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Within this work, we report the results of nuclear inelastic scattering experiments of the low-spin phase of the iron(II) mononuclear SCO complex Fe[HBpz3]2 and density functional theory based calculations performed on a model molecule of the complex. We show that the calculated partial density of vibrational states based on the structure of a single iron(II) center which is linked by three pyrazole rings to borat is in good accordance with the experimentally obtained 57Fe-pDOS and assign the molecular vibrations to the prominent optical phonons.
We present new results on standard basis computations of a 0-dimensional ideal I in a power series ring or in the localization of a polynomial ring over a computable field K. We prove the semicontinuity of the “highest corner” in a family of ideals, parametrized by the spectrum of a Noetherian domain A. This semicontinuity is used to design a new modular algorithm for computing a standard basis of I if K is the quotient field of A. It uses the computation over the residue field of a “good” prime ideal of A to truncate high order terms in the subsequent computation over K. We prove that almost all prime ideals are good, so a random choice is very likely to be good, and whether it is good is detected a posteriori by the algorithm. The algorithm yields a significant speed advantage over the non-modular version and works for arbitrary Noetherian domains. The most important special cases are perhaps A = ℤ and A = k[t], k any field and t a set of parameters. Besides its generality, the method differs substantially from previously known modular algorithms for A = ℤ, since it does not manipulate the coefficients. It is also usually faster and can be combined with other modular methods for computations in local rings. The algorithm is implemented in the computer algebra system SINGULAR and we present several examples illustrating its power.
Nanostructured tantalum (Ta)-based dental implants have recently attracted significant attention thanks to their superior biocompatibility and bioactivity as compared to their titanium-based counterparts. While the biological and chemical aspects of Ta implants have been widely studied, their mechanical features have been investigated more rarely. Additionally, the mechanical behavior of these implants and, more importantly, their plastic deformation mechanisms are still not fully understood. Accordingly, in the current research, molecular dynamics simulation as a powerful tool for probing the atomic-scale phenomena is utilized to explore the microstructural evolution of pure polycrystalline Ta samples under tensile loading conditions. Various samples with an average grain size of 2–10 nm are systematically examined using various crystal structure analysis tools to determine the underlying deformation mechanisms. The results reveal that for the samples with an average grain size larger than 8 nm, twinning and dislocation slip are the main sources of any plasticity induced within the sample. For finer-grained samples, the activity of grain boundaries—including grain elongation, rotation, migration, and sliding—are the most important mechanisms governing the plastic deformation. Finally, the temperature-dependent Hall–Petch breakdown is thoroughly examined for the nanocrystalline samples via identification of the grain boundary dynamics.
In many applications, visual analytics (VA) has developed into a standard tool to ease data access and knowledge generation. VA describes a holistic cycle transforming data into hypothesis and visualization to generate insights that enhance the data. Unfortunately, many data sources used in the VA process are affected by uncertainty. In addition, the VA cycle itself can introduce uncertainty to the knowledge generation process but does not provide a mechanism to handle these sources of uncertainty. In this manuscript, we aim to provide an extended VA cycle that is capable of handling uncertainty by quantification, propagation, and visualization, defined as uncertainty-aware visual analytics (UAVA). Here, a recap of uncertainty definition and description is used as a starting point to insert novel components in the visual analytics cycle. These components assist in capturing uncertainty throughout the VA cycle. Further, different data types, hypothesis generation approaches, and uncertainty-aware visualization approaches are discussed that fit in the defined UAVA cycle. In addition, application scenarios that can be handled by such a cycle, examples, and a list of open challenges in the area of UAVA are provided.
In this paper we consider the stochastic primitive equation for geophysical flows subject to transport noise and turbulent pressure. Admitting very rough noise terms, the global existence and uniqueness of solutions to this stochastic partial differential equation are proven using stochastic maximal
-regularity, the theory of critical spaces for stochastic evolution equations, and global a priori bounds. Compared to other results in this direction, we do not need any smallness assumption on the transport noise which acts directly on the velocity field and we also allow rougher noise terms. The adaptation to Stratonovich type noise and, more generally, to variable viscosity and/or conductivity are discussed as well.
Municipal wastewater is an interesting source of phosphorus and several processes for the recovery of phosphorus from this source have been described. These processes yield magnesium ammonium phosphate (MAP), a valuable fertilizer. In these processes, pH shifts and the addition of chemicals are used to influence the species distribution in the solution such as to finally obtain the desired product and to prevent the co-precipitation of salts of heavy metal ions. Elucidating these species distributions experimentally is a challenging and cumbersome task. Therefore, in the present work, a thermodynamic model was developed that can be used for predicting the species distributions in the various steps of the recovery process. The model combines the extended Debye-Hückel equation for the prediction of activity coefficients with dissociation constants and solubility product data from the literature and contains no parameters that need to be adjusted to process data. The model was successfully tested by comparison to experimental data for the Stuttgart process from the literature and used for analyzing the different process steps. Furthermore, it was demonstrated how the model can be used for optimizing the process.
Aflatoxins, a group of mycotoxins produced by various mold species within the genus Aspergillus, have been extensively investigated for their potential to contaminate food and feed, rendering them unfit for consumption. Nevertheless, the role of aflatoxins as environmental contaminants in soil, which represents their natural habitat, remains a relatively unexplored area in aflatoxin research. This knowledge gap can be attributed, in part, to the methodological challenges associated with detecting aflatoxins in soil. The main objective of this PhD project was to develop and validate an analytical method that allows monitoring of aflatoxins in soil, and scrutinize the mechanisms and extent of occurrence of aflatoxins in soil, the processes governing their dissipation, and their impact on the soil microbiome and associated soil functions. By utilizing an efficient extraction solvent mixture comprising acetonitrile and water, coupled with an ultrasonication step, recoveries of 78% to 92% were achieved, enabling reliable determination of trace levels in soil ranging from 0.5 to 20 µg kg-1. However, in a field trial conducted in a high-risk model region for aflatoxin contamination in Sub-Saharan Africa, no aflatoxins were detected using this procedure, underscoring the complexities of field monitoring. These challenges encompassed rapid degradation, spatial heterogeneity, and seasonal fluctuations in aflatoxin occurrence. Degradation experiments revealed the importance of microbial and photochemical processes in the dissipation of aflatoxins in soil with half-lives of 20 - 65 days. The rate of dissipation was found to be influenced by soil properties, most notably soil texture and the initial concentration of aflatoxins in the soil. An exposure study provided evidence that aflatoxins do not pose a substantial threat to the soil microbiome, encompassing microbial biomass, activity, and catabolic functionality. This was particularly evident in clayey soils, where the toxicity of aflatoxins diminished significantly due to their strong binding to clay minerals. However, several critical questions remain unanswered, emphasizing the necessity for further research to attain a more comprehensive understanding of the ecological importance of aflatoxins. Future research should prioritize the challenges associated with field monitoring of aflatoxins, elucidate the mechanisms responsible for the dissipation of aflatoxins in soil during microbial and photochemical degradation, and investigate the ecological consequences of aflatoxins in regions heavily affected by aflatoxins, taking into account the interactions between aflatoxins and environmental and anthropogenic stressors. Addressing these questions contributes to a comprehensive understanding of the environmental impact of aflatoxins in soil, ultimately contributing to more effective strategies for aflatoxin management in agriculture.
In recent decades, academia has addressed a wide range of research topics in the field of ethical decision-making. Besides a great amount of research on ethical consumption, also the domain of ethical investments increasingly moves in the focus of scholars. While in this area most research focuses on whether socially or environmentally sustainable businesses outperform traditional investments financially or investigates the character traits as well as other socio-demographic factors of ethical investors, the impact of sustainable corporate conduct on the investment intentions of private investors still requires further research. Hence, we conducted two studies to shed more light on this highly relevant topic. After discussing the current state of research, in our first empirical study, we explore whether besides the traditional triad of risk, return, and liquidity, also sustainability exerts a significant impact on the willingness to invest. As hypothesized, we find that sustainability shows a clear and decisive impact in addition to the traditional factors. In a consecutive study, we investigate deeper into the sustainability-willingness to invest link. Here, our results show that improved sustainability might not pay off in terms of investment attractiveness, however and conversely, it certainly harms to conduct business in a non-sustainable manner, which cannot even be compensated by an increased return.