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Connections between crystal chemistry and critical temperature Tc have been in the focus of superconductivity, one of the most widely studied phenomena in physics, chemistry, and materials science alike. In most Fe-based superconductors, materials chemistry and physics conspire so that Tc correlates with the average anion height above the Fe plane, i.e., with the geometry of the FeAs4 or FeCh4 (Ch = Te, Se, or S) tetrahedron. By synthesizing Fe1–ySe1–xSx (0 ≤ x ≤ 1; y ≤ 0.1), we find that in alloyed crystals Tc is not correlated with the anion height like it is for most other Fe superconductors. Instead, changes in Tc(x) and tetragonal-to-orthorhombic (nematic) transition Ts(x) upon cooling are correlated with disorder in Fe vibrations in the direction orthogonal to Fe planes, along the crystallographic c-axis. The disorder stems from the random nature of S substitution, causing deformed Fe(Se,S)4 tetrahedra with different Fe–Se and Fe–S bond distances. Our results provide evidence of Tc and Ts suppression by disorder in anion height. The connection to local crystal chemistry may be exploited in computational prediction of new superconducting materials with FeSe/S building blocks.

Remote sensing satellite images in the optical domain often contain missing or misleading data due to overcast conditions or sensor malfunctioning, concealing potentially important information. In this paper, we apply expectation maximization (EM) Tucker to NDVI satellite data from the Iberian Peninsula in order to gap-fill missing information. EM Tucker belongs to a family of tensor decomposition methods that are known to offer a number of interesting properties, including the ability to directly analyze data stored in multidimensional arrays and to explicitly exploit their multiway structure, which is lost when traditional spatial-, temporal- and spectral-based methods are used. In order to evaluate the gap-filling accuracy of EM Tucker for NDVI images, we used three data sets based on advanced very-high resolution radiometer (AVHRR) imagery over the Iberian Peninsula with artificially added missing data as well as a data set originating from the Iberian Peninsula with natural missing data. The performance of EM Tucker was compared to a simple mean imputation, a spatio-temporal hybrid method, and an iterative method based on principal component analysis (PCA). In comparison, imputation of the missing data using EM Tucker consistently yielded the most accurate results across the three simulated data sets, with levels of missing data ranging from 10 to 90%

ticks carry pathogens that can cause disease in both animals and humans, and there is a need to monitor the distribution and abundance of ticks and the pathogens they carry to pinpoint potential high risk areas for tick-borne disease transmission. In a joint Scandinavian study, we measured Ixodes ricinus instar abundance at 159 sites in southern Scandinavia in August-September, 2016, and collected 29,440 tick nymphs at 50 of these sites. We additionally measured abundance at 30 sites in August-September, 2017. We tested the 29,440 tick nymphs in pools of 10 in a Fluidigm real-time PCR chip to screen for 17 different tick-associated pathogens, 2 pathogen groups and 3 tick species. We present data on the geolocation, habitat type and instar abundance of the surveyed sites, as well as presence/absence of each pathogen in all analysed pools from the 50 collection sites and individual prevalence for each site. these data can be used alone or in combination with other data for predictive modelling and mapping of high-risk areas., Ticks carry pathogens that can cause disease in both animals and humans, and there is a need to monitor the distribution and abundance of ticks and the pathogens they carry to pinpoint potential high risk areas for tick-borne disease transmission. In a joint Scandinavian study, we measured Ixodes ricinus instar abundance at 159 sites in southern Scandinavia in August-September, 2016, and collected 29,440 tick nymphs at 50 of these sites. We additionally measured abundance at 30 sites in August-September, 2017. We tested the 29,440 tick nymphs in pools of 10 in a Fluidigm real-time PCR chip to screen for 17 different tick-associated pathogens, 2 pathogen groups and 3 tick species. We present data on the geolocation, habitat type and instar abundance of the surveyed sites, as well as presence/absence of each pathogen in all analysed pools from the 50 collection sites and individual prevalence for each site. These data can be used alone or in combination with other data for predictive modelling and mapping of high-risk areas.

During water stress, crops undertake adjustments in functional, structural, and biochemical traits. Hyperspectral data and machine learning techniques (PLS-R) can be used to assess water stress responses in plant physiology. In this study, we investigated the potential of hyperspectral optical (VNIR) measurements supplemented with thermal remote sensing and canopy height (hc) to detect changes in leaf physiology of soybean (C3) and maize (C4) plants under three levels of soil moisture in controlled environmental conditions. We measured canopy evapotranspiration (ET), leaf transpiration (Tr), leaf stomatal conductance (gs), leaf photosynthesis (A), leaf chlorophyll content and morphological properties (hc and LAI), as well as vegetation cover reflectance and radiometric temperature (TL,Rad). Our results showed that water stress caused significant ET decreases in both crops. This reduction was linked to tighter stomatal control for soybean plants, whereas LAI changes were the primary control on maize ET. Spectral vegetation indices (VIs) and TL,Rad were able to track these different responses to drought, but only after controlling for confounding changes in phenology. PLS-R modeling of gs, Tr, and A using hyperspectral data was more accurate when pooling data from both crops together rather than individually. Nonetheless, separated PLS-R crop models are useful to identify the most relevant variables in each crop such as TL,Rad for soybean and hc for maize under our experimental conditions. Interestingly, the most important spectral bands sensitive to drought, derived from PLS-R analysis, were not exactly centered at the same wavelengths of the studied VIs sensitive to drought, highlighting the benefit of having contiguous narrow spectral bands to predict leaf physiology and suggesting different wavelength combinations based on crop type.

Unlike satellite earth observation, multispectral images acquired by Unmanned Aerial Systems (UAS) provide great opportunities to monitor land surface conditions also in cloudy or overcast weather conditions. This is especially relevant for high latitudes where overcast and cloudy days are common. However, multispectral imagery acquired by miniaturized UAS sensors under such conditions tend to present low brightness and dynamic ranges, and high noise levels. Additionally, cloud shadows over space (within one image) and time (across images) are frequent in UAS imagery collected under variable irradiance and result in sensor radiance changes unrelated to the biophysical dynamics at the surface. To exploit the potential of UAS for vegetation mapping, this study proposes methods to obtain robust and repeatable reflectance time series under variable and low irradiance conditions. To improve sensor sensitivity to low irradiance, a radiometric pixel-wise calibration was conducted with a six-channel multispectral camera (mini-MCA6, Tetracam) using an integrating sphere simulating the varying low illumination typical of outdoor conditions at 55oN latitude. The sensor sensitivity was increased by using individual settings for independent channels, obtaining higher signal-to-noise ratios compared to the uniform setting for all image channels. To remove cloud shadows, a multivariate statistical procedure, Tucker tensor decomposition, was applied to reconstruct images using a four-way factorization scheme that takes advantage of spatial, spectral and temporal information simultaneously. The comparison between reconstructed (with Tucker) and original images showed an improvement in cloud shadow removal. Outdoor vicarious reflectance validation showed that with these methods, the multispectral imagery can provide reliable reflectance at sunny conditions with root mean square deviations of around 3%. The proposed methods could be useful for operational multispectral mapping with UA

Efficient regeneration of NAD(P)+ cofactors is essential for large‐scale application of alcohol dehydrogenases due to the high cost and chemical instability of these cofactors. NAD(P)+ can be regenerated effectively using NAD(P)H oxidases that require molecular oxygen as a co‐substrate. In large‐scale biocatalytic processes, agitation and aeration are needed for sufficient oxygen transfer into the liquid phase, both of which have been shown to significantly increase the rate of enzyme deactivation. As such, the aim of this study was to identify the existence of a correlation between enzyme stability and gas‐liquid interfacial area inside the bioreactor. This was done by measuring gas‐liquid interfacial areas inside an aerated stirred reactor, using an in situ optical probe, and simultaneously measuring the kinetic stability of NAD(P)H oxidase. Following enzyme incubation at various power inputs and gas‐phase compositions, the residual activity was assessed and video samples were analysed through an image processing algorithm. Enzyme deactivation was found to be proportional to an increase in interfacial area up to a certain limit, where power input appears to have a higher impact. Furthermore, the presence of oxygen increased enzyme deactivation rates at low interfacial areas. The areas were validated with defined glass beads and found to be in the range of those in large‐scale bioreactors. Finally, a correlation between the enzyme half‐life and specific interfacial area was obtained. Therefore, we conclude that the method developed in this contribution can help to predict the behavior of biocatalyst stability under industrially relevant conditions, concerning specific gas‐liquid interfacial areas.

Recently, focus on tick-borne diseases has increased as ticks and their pathogens have become widespread and represent a health problem in Europe. Understanding the epidemiology of tickborne infections requires the ability to predict and map tick abundance. We measured Ixodes ricinus abundance at 159 sites in southern Scandinavia from August-September, 2016. We used feld data and environmental variables to develop predictive abundance models using machine learning algorithms, and also tested these models on 2017 data. Larva and nymph abundance models had relatively high predictive power (normalized RMSE from 0.65–0.69, R2 from 0.52–0.58) whereas adult tick models performed poorly (normalized RMSE from 0.94–0.96, R2 from 0.04–0.10). Testing the models on 2017 data produced good results with normalized RMSE values from 0.59–1.13 and R2 from 0.18–0.69. The resulting 2016 maps corresponded well with known tick abundance and distribution in Scandinavia. The models were highly infuenced by temperature and vegetation, indicating that climate may be an important driver of I. ricinus distribution and abundance in Scandinavia. Despite varying results, the models predicted abundance in 2017 with high accuracy. The models are a frst step towards environmentally driven tick abundance models that can assist in determining risk areas and interpreting human incidence data.

Background: Tick-borne diseases have become increasingly common in recent decades and present a health problem in many parts of Europe. Control and prevention of these diseases require a better understanding of vector distribution. Aim: Our aim was to create a model able to predict the distribution of Ixodes ricinus nymphs in southern Scandinavia and to assess how this relates to risk of human exposure. Methods: We measured the presence of I. ricinus tick nymphs at 159 stratified random lowland forest and meadow sites in Denmark, Norway and Sweden by dragging 400 m transects from August to September 2016, representing a total distance of 63.6 km. Using climate and remote sensing environmental data and boosted regression tree modelling, we predicted the overall spatial distribution of I. ricinus nymphs in Scandinavia. To assess the potential public health impact, we combined the predicted tick distribution with human density maps to determine the proportion of people at risk. Results: Our model predicted the spatial distribution of I. ricinus nymphs with a sensitivity of 91% and a specificity of 60%. Temperature was one of the main drivers in the model followed by vegetation cover. Nymphs were restricted to only 17.5% of the modelled area but, respectively, 73.5%, 67.1% and 78.8% of the human populations lived within 5 km of these areas in Denmark, Norway and Sweden. Conclusion: The model suggests that increasing temperatures in the future may expand tick distribution geographically in northern Europe, but this may only affect a small additional proportion of the human population.

Partial Least Squares (PLS) regression is a statistical method for supervised multivariate analysis. It relates two data blocks X and Y to each other with the aim of establishing a prediction model. When deployed in production, this model can be used to predict an outcome y from a newly measured feature vector x. PLS is popular in chemometrics, process control and other analytic fields, due to its striking advantages, namely the ability to analyze small sample sizes and the ability to handle high-dimensional data with cross-correlated features (where Ordinary Least Squares regression typically fails). In addition, and in contrast to many other machine learning approaches, PLS models can be interpreted using its latent variable structure just like principal components can be interpreted for a PCA analysis.

Magnetic order is a dominating phase in iron based pnictides and chalcogenides. Neither its origin nor its interplay with the neighbouring phases of nematic order and unconventional superconductivity are well understood yet. Raman spectroscopy allows access to the relevant excitations. This thesis focusses on the role of magnetism on lattice anomalies and the discrimination of localized and itinerant magnetic order. Simulations and experiments show that the magnetism in FeSe results from frustrated localized moments., Magnetische Ordnung ist eine dominierende Phase in eisenbasierten Pniktiden und Chalcogeniden. Weder ihr Ursprung noch ihre Wechselwirkung mit den benachbarten Phasen der nematischen Ordnung und der unkonventionellen Supraleitung sind wohlverstanden. Raman-Spektroskopie erlaubt Zugang zu den relevanten Anregungen. Im Fokus dieser Arbeit stehen die Rolle des Magnetismus bei Gitteranomalien und die Unterscheidung von lokalisierter und itineranter magnetischer Ordnung. Simulationen und Experiment zeigen, dass der Magnetismus in FeSe von frustrierten lokalisierten Momenten stammt.

Magnetic order is a dominating phase in iron based pnictides and chalcogenides. Neither its origin nor its interplay with the neighbouring phases of nematic order and unconventional superconductivity are well understood yet. Raman spectroscopy allows access to the relevant excitations. This thesis focusses on the role of magnetism on lattice anomalies and the discrimination of localized and itinerant magnetic order. Simulations and experiments show that the magnetism in FeSe results from frustrated localized moments., Magnetische Ordnung ist eine dominierende Phase in eisenbasierten Pniktiden und Chalcogeniden. Weder ihr Ursprung noch ihre Wechselwirkung mit den benachbarten Phasen der nematischen Ordnung und der unkonventionellen Supraleitung sind wohlverstanden. Raman-Spektroskopie erlaubt Zugang zu den relevanten Anregungen. Im Fokus dieser Arbeit stehen die Rolle des Magnetismus bei Gitteranomalien und die Unterscheidung von lokalisierter und itineranter magnetischer Ordnung. Simulationen und Experiment zeigen, dass der Magnetismus in FeSe von frustrierten lokalisierten Momenten stammt.

In recent years, focus on tick-borne diseases has increased as diseases such as Lyme disease and tick-borne encephalitis have become more common and represent a health problem in many parts of Scandinavia. More effective prevention of infections requires a better understanding of the factors affecting the vector abundance as well as human exposure to the vectors. Hence, there is a great need for analyses and models that can predict how vectors and their associated diseases are distributed now and possibly in the future. As a part of the ScandTick Innovation project, we surveyed tick nymphs at 159 sites (forests and meadows) in Denmark, southern Norway and south-eastern Sweden. At each site we measured presence/absence, and used the data obtained along with environmental data from satellite images to run Boosted Regression Tree machine learning algorithms to predict overall distribution in southern Scandinavia. Together with the predicted distribution maps, we used human density maps to identify and plot areas with high risk of exposure to ticks. The predicted distribution and the spatial variation found corresponded well with known distributions of ticks in Scandinavia (sensitivity: 91%, specificity: 60%), and we found that the model was predominantly temperature-driven. Because presence was strongly correlated with forested habitats the risk areas were much larger in Sweden and Norway compared to Denmark. When combining these distribution maps with human population density maps, we were able to quantify the proportion of people living in areas with tick presence in Scandinavia. We found that although tick nymphs were restricted to a small proportion of the modelled area, high proportions of the human populations (67-79%) lived within these same areas. The model suggests that a potential future range expansion of I. ricinus in Scandinavia is likely but may only affect a relatively small additional proportion of the human population.

In relation to downstream processing of a fermentation broth coagulation/flocculation is a typical pretreatment method for separating undesirable particles/impurities from the wanted product. In the coagulation process the negatively charged impurities are destabilized by adding of a clarifying agent thereby neutralizing the charges on the particles. Particles thus agglomerate. Larger agglomerates are formed in the flocculation process by adding a polymer, which forms bridges between the particles. The operation of coagulators, flocculators and clarifiers requires trained operators implying the human factor to play a major risk with regard to performance. Better process monitoring will provide the means for improved control giving higher yield, better quality, and minimize the consumption of water. In particular, the optimal separation of biomass from a soluble enzyme phase is often dependent on an initial coagulation of the biomass and a final flocculation of the solids just prior to separation. We investigate flocculation processes at Novozymes facilities so that the response time and risk of error is minimized. We use oCelloScope [1], an automated microscope, for imaging samples from the flocculation process and subsequently we extract image features for qualitative and quantitative image characterization. The processing include image morphology, image segmentation and image quantification. The aim is to correlate image information to “quality” of the separation process. Here we report our initial finding. [1] M.Fredborg et al. Journal of Clinical Microbiology Vol 51 Number 7 p. 2047–2053 (2013); http://www.biosensesolutions.dk

Ein sich ändernder Energiesektor erfordert Anpassungen der Betriebsweise von in Kraftwerken eingesetzten Pumpen. Insbesondere im Falle mehrstufiger Kesselspeisepumpen restringieren auftretende Kennlinieninstabilitäten die Betriebsgrenzen der Maschinen. Um einen sicheren teillastigen Betrieb solcher Pumpen sicherzustellen, besteht die Herausforderung allgemein gültige Methoden zur Beseitigung auftretender Kennlinieninstabilität herauszuarbeiten. Als Ursache von Kennlinieninstabilitäten mehrstufiger Kesselspeisepumpen konnte in einer Vielzahl vorangegangener Untersuchungen die auftretende Rotor-Stator Interaktion zwischen Laufrad und nachgeschaltetem Leitrad ausgemacht werden. Aufgrund der Komplexität der durch die Rotor-Stator Interaktion induzierten, hochgradig instationären Strömung, sind die der Kennlinieninstabilität zugrundeliegenden Strömungsphänomene bis heute noch nicht vollständig verstanden. Einigkeit herrscht darüber, dass der Schrägabschnitt des Leitrades bei Einsetzen einer Kennlinieninstabilität einen Einbruch im Druckaufbau erfährt, was die Stabilität der gesamten Kennlinie signifikant beeinflusst. Die vorliegende Arbeit befasst sich mit der Untersuchung der Schrägabschnittsgestaltung von Leiträdern und deren Einfluss auf die Kennlinieninstabilität einer radialen Kreiselpumpe. Hierzu wurde ein modularer Pumpenprüfstand entwickelt. Dieser umfasst als Hydraulik eine Repetierstufe mit einer im Auslegungspunkt vorherrschenden, spezifischen Drehzahl von nq = 35 (min,m3/s, m). Bei der Leitradauslegung wurde darauf geachtet, dass sich lediglich der Querschnittsflächenverlauf im Schrägabschnitt ändert. Der Leitradeintrittswinkel, engste Querschnitt und Diffusorverlauf blieben unverändert. Als Referenz zum allgemeinen Einfluss des Leitrades auf die Kennlinie wurde zusätzlich eine Variante mit glattem Leitring untersucht. Neben den klassischen Performance-Kennwerten erfolgte zur Bestimmung des sich ändernden Strömungsverhaltens eine Auswertung der Komponentenken, Changing demands during the energy transmission require the operating mode of pumps used in power plants to be adapted. Particularly in the case of multi-stage boiler feed pumps, head-curve instability restricts the operating flow range. In order to ensure safe off-design operation, the challenge is to find out generally valid ways to eliminate the head-curve instability of those pumps. A large number of previous studies have identified the rotor-stator interaction between the impeller and the vaned diffuser as the cause of the head-curve instability for this specific type of pumps. Due to the complexity of the highly unsteady flow induced by rotor-stator interaction, the flow phenomena underlying the performance curve instability are not fully understood yet. It is commonly believed, that the inlet triangle section of the vaned diffuser has an important role in the shape of the head-curve and instability. The present work investigates the inlet triangle section design of the vaned diffuser and its influence on the head-curve instability of a centrifugal pump. For this purpose a model pump with a modular design has been developed. The pump represents a middle stage of a multistage pumpe with a specific speed of nq = 35 (min,m3/s, m) at design conditions. When designing the vaned diffuser, care was taken to ensure that only the area distribution in the inlet triangle section is changed, while the inlet angle, throat area and the guide-vane channel shape are kept unaffected. As a reference, a model variation with a vaneless diffuser has additionally been investigated. Besides classic performance characteristics the changing flow behavior was determined by evaluating the internal head curves. Furthermore, pressure pulsations occurring at various radial positions in the vaned diffuser and axial forces are evaluated.