Direct Imaging of Chiral Domain Walls and Néel-Type Skyrmionium in Ferrimagnetic Alloys

The evolution of chiral spin structures is studied in ferrimagnetic Ta/Ir/Fe/GdFeCo/Pt multilayers as a function of temperature using scanning electron microscopy with polarization analysis (SEMPA). The GdFeCo ferrimagnet exhibits pure right-handed Néel-type domain wall (DW) spin textures over a large temperature range. This indicates the presence of a negative Dzyaloshinskii–Moriya interaction that can originate from both the top Fe/Pt and the Co/Pt interfaces. From measurements of the DW width, as well as complementary magnetic characterization, the exchange stiffness as a function of temperature is ascertained. The exchange stiffness is surprisingly more or less constant, which is explained by theoretical predictions. Beyond single skyrmions, it is identified by direct imaging a pure Néel-type skyrmionium, which due to the expected vanishing skyrmion Hall angle, is a promising topological spin structure to enable applications by next generation of spintronic devices.     

An online method for estimation of degradable substrate and biomass in an aerated activated sludge process

The activated sludge process for degradation of organic matter is one of the main processes commonly used in biological wastewater treatment, and aeration in that process stands for a large part of the energy consumed in a plant. Hence, there have been many attempts to improve the operation of the activated sludge process using mathematical models of the process. The advanced models used has in general their origin in IWA (former IAWQ) activated sludge model no 1 (ASM1). Unfortunately, optimization w.r.t. discharge and economy is limited for municipal wastewater treatment plants because several of the most important variables; heterotrophic biomass, readily biodegradable soluble substrate, and slowly biodegradable substrate cannot be reliably measured online because of their complexity hiding behind their notation. With the predenitrifying WWTP in Göteborg having post nitrification in trickling filters as an example, we resolve this problem by deriving an observer that estimates these concentrations in the aerobic parts based on only the commonly available online measurements of oxygen, water flows, TSS concentration and supplied air. Based on control theory analysis and simulations it is concluded that estimation does not work for an activated sludge process with aeration in one stirred tank alone, but when the activated sludge process can be described by at least two tanks in series, with oxygen measurements in each tank, the estimates converge. A sensitivity analysis with respect to deviations in model parameters reveals that the derived estimator is also fairly robust to model errors.     

Modeling the elution of organic chemicals from a melting homogeneous snow pack

Organic chemicals are often released in peak concentrations from melting snow packs. A simple, mechanistic snowmelt model was developed to simulate and predict the elution of organic substances from melting, homogeneous snow, as influenced by chemical properties and snow pack characteristics. The model calculates stepwise the chemical transport along with the melt water flow in a multi-layered snow pack, based on chemical equilibrium partitioning between the individual bulk snow phases. The model succeeds in reproducing the elution behavior of several organic contaminants observed in previously conducted cold room experiments. The model aided in identifying four different types of enrichment of organic substances during snowmelt. Water soluble substances experience peak releases early during a melt period (type 1), whereas chemicals that strongly sorb to particulate matter (PM) or snow grain surfaces elute at the end of melting (type 2). Substances that are somewhat water soluble and at the same time have a high affinity for snow grain surfaces may exhibit increasing concentrations in the melt water (type 3). Finally, elution sequences involving peak loads both at the beginning and the end of melting are simulated for chemicals that are partially dissolved in the aqueous melt water phase and partially sorbed to PM (type 4). The extent of type 1 enrichment mainly depends on the snow depth, whereby deeper snow generates more pronounced concentration peaks. PM influences the elution behavior of organic chemicals strongly because of the very large natural variability in the type and amount of particles present in snow. Urban and road-side snow rich in PM can generate type 2 concentration peaks at the end of the melt period for even relatively water soluble substances. From a clean, melting snow pack typical for remote regions, even fairly hydrophobic chemicals can be released in type 1 mode while being almost completely dissolved in the aqueous melt water phase. The model provides a mechanistic understanding of the processes that lead to chemical peak releases during snowmelt.     

Protein association of β-N-methylamino-L-alanine in Triticum aestivum via irrigation

Bioaccumulation of several cyanotoxins has been observed in numerous food webs. More recently, the neurotoxic, non-proteinogenic amino acid β-N-methylamino-L-alanine (BMAA) was shown to biomagnify in marine food webs. It was thus necessary to assess whether a human exposure risk via a terrestrial food source could exist. As shown for other cyanotoxins, spray irrigation of crop plants with cyanobacterial bloom-contaminated surface water poses the risk of toxin transfer into edible plant parts. Therefore, in the present study, we evaluated a possible transfer of BMAA via spray irrigation into the seeds of one of the world’s most widely cultivated crop plants, Triticum aestivum. Wheat plants were irrigated with water containing 10 µg L^?1 BMAA until they reached maturity and seed-bearing stage (205 days). Several morphological characteristics, such as germination rate, number of roots per seedling, length of primary root and cotyledon, and diameter of the stems were evaluated to assess the effects of chronic exposure. After 205 days, BMAA bioaccumulation was quantified in roots, shoots, and mature seeds of T. aestivum. No adverse morphology effects were observed and no free intracellular BMAA was detected in any of the exposed plants. However, in mature seeds, protein-associated BMAA was detected at 217 ± 150 ng g FW^?1; significantly more than in roots and shoots. This result demonstrates the unexpected bioaccumulation of a hydrophilic compound and highlights the demand to specify in addition to limit values for drinking water, tolerable daily intake rates for the cyanobacterial-neurotoxin BMAA.     

Modelling of Thermal Sterilisation of High-Moisture Snack Foods: Feasibility Analysis and Optimization

High-moisture snacks, such as steamed buns and rice cakes, are traditional and popular in Asian countries. However, their shelf life is short, primarily due to microbial spoilage. Current manufacturing methods address this shortcoming through the use of chemical preservatives. To satisfy consumers’ demand for preservative-free food, thermal sterilisation of a model high-moisture snack (steamed rice cakes) is investigated in this work. Bacillus cereus spores are heat-resistant pathogens typically found in rice products; hence, they constitute a suitable candidate to assess the effectiveness of thermal sterilisation. A validated combination of predicted temperature profile of rice cakes based on thermal properties extracted experimentally with thermal inactivation kinetics of B. cereus spores allows us to assess the sensitivity of processing conditions to sterilisation efficiency. Using both experimentation and modelling, it is shown that enhancement of heat transfer by improving convection from the heating medium (either water or steam) has a limited effect on inactivation due to the intrinsic kinetics of spore inactivation.     

Illustrating sensitivity and uncertainty in environmental fate models using partitioning maps

Variations of model predictions of the environmental fate of organic contaminants are usually analyzed for only one or at most a few selected chemicals, even though parameter sensitivity and contribution to uncertainty are widely different for different chemicals. A graphical method is introduced that allows for the comprehensive investigation of model sensitivity and uncertainty for all persistent organic nonelectrolytes at the same time. This is achieved by defining a two-dimensional hypothetical "chemical space" as a function of the equilibrium partition coefficients between air, water, and octanol (KOW, KAW, KOA), and plotting sensitivity and/or uncertainty of a specific model result to each input parameter as a function of this chemical space. The approach is illustrated for the bulk phase concentrations in air, water, soil, and sediment calculated by a level III model. Colored contour maps facilitate the identification of those input parameters that cause a high output variation of hypothetical and real chemicals. They also allow for the easy categorization of chemicals in terms of common parameter sensitivities, and thus comparable environmental behavior. Sensitivity varies with the mode of emission and the degradability of the chemicals, making it necessary to develop multiple sets of contour maps. Comparison of these sets of maps in turn allows the investigation of how parameter sensitivities change as a result of changes in mode of emission and persistence. The presented method can be used for investigating the sensitivity of any prediction obtained with any linear fate model that characterizes the partitioning behavior of organic chemicals with KAW, KoW, and KOA. Once the sensitivity maps have been constructed for a given environmental scenario, it is possible to perform a sensitivity analysis for a specific chemical by simple. placement of the substances' partitioning combinations within the chemical space. The maps can further contribute to the mechanistic understanding of a model's behavior, can aid in explaining observations of divergent environmental behavior of related substances, and can provide a rationale for grouping chemicals with similar model behavior, or for selecting representative example chemicals for a model investigation. They can also help in deciding when accurate and precise knowledge of physical chemical property data is crucial and when approximate numbers suffice to conduct a model investigation.     

Differentiation of animal species in food by oligonucleotide microarray hybridization

Oligonucleotide microarray hybridization analysis of polymerase chain reaction (PCR) products from the mitochondrial cytochrome b gene DNA was applied to identify different animal species in meat and cheese food samples. A pair of universal primers binding to conserved regions of the vertebrate mitochondrial cytochrome b gene was used to amplify a 377 bp fragment with internal regions of high inter-species variability. PCR products of cattle, pig, chicken, turkey, sheep and goat were unequivocally identified by hybridization with species-specific probe sequences immobilized on an oligonucleotide microarray. In meat samples, 0.1% admixtures of beef or chicken meat were still detectable. By using this new PCR-based DNA chip hybridization for the analysis of 24 commercial food samples from routine control, the simultaneous species composition of mixtures with up to four different species could be determined in a single experiment. The results agreed well with those from the reference methods performed at the local food control authority, which are a combination of enzyme-linked immunosorbent assay (ELISA), species-specific PCR and PCR–RFLP (restriction fragment length polymorphism). Thus, the DNA chip hybridization analysis of cytochrome b PCR products offers a new way for rapid and sensitive species differentiation in food.     

UXO and environmental risk factors impacting EOD operations in German waters**

This article presents risk factors that are associated with the handling of unexploded ordnance (UXO) during explosive ordnance disposal (EOD) operations in German waters. The construction of offshore wind parks and the German immediate action program are expected to increase the number of EOD operations. Existing literature and guidelines do not offer a structured and reproducible framework for assessing EOD risk. To fill this gap, a network of EOD risk factors was developed by means of a literature review and validation via expert consultation. The study was scoped to “personnel and equipment at the EOD location” as the risk receptor and “undesired detonation” as the undesired event under investigation. Factors are subdivided into UXO factors that depend on the object that should be handled and factors that describe the object's surrounding environment. While the former can be researched by an EOD expert, the latter must be measured on site or acquired from a model. Each of these factors contributes to risk, some directly and others indirectly via other factors. The complexity of the resulting network, with its 33 factors, demonstrates the need for a reliable and reproducible model to quantify EOD risk. Its purpose is not to replace EOD experts but to aid them in their decision-making process. Such a tool can provide valuable support for the high-cost and high-risk EOD operations.