building process.
We conducted a scoping review for active learning in the domain of natural language processing (NLP), which we summarize in accordance with the PRISMA-ScR guidelines as follows:
Objective: Identify active learning strategies that were proposed for entity recognition and their evaluation environments (datasets, metrics, hardware, execution time).
Design: We used Scopus and ACM as our search engines. We compared the results with two literature surveys to assess the search quality. We included peer-reviewed English publications introducing or comparing active learning strategies for entity recognition.
Results: We analyzed 62 relevant papers and identified 106 active learning strategies. We grouped them into three categories: exploitation-based (60x), exploration-based (14x), and hybrid strategies (32x). We found that all studies used the F1-score as an evaluation metric. Information about hardware (6x) and execution time (13x) was only occasionally included. The 62 papers used 57 different datasets to evaluate their respective strategies. Most datasets contained newspaper articles or biomedical/medical data. Our analysis revealed that 26 out of 57 datasets are publicly accessible.
Conclusion: Numerous active learning strategies have been identified, along with significant open questions that still need to be addressed. Researchers and practitioners face difficulties when making data-driven decisions about which active learning strategy to adopt. Conducting comprehensive empirical comparisons using the evaluation environment proposed in this study could help establish best practices in the domain.
Subglacial environments on Earth offer important analogs to Ocean World targets in our solar system. These unique microbial ecosystems remain understudied due to the challenges of access through thick glacial ice (tens to hundreds of meters). Additionally, sub-ice collections must be conducted in a clean manner to ensure sample integrity for downstream microbiological and geochemical analyses. We describe the field-based cleaning of a melt probe that was used to collect brine samples from within a glacier conduit at Blood Falls, Antarctica, for geomicrobiological studies. We used a thermoelectric melting probe called the IceMole that was designed to be minimally invasive in that the logistical requirements in support of drilling operations were small and the probe could be cleaned, even in a remote field setting, so as to minimize potential contamination. In our study, the exterior bioburden on the IceMole was reduced to levels measured in most clean rooms, and below that of the ice surrounding our sampling target. Potential microbial contaminants were identified during the cleaning process; however, very few were detected in the final englacial sample collected with the IceMole and were present in extremely low abundances (∼0.063% of 16S rRNA gene amplicon sequences). This cleaning protocol can help minimize contamination when working in remote field locations, support microbiological sampling of terrestrial subglacial environments using melting probes, and help inform planetary protection challenges for Ocean World analog mission concepts.
Methane is a valuable energy source helping to mitigate the growing energy demand worldwide. However, as a potent greenhouse gas, it has also gained additional attention due to its environmental impacts. The biological production of methane is performed primarily hydrogenotrophically from H2 and CO2 by methanogenic archaea. Hydrogenotrophic methanogenesis also represents a great interest with respect to carbon re-cycling and H2 storage. The most significant carbon source, extremely rich in complex organic matter for microbial degradation and biogenic methane production, is coal. Although interest in enhanced microbial coalbed methane production is continuously increasing globally, limited knowledge exists regarding the exact origins of the coalbed methane and the associated microbial communities, including hydrogenotrophic methanogens. Here, we give an overview of hydrogenotrophic methanogens in coal beds and related environments in terms of their energy production mechanisms, unique metabolic pathways, and associated ecological functions.
Ga-doped Li7La3Zr2O12 garnet solid electrolytes exhibit the highest Li-ion conductivities among the oxide-type garnet-structured solid electrolytes, but instabilities toward Li metal hamper their practical application. The instabilities have been assigned to direct chemical reactions between LiGaO2 coexisting phases and Li metal by several groups previously. Yet, the understanding of the role of LiGaO2 in the electrochemical cell and its electrochemical properties is still lacking. Here, we are investigating the electrochemical properties of LiGaO2 through electrochemical tests in galvanostatic cells versus Li metal and complementary ex situ studies via confocal Raman microscopy, quantitative phase analysis based on powder X-ray diffraction, energy-dispersive X-ray spectroscopy, X-ray photoelectron spectroscopy, and electron energy loss spectroscopy. The results demonstrate considerable and surprising electrochemical activity, with high reversibility. A three-stage reaction mechanism is derived, including reversible electrochemical reactions that lead to the formation of highly electronically conducting products. The results have considerable implications for the use of Ga-doped Li7La3Zr2O12 electrolytes in all-solid-state Li-metal battery applications and raise the need for advanced materials engineering to realize Ga-doped Li7La3Zr2O12for practical use.
The thermal conductivity of components manufactured using Laser Powder Bed Fusion (LPBF), also called Selective Laser Melting (SLM), plays an important role in their processing. Not only does a reduced thermal conductivity cause residual stresses during the process, but it also makes subsequent processes such as the welding of LPBF components more difficult. This article uses 316L stainless steel samples to investigate whether and to what extent the thermal conductivity of specimens can be influenced by different LPBF parameters. To this end, samples are set up using different parameters, orientations, and powder conditions and measured by a heat flow meter using stationary analysis. The heat flow meter set-up used in this study achieves good reproducibility and high measurement accuracy, so that comparative measurements between the various LPBF influencing factors to be tested are possible. In summary, the series of measurements show that the residual porosity of the components has the greatest influence on conductivity. The degradation of the powder due to increased recycling also appears to be detectable. The build-up direction shows no detectable effect in the measurement series.
In this work, the effect of low air relative humidity on the operation of a polymer electrolyte membrane fuel cell is investigated. An innovative method through performing in situ electrochemical impedance spectroscopy is utilised to quantify the effect of inlet air relative humidity at the cathode side on internal ionic resistances and output voltage of the fuel cell. In addition, algorithms are developed to analyse the electrochemical characteristics of the fuel cell. For the specific fuel cell stack used in this study, the membrane resistance drops by over 39 % and the cathode side charge transfer resistance decreases by 23 % after increasing the humidity from 30 % to 85 %, while the results of static operation also show an increase of ∼2.2 % in the voltage output after increasing the relative humidity from 30 % to 85 %. In dynamic operation, visible drying effects occur at < 50 % relative humidity, whereby the increase of the air side stoichiometry increases the drying effects. Furthermore, other parameters, such as hydrogen humidification, internal stack structure, and operating parameters like stoichiometry, pressure, and temperature affect the overall water balance. Therefore, the optimal humidification range must be determined by considering all these parameters to maximise the fuel cell performance and durability. The results of this study are used to develop a health management system to ensure sufficient humidification by continuously monitoring the fuel cell polarisation data and electrochemical impedance spectroscopy indicators.
Critical quantitative evaluation of integrated health management methods for fuel cell applications
(2024)
Online fault diagnostics is a crucial consideration for fuel cell systems, particularly in mobile applications, to limit downtime and degradation, and to increase lifetime. Guided by a critical literature review, in this paper an overview of Health management systems classified in a scheme is presented, introducing commonly utilised methods to diagnose FCs in various applications. In this novel scheme, various Health management system methods are summarised and structured to provide an overview of existing systems including their associated tools. These systems are classified into four categories mainly focused on model-based and non-model-based systems. The individual methods are critically discussed when used individually or combined aimed at further understanding their functionality and suitability in different applications. Additionally, a tool is introduced to evaluate methods from each category based on the scheme presented. This tool applies the technique of matrix evaluation utilising several key parameters to identify the most appropriate methods for a given application. Based on this evaluation, the most suitable methods for each specific application are combined to build an integrated Health management system.
Meitner-Auger-electron emitters have a promising potential for targeted radionuclide therapy of cancer because of their short range and the high linear energy transfer of Meitner-Auger-electrons (MAE). One promising MAE candidate is 197m/gHg with its half-life of 23.8 h and 64.1 h, respectively, and high MAE yield. Gold nanoparticles (AuNPs) that are labelled with 197m/gHg could be a helpful tool for radiation treatment of glioblastoma multiforme when infused into the surgical cavity after resection to prevent recurrence. To produce such AuNPs, 197m/gHg was embedded into pristine AuNPs. Two different syntheses were tested starting from irradiated gold containing trace amounts of 197m/gHg. When sodium citrate was used as reducing agent, no 197m/gHg labelled AuNPs were formed, but with tannic acid, 197m/gHg labeled AuNPs were produced. The method was optimized by neutralizing the pH (pH = 7) of the Au/197m/gHg solution, which led to labelled AuNPs with a size of 12.3 ± 2.0 nm as measured by transmission electron microscopy. The labelled AuNPs had a concentration of 50 μg (gold)/mL with an activity of 151 ± 93 kBq/mL (197gHg, time corrected to the end of bombardment).
We present the production of 58mCo on a small, 13 MeV medical cyclotron utilizing a siphon style liquid target system. Different concentrated iron(III)-nitrate solutions of natural isotopic distribution were irradiated at varying initial pressures and subsequently separated by solid phase extraction chromatography. The radio cobalt (58m/gCo and 56Co) was successfully produced with saturation activities of (0.35 ± 0.03) MBq μA−1 for 58mCo with a separation recovery of (75 ± 2) % of cobalt after one separation step utilizing LN-resin.
Density reduction effects on the production of [11C]CO2 in Nb-body targets on a medical cyclotron
(2023)
Medical isotope production of 11C is commonly performed in gaseous targets. The power deposition of the proton beam during the irradiation decreases the target density due to thermodynamic mixing and can cause an increase of penetration depth and divergence of the proton beam. In order to investigate the difference how the target-body length influences the operation conditions and the production yield, a 12 cm and a 22 cm Nb-target body containing N2/O2 gas were irradiated using a 13 MeV proton cyclotron. It was found that the density reduction has a large influence on the pressure rise during irradiation and the achievable radioactive yield. The saturation activity of [11C]CO2 for the long target (0.083 Ci/μA) is about 10% higher than in the short target geometry (0.075 Ci/μA).
Elastic transmission eigenvalues and their computation via the method of fundamental solutions
(2020)
A stabilized version of the fundamental solution method to catch ill-conditioning effects is investigated with focus on the computation of complex-valued elastic interior transmission eigenvalues in two dimensions for homogeneous and isotropic media. Its algorithm can be implemented very shortly and adopts to many similar partial differential equation-based eigenproblems as long as the underlying fundamental solution function can be easily generated. We develop a corroborative approximation analysis which also implicates new basic results for transmission eigenfunctions and present some numerical examples which together prove successful feasibility of our eigenvalue recovery approach.
In der wasserbaulichen Forschung werden neben klassischen Messinstrumenten zunehmend kamerabasierte Verfahren genutzt. Diese erlauben neben der Bestimmung von Fließgeschwindigkeiten auch die Detektion der freien Wasseroberfläche oder zeitliche Vermessung von Kolken. Durch die hohen räumlichen und zeitlichen Auflösungen, welche neueste Kamerasensoren liefern, können neue Erkenntnisse in turbulenten, komplexen Strömungen gewonnen werden. Auch in der Praxis können diese Verfahren mit geringem Aufwand wichtige Daten liefern.
The low-pressure system Bernd involved extreme rainfalls in the Western part of Germany in July 2021,
resulting in major floods, severe damages and a tremendous number of casualties. Such extreme events
are rare and full flood protection can never be ensured with reasonable financial means. But still, this
event must be starting point to reconsider current design concepts. This article aims at sharing some
thoughts on potential hazards, the selection of return periods and remaining risk with the focus on Germany.
Direct sampling method via Landweber iteration for an absorbing scatterer with a conductive boundary
(2024)
In this paper, we consider the inverse shape problem of recovering isotropic scatterers with a conductive boundary condition. Here, we assume that the measured far-field data is known at a fixed wave number. Motivated by recent work, we study a new direct sampling indicator based on the Landweber iteration and the factorization method. Therefore, we prove the connection between these reconstruction methods. The method studied here falls under the category of qualitative reconstruction methods where an imaging function is used to recover the absorbing scatterer. We prove stability of our new imaging function as well as derive a discrepancy principle for recovering the regularization parameter. The theoretical results are verified with numerical examples to show how the reconstruction performs by the new Landweber direct sampling method.
We consider the numerical approximation of second-order semi-linear parabolic stochastic partial differential equations interpreted in the mild sense which we solve on general two-dimensional domains with a C² boundary with homogeneous Dirichlet boundary conditions. The equations are driven by Gaussian additive noise, and several Lipschitz-like conditions are imposed on the nonlinear function. We discretize in space with a spectral Galerkin method and in time using an explicit Euler-like scheme. For irregular shapes, the necessary Dirichlet eigenvalues and eigenfunctions are obtained from a boundary integral equation method. This yields a nonlinear eigenvalue problem, which is discretized using a boundary element collocation method and is solved with the Beyn contour integral algorithm. We present an error analysis as well as numerical results on an exemplary asymmetric shape, and point out limitations of the approach.
Analysis and computation of the transmission eigenvalues with a conductive boundary condition
(2022)
We provide a new analytical and computational study of the transmission eigenvalues with a conductive boundary condition. These eigenvalues are derived from the scalar inverse scattering problem for an inhomogeneous material with a conductive boundary condition. The goal is to study how these eigenvalues depend on the material parameters in order to estimate the refractive index. The analytical questions we study are: deriving Faber–Krahn type lower bounds, the discreteness and limiting behavior of the transmission eigenvalues as the conductivity tends to infinity for a sign changing contrast. We also provide a numerical study of a new boundary integral equation for computing the eigenvalues. Lastly, using the limiting behavior we will numerically estimate the refractive index from the eigenvalues provided the conductivity is sufficiently large but unknown.
An alternative method is presented to numerically compute interior elastic transmission eigenvalues for various domains in two dimensions. This is achieved by discretizing the resulting system of boundary integral equations in combination with a nonlinear eigenvalue solver. Numerical results are given to show that this new approach can provide better results than the finite element method when dealing with general domains.
The hot spots conjecture is only known to be true for special geometries. This paper shows numerically that the hot spots conjecture can fail to be true for easy to construct bounded domains with one hole. The underlying eigenvalue problem for the Laplace equation with Neumann boundary condition is solved with boundary integral equations yielding a non-linear eigenvalue problem. Its discretization via the boundary element collocation method in combination with the algorithm by Beyn yields highly accurate results both for the first non-zero eigenvalue and its corresponding eigenfunction which is due to superconvergence. Additionally, it can be shown numerically that the ratio between the maximal/minimal value inside the domain and its maximal/minimal value on the boundary can be larger than 1 + 10− 3. Finally, numerical examples for easy to construct domains with up to five holes are provided which fail the hot spots conjecture as well.
There is a very large number of very important situations which can be modeled with nonlinear parabolic partial differential equations (PDEs) in several dimensions. In general, these PDEs can be solved by discretizing in the spatial variables and transforming them into huge systems of ordinary differential equations (ODEs), which are very stiff. Therefore, standard explicit methods require a large number of iterations to solve stiff problems. But implicit schemes are computationally very expensive when solving huge systems of nonlinear ODEs. Several families of Extrapolated Stabilized Explicit Runge-Kutta schemes (ESERK) with different order of accuracy (3 to 6) are derived and analyzed in this work. They are explicit methods, with stability regions extended, along the negative real semi-axis, quadratically with respect to the number of stages s, hence they can be considered to solve stiff problems much faster than traditional explicit schemes. Additionally, they allow the adaptation of the step length easily with a very small cost.
Two new families of ESERK schemes (ESERK3 and ESERK6) are derived, and analyzed, in this work. Each family has more than 50 new schemes, with up to 84.000 stages in the case of ESERK6. For the first time, we also parallelized all these new variable step length and variable number of stages algorithms (ESERK3, ESERK4, ESERK5, and ESERK6). These parallelized strategies allow to decrease times significantly, as it is discussed and also shown numerically in two problems. Thus, the new codes provide very good results compared to other well-known ODE solvers. Finally, a new strategy is proposed to increase the efficiency of these schemes, and it is discussed the idea of combining ESERK families in one code, because typically, stiff problems have different zones and according to them and the requested tolerance the optimum order of convergence is different.
A second-order L-stable exponential time-differencing (ETD) method is developed by combining an ETD scheme with approximating the matrix exponentials by rational functions having real distinct poles (RDP), together with a dimensional splitting integrating factor technique. A variety of non-linear reaction-diffusion equations in two and three dimensions with either Dirichlet, Neumann, or periodic boundary conditions are solved with this scheme and shown to outperform a variety of other second-order implicit-explicit schemes. An additional performance boost is gained through further use of basic parallelization techniques.
In this article, a concept of implicit methods for scalar conservation laws in one or more spatial dimensions allowing also for source terms of various types is presented. This material is a significant extension of previous work of the first author (Breuß SIAM J. Numer. Anal. 43(3), 970–986 2005). Implicit notions are developed that are centered around a monotonicity criterion. We demonstrate a connection between a numerical scheme and a discrete entropy inequality, which is based on a classical approach by Crandall and Majda. Additionally, three implicit methods are investigated using the developed notions. Next, we conduct a convergence proof which is not based on a classical compactness argument. Finally, the theoretical results are confirmed by various numerical tests.
The inverse scattering problem for a conductive boundary condition and transmission eigenvalues
(2018)
In this paper, we consider the inverse scattering problem associated with an inhomogeneous media with a conductive boundary. In particular, we are interested in two problems that arise from this inverse problem: the inverse conductivity problem and the corresponding interior transmission eigenvalue problem. The inverse conductivity problem is to recover the conductive boundary parameter from the measured scattering data. We prove that the measured scatted data uniquely determine the conductivity parameter as well as describe a direct algorithm to recover the conductivity. The interior transmission eigenvalue problem is an eigenvalue problem associated with the inverse scattering of such materials. We investigate the convergence of the eigenvalues as the conductivity parameter tends to zero as well as prove existence and discreteness for the case of an absorbing media. Lastly, several numerical and analytical results support the theory and we show that the inside–outside duality method can be used to reconstruct the interior conductive eigenvalues.
The aim of the current study was to investigate the performance of integrated RF
transmit arrays with high channel count consisting of meander microstrip antennas
for body imaging at 7 T and to optimize the position and number of transmit ele-
ments. RF simulations using multiring antenna arrays placed behind the bore liner
were performed for realistic exposure conditions for body imaging. Simulations were
performed for arrays with as few as eight elements and for arrays with high channel
counts of up to 48 elements. The B1+ field was evaluated regarding the degrees of
freedom for RF shimming in the abdomen. Worst-case specific absorption rate
(SARwc ), SAR overestimation in the matrix compression, the number of virtual obser-
vation points (VOPs) and SAR efficiency were evaluated. Constrained RF shimming
was performed in differently oriented regions of interest in the body, and the devia-
tion from a target B1+ field was evaluated. Results show that integrated multiring
arrays are able to generate homogeneous B1+ field distributions for large FOVs, espe-
cially for coronal/sagittal slices, and thus enable body imaging at 7 T with a clinical
workflow; however, a low duty cycle or a high SAR is required to achieve homoge-
neous B1+ distributions and to exploit the full potential. In conclusion, integrated
arrays allow for high element counts that have high degrees of freedom for the pulse
optimization but also produce high SARwc , which reduces the SAR accuracy in the
VOP compression for low-SAR protocols, leading to a potential reduction in array
performance. Smaller SAR overestimations can increase SAR accuracy, but lead to a
high number of VOPs, which increases the computational cost for VOP evaluation
and makes online SAR monitoring or pulse optimization challenging. Arrays with
interleaved rings showed the best results in the study.
Im Verfahren gegen die Österreichische Post AG (Rs. C-300/21) befasste sich der EuGH erstmals mit dem in Art. 82 DS-GVO geregelten datenschutzrechtlichen Schadensersatzanspruch. Mit den Klarstellungen des EuGH verschieben sich die Probleme nun stärker zu den „klassischen“ Fragen des Schadensersatzrechts im Zivilprozess. Relevant sind dabei vor allem Aspekte der Darlegungs- und Beweislast und deren Besonderheiten mit Blick auf den Ersatz immaterieller Schäden. Der Beitrag fokussiert sich auf die Voraussetzungen und den dabei zu führenden Tatsachenbeweis bei der Klage des Betroffenen gegen den Verantwortlichen auf Ersatz immaterieller Schäden.