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A significant fraction of massive stars move at speed through the interstellar medium of galaxies.
After their death as core-collapse supernovae, a possible final evolutionary state is that of a fast-rotating magnetized neutron star, shaping its circumstellar medium into a pulsar wind nebula.
Understanding the properties of pulsar wind nebulae requires knowledge of the evolutionary history of their massive progenitors.
Using two-dimensional magnetohydrodynamical simulations, we demonstrate that, in the context of a runaway high-mass red-supergiant supernova progenitor, the morphology of its subsequent pulsar wind nebula is strongly affected by the wind of the defunct progenitor star pre-shaping the stellar surroundings throughout its entire past life.
In particular, pulsar wind nebulae of obscured runaway massive stars harbour asymmetries as a function of the morphology of the progenitor's wind-blown cavity, inducing projected asymmetric up-down synchrotron emission.
Equilibrium mass-dependent ("stable") isotopic fractionation of an element during magmatic processes is driven by a contrast in bonding environment between minerals and silicate melt, which is expressed as an isotopic fractionation factor.
A quantitative understanding of such isotopic fractionation factors is vital to interpret observed isotopic variations in magmatic rocks.
It is well known that the local environment and the bond strength of an element dictate the sign and magnitude of isotopic fractionation between minerals, but it is uncertain how the structure and chemical composition of a silicate melt can affect mineral-melt isotopic fractionation factors.
To explore this, we studied the coordination environment of nickel (Ni) in different silicate glasses using extended X-ray absorption fine structure (EXAFS) measurements at the German synchrotron X-ray source (DESY).
We determined -Ni-O bond lengths in a suite of synthetic but near-natural silicate glasses using EXAFS and found that the former vary systematically with melt alkalinity, which is best described by the parameter ln[1 + (Na + K)/Ca]. With increasing melt alkalinity, Ni occupies more IV-fold coordinated sites, which are associated with a shorter -Ni-O bond length. Next, we use the ionic model, which allows to predict isotopic fractionation factors based on the difference in bond length between two phases.
We find that more alkaline melts have a stronger preference for the heavier isotopes of Ni than less alkaline melts. This implies that the magnitude of mineral-melt Ni isotope fractionation factors, for instance between olivine and melt, will depend on the alkalinity of the melt.
At magmatic temperatures, however, the variation in fractionation factors caused by melt alkalinity will rarely exceed 0.05 parts per thousand and is thus mostly negligible, in particular in the realm of basaltic melt compositions. Nevertheless, the relationship between melt alkalinity and fractionation factor reported here can be used to extrapolate empirical data for mineral-melt Ni isotope fractionation factors, once such data become available, to the full range of magma compositions on Earth and other Solar System bodies.
Reentrant tensegrity
(2021)
We present a three-periodic, chiral, tensegrity structure and demonstrate that it is auxetic. Our tensegrity structure is constructed using the chiral symmetry Pi(+) cylinder packing, transforming cylinders to elastic elements and cylinder contacts to incompressible rods. The resulting structure displays local reentrant geometry at its vertices and is shown to be auxetic when modeled as an equilibrium configuration of spatial constraints subject to a quasi-static deformation. When the structure is subsequently modeled as a lattice material with elastic elements, the auxetic behavior is again confirmed through finite element modeling. The cubic symmetry of the original structure means that the auxetic behavior is observed in both perpendicular directions and is close to isotropic in magnitude. This structure could be the simplest three-dimensional analog to the two-dimensional reentrant honeycomb. This, alongside the chirality of the structure, makes it an interesting design target for multifunctional materials.
Landslide hazard models aim at mitigating landslide impact by providing probabilistic forecasting, and the accuracy of these models hinges on landslide databases for model training and testing.
Landslide databases at times lack information on the underlying triggering mechanism, making these inventories almost unusable in hazard models.
We developed a Python-based unique library, Landsifier, that contains three different machine-Learning frameworks for assessing the likely triggering mechanisms of individual landslides or entire inventories based on landslide geometry.
Two of these methods only use the 2D landslide planforms, and the third utilizes the 3D shape of landslides relying on an underlying digital elevation model (DEM). The base method extracts geometric properties of landslide polygons as a feature space for the shallow learner - random forest (RF).
An alternative method relies on landslide planform images as an input for the deep learning algorithm - convolutional neural network (CNN).
The last framework extracts topological properties of 3D landslides through topological data analysis (TDA) and then feeds these properties as a feature space to the random forest classifier.
We tested all three interchangeable methods on several inventories with known triggers spread over the Japanese archipelago. To demonstrate the effectiveness of developed methods, we used two testing configurations.
The first configuration merges all the available data for the k-fold cross-validation, whereas the second configuration excludes one inventory during the training phase to use as the sole testing inventory.
Our geometric-feature-based method performs satisfactorily, with classification accuracies varying between 67 % and 92 %. We have introduced a more straightforward but data-intensive CNN alternative, as it inputs only landslide images without manual feature selection.
CNN eases the scripting process without losing classification accuracy. Using topological features from 3D landslides (extracted through TDA) in the RF classifier improves classification accuracy by 12 % on average.
TDA also requires less training data. However, the landscape autocorrelation could easily bias TDA-based classification. Finally, we implemented the three methods on an inventory without any triggering information to showcase a real-world application.
Riverine ecosystems provide various ecosystem services. One of these services is the biological control of eutrophication by grazing macroinvertebrates.
However, riverine ecosystems are subject to numerous stressors that affect community structure, functions, and stability properties. To manage rivers in response to these stressors, a better understanding of the ecological functions underlying services is needed.
This requires consideration of local and regional processes, which requires a metacommunity approach that links local food webs through drift and dispersal. This takes into account long-distance interactions that can compensate for local effects of stressors.
Our modular model MASTIFF (Multiple Aquatic STressors In Flowing Food webs) is stage-structured, spatially explicit, and includes coupled food webs consisting of benthic resource-consumer interactions between biofilm and three competing macroinvertebrate functional types. River segments are unidirectionally connected through organismal drift and bidirectionally connected through dispersal. Climate and land use stressors along the river can be accounted for. Biocontrol of biofilm eutrophication is used as an exemplary functional indicator.
We present the model and the underlying considerations, and show in an exemplary application that explicit consideration of drift and dispersal is essential for understanding the spatiotemporal biocontrol of eutrophication.
The combination of drift and dispersal reduced eutrophication events. While dispersal events were linked to specific periods in the species life cycles and therefore had limited potential to control, drift was ubiquitous and thus responded more readily to changing habitat conditions.
This indicates that drift is an important factor for coping with stress situations.
Finally, we outline and discuss the potential and possibilities of MASTIFF as a tool for mechanistic, cross-scale analyses of multiple stressors to advance knowledge of riverine ecosystem functioning.
Self-organized patterns in the actin cytoskeleton are essential for eukaryotic cellular life. They are the building blocks of many functional structures that often operate simultaneously to facilitate, for example, nutrient uptake and movement of cells. However, identifying how qualitatively distinct actin patterns can coexist remains a challenge.
Using bifurcation theory of a mass conserved activator-inhibitor system, we uncover a generic mechanism of how different actin waves-traveling waves and excitable pulses- organize and simultaneously emerge.
Live-cell imaging experiments indeed reveal that narrow, planar, and fast-moving excitable pulses may coexist with ring-shaped macropinocytic actin waves in the cortex of motile amoeboid cells.
Over the past years, NGS has become a crucial workhorse for open-view pathogen diagnostics.
Yet, long turnaround times result from using massively parallel high-throughput technologies as the analysis can only be performed after sequencing has finished. The interpretation of results can further be challenged by contaminations, clinically irrelevant sequences, and the sheer amount and complexity of the data.
We implemented PathoLive, a real-time diagnostics pipeline for the detection of pathogens from clinical samples hours before sequencing has finished.
Based on real-time alignment with HiLive2, mappings are scored with respect to common contaminations, low-entropy areas, and sequences of widespread, non-pathogenic organisms.
The results are visualized using an interactive taxonomic tree that provides an easily interpretable overview of the relevance of hits. For a human plasma sample that was spiked in vitro with six pathogenic viruses, all agents were clearly detected after only 40 of 200 sequencing cycles.
For a real-world sample from Sudan, the results correctly indicated the presence of Crimean-Congo hemorrhagic fever virus. In a second real-world dataset from the 2019 SARS-CoV-2 outbreak in Wuhan, we found the presence of a SARS coronavirus as the most relevant hit without the novel virus reference genome being included in the database.
For all samples, clinically irrelevant hits were correctly de-emphasized.
Our approach is valuable to obtain fast and accurate NGS-based pathogen identifications and correctly prioritize and visualize them based on their clinical significance: PathoLive is open source and available on GitLab and BioConda.
This joint experimental-theoretical work focuses on molecular and photophysical properties of the spiropyran-containing amphiphilic molecule in organic and aqueous solutions.
Being dissolved in tested organic solvents, the system demonstrates positive photochromism, i.e., upon UV stimulus the colorless spiropyran form is transformed into colorful merocyanine isomer.
However, the aqueous solution of the amphiphile possesses a negative photochromism: the orange-red merocyanine form becomes thermodynamically more stable in water, and both UV and vis stimuli lead to the partial or complete photobleaching of the solution.
The explanation of this phenomenon is given on the basis of density functional theory calculations and classical modeling including thermodynamic integration.
The simulations reveal that stabilization of merocyanine in water proceeds with the energy of ca. 70 kJ mol-1, and that the Helmholtz free energy of hydration of merocyanine form is 100 kJ mol-1 lower as compared to the behavior of SP isomer in water.
The explanation of such a difference lies in the molecular properties of the merocyanine: after ring-opening reaction this molecule transforms into a zwitterionic form, as evidenced by the electrostatic potential plotted around the opened form.
The presence of three charged groups on the periphery of a flat conjugated backbone stimulates the self-assembly of merocyanine molecules in water, ending up with the formation of elongated associates with stack-like building blocks, as shown in molecular dynamics simulations of the aqueous solution with the concentration above critical micelle concentration.
Our quantitative evaluation of the hydrophilicity switching in spiropyran/merocyanine containing surfactants may prompt the search for new systems, including colloidal and polymeric ones, aiming at remote tuning of their morphology, which could give new promising shapes and patterns for the needs of modern nanotechnology.
Noble metal nanostructures are known to confine photon energies to their dimensions with resonant oscillations of their conduction electrons, leading to the ultrahigh enhancement of electromagnetic fields in numerous spectroscopic methods.
Of all the possible plasmonic nanomaterials, silver offers the most intriguing properties, such as best field enhancements and tunable resonances in visible-to-near infrared regions.
This review highlights the recent developments in silver nanostructured substrates for plasmonic sensing with the main emphasis on surface plasmon resonance (SPR) and surface-enhanced Raman spectroscopy (SERS) over the past decade.
The main focus is on the synthesis of silver nanostructured substrates via physical vapor deposition and chemical synthesis routes and their applications in each sensing regime.
A comprehensive review of recent literature on various possible silver nanostructures prepared through these methodologies is discussed and critically reviewed for various planar and optical fiber-based substrates.
Origin and migration of fluoride in the area of the Aluto Volcanic Complex (Main Ethiopian Rift)
(2022)
Fluoride-enriched ground and surface waters represent a major health risk for the local population in many areas along the East African Rift.
The present study investigates the origin of fluoride and the reason for its accumulation in the rift waters, following two hypotheses: (i) fluid-rock-interactions release fluoride from minerals into the water and (ii) magmatic-derived fluoride-containing liquids and gases migrate along permeable fault zones until they dissolve in ground-and surface water or be released to the atmosphere.
Rock-, gas, water-, soil-, and plant samples were collected from the area within and close by the Aluto Volcanic Complex, which is part of the Main Ethiopian Rift. Most analyzed waters showed fluoride concentrations above the drinking water limit (> 1.5 mg/L) with the highest values in hot springs (up to 70 mg/L) and the geothermal well (76 mg/L).
In the solid phase, a high fluoride content was found in acid volcanic rocks (ignimbrite: 4391 ppm; rhyolite: 3248 ppm) as well as in pumice (up to 1955 ppm). The fluoride content of soil samples collected within the volcanic complex varied between 82 and 1036 ppm, whereas former lake sediments from outside the Aluto Volcanic Complex showed higher fluoride contents ranging from 674 to 8171 ppm. Identified fluoride-rich minerals are various amphiboles (about 3 wt.-% F-), fluor-apatite (about 3 wt % F-), minerals of the fluorcaphite group (about 5 wt.-% F-), parisite (up to 9 wt.-% F-), and fluorite (CaF2).
Elevated fluoride concentrations were also measured in some gas samples from fumaroles (up to 50 ppm) and in plant samples collected next to the fumaroles (up to 65 ppm). Leaching experiments of solid samples with deionized water demonstrated that fluoride can easily be mobilized from pumice and sediments but hardly from consolidated rocks.
This fluoride release increased with temperature (up to 150 C) and correlated roughly with dis-solved silica indicating the binding of some fluoride to the amorphous or weakly crystalline silica fraction. Based on these results it was concluded that fluoride migrates via different pathways through the environment: At the depth of the magma chamber during magmatic differentiation fluoride enriches initially in the magmatic melt and accumulates in some late-crystallizing minerals of igneous rocks such as fluorite or mica. Upon volcanic eruption fluoride is predominantly incorporated in the glass (ignimbrite) and ash phase (pumice).
On the surface, these rocks are exposed to weathering and fluoride leaches partly out into the aqueous phase. Soft and porous rocks such as pumice release fluoride first whereas hard extrusive/igneous rocks are less prone to weathering and retain the fluoride. Pumice and (lake) sediments might act both, as source and as sink for fluoride in the area.
Although some fluoride might drain from the surface into the deeper subsoil, we conclude that magmatic fluids (liquid and gas) contribute more substantially to the overall fluoride ground water content because (i) of the much higher fluoride content in deep geothermal waters and hot springs as compared to surface-near waters; (ii) active geothermal surface manifestations located along fault zones indicate that fluids migrate from deep magmatic intrusions (as gas and liquid) towards the surface, where fluoride dissolves in groundwater; (iii) and the good correlation between bicarbonate (deriving from dissolution of magmatic CO2) and fluoride content in all analyzed water samples.
Carbon suboxide (C3O2) is a unique molecule able to polymerize spontaneously into highly conjugated light-absorbing structures at temperatures as low as 0 degrees C. Despite obvious advantages, little is known about the nature and the functional properties of this carbonaceous material. In this work, the aim is to bring "red carbon," a forgotten polymeric semiconductor, back to the community's attention.
A solution polymerization process is adapted to simplify the synthesis and control the structure.
This allows one to obtain this crystalline covalent material at low temperatures. Both spectroscopic and elemental analyses support the chemical structure represented as conjugated ladder polypyrone ribbons.
Density functional theory calculations suggest a crystalline structure of AB stacks of polypyrone ribbons and identify the material as a direct bandgap semiconductor with a medium bandgap that is further confirmed by optical analysis.
The material shows promising photocatalytic performance using blue light.
Moreover, the simple condensation-aromatization route described here allows the straightforward fabrication of conjugated ladder polymers and can be inspiring for the synthesis of carbonaceous materials at low temperatures in general.
In this paper, we propose a revised fractional Brownian motion run with a nonlinear clock (fBm-nlc) model and utilize it to illustrate the microscopic mechanism analysis of the fractal derivative diffusion model with variable coefficient (VC-FDM).
The power-law mean squared displacement (MSD) links the fBm-nlc model and the VC-FDM via the two-parameter power law clock and the Hurst exponent is 0.5.
The MSD is verified by using the experimental points of the chloride ions diffusion in concrete.
When compared to the linear Brownian motion, the results show that the power law MSD of the fBm-nlc is much better in fitting the experimental points of chloride ions in concrete.
The fBm-nlc clearly interprets the VC-FDM and provides a microscopic strategy in characterizing different types of non-Fickian diffusion processes with more different nonlinear functions.
Paleogenomes reveal a complex evolutionary history of late Pleistocene bison in Northeastern China
(2022)
Steppe bison are a typical representative of the Mid-Late Pleistocene steppes of the northern hemisphere.
Despite the abundance of fossil remains, many questions related to their genetic diversity, population structure and dispersal route are still elusive.
Here, we present both near-complete and partial mitochondrial genomes, as well as a partial nuclear genome from fossil bison samples excavated from Late Pleistocene strata in northeastern China.
Maximum-likelihood and Bayesian trees both suggest the bison clade are divided into three maternal haplogroups (A, B and C), and Chinese individuals fall in two of them. Bayesian analysis shows that the split between haplogroup C and the ancestor of haplogroups A and B dates at 326 ky BP (95% HPD: 397-264 ky BP).
In addition, our nuclear phylogenomic tree also supports a basal position for the individual carrying haplogroup C. Admixture analyses suggest that CADG467 (haplogroup C) has a similar genetic structure to steppe bison from Siberia (haplogroup B).
Our new findings indicate that the genetic diversity of Pleistocene bison was probably even higher than previously thought and that northeastern Chinese populations of several mammalian species, including Pleistocene bison, were genetically distinct.
Forward stratigraphic modelling is a fast-developing modelling approach, used to test conceptual models, and predict stratigraphic architecture and depositional facies from basin to reservoir scales.
Published subsurface applications demonstrate its added value by integrating multidisciplinary data as well as geological concepts into its constraints.
When applied to carbonate depositional systems, composed of multiple sediment factories, the cooperating and interdependent production mechanisms remain poorly studied.
By applying the technique to a well-studied section of the Maldives carbonate platform, a specific model design-adapted to the geological age and setting, and constrained by available data-sheds light on the interaction of its carbonate producers.
The results yield a naturalistic depositional facies distribution and offer insight in the changing relationship between biotic communities during the platform evolution.
After calibration, the reference model unequivocally links the formerly proposed genetic model to the seismostratigraphic architecture.
Furthermore, the results show how environmental changes (seemingly of secondary impact compared to changes in physical accommodation in the stratigraphic record) can induce substantial fluctuations in carbonate production rates of biotic communities, affect the ecological accommodation, and thus impact the platform architecture. Therefore, it is crucial to treat carbonate production rates during periods of environmental change as variables with associated uncertainties in a forward stratigraphic model setup.
A special class of English words with tense vowel/diphthong nuclei and liquid codas receive variable syllable count judgments (one and over-one syllables).
Tilsen and Cohn (2016) showed that differences in judgments correlate with differences in production, supporting their hypothesis that meta-phonological judgments and speech motor control share a common representation.
In the present study, we further propose that syllable count judgments are related to subsegmental representation in the rime, and are independent of acoustic duration.
We test the hypothesis by comparing English and German, chosen for their similar word structures and vowel length contrast, and their crucial difference in the gestural specification of coda liquids.
In English, coda liquids have an earlier vocalic gesture relative to the consonantal one, while in German, both gestures are simultaneous.
We stipulated that sesquisyllabic (over-one) judgments are related to the count of sequentially-timed vocalic gestures in the rime. The difference in the coda liquid composition between the two languages predicts that sesquisyllables should not emerge in German.
Our predictions were confirmed by the results of parallel production (acoustic) and syllable count judgment experiments in English and German.
We propose a model accounting for these results, and we discuss its typological implications and its limitations.
Production and comprehension of prosodic boundary marking in persons with unilateral brain lesions
(2022)
Purpose: Persons with unilateral brain damage in the right hemisphere (RH) or left hemisphere (LH) show limitations in processing linguistic prosody, with yet inconclusive results on their ability to process prosodically marked structural boundaries for syntactic ambiguity resolution. We aimed at systematically investigating production and comprehension of three prosodic cues (f(0) range, final lengthening, and pause) at structural boundaries in coordinate sequences in participants with right hemisphere brain damage (RHDP) and participants with left hemisphere brain damage (LHDP). Method: Twenty RHDP and 15 LHDP participated in our study.
Comprehension experiment: Participants and a control group listened to coordinate name sequences with internal grouping by a prosodically marked structural boundary (grouped condition, e.g., "(Gabi und Leni) # und Nina") or without internal grouping (ungrouped condition, e.g., "Gabi und Leni und Nina") and had to identify the target condition. The strength and combinations of prosodic cues in the stimuli were manipulated.
Production experiment: Participants were asked to produce coordinate sequences in the two conditions (grouped, ungrouped) in two different tasks: a Reading Aloud and a Repetition experiment. Accuracy of participants' productions was subsequently assessed in a rating study and productions were analyzed with respect to use of prosodic cues.
Results: In the Comprehension experiment, RHDP and LHDP had overall lower identification accuracies than unimpaired control participants and LHDP were found to have particular problems with boundary identification when the pause cue was reduced. In production, LHDP and RHDP employed all three prosodic cues for boundary marking, but struggled to clearly mark prosodic boundaries in 28% of all productions. Both groups showed better performance in reading aloud than in repetition. LHDP relied more on using f(0) range and pause duration to prosodically mark structural boundaries, whereas RHDP employed final lengthening more vigorously than LHDP in reading aloud.
Conclusions: We conclude that processing of linguistic prosody is affected in RHDP and LHDP, but not completely impaired. Therefore, prosody can serve as a relevant communicative resource. However, it should also be considered as a target area for assessment and treatment in both groups.
The printability of artificial defects inside the additively manufactured laser powder bed fusion (LPBF) 316L stainless steel is investigated.
The printing parameters of the LPBF process are optimized to produce artificial defects with reproducible sizes at desired positions while minimizing redundant porosity. The smallest obtained artificial defect is 90 mu m in diameter.
The accuracy of the geometry of the printed defect depends on both the height and the diameter in the input model.
The effect of artificial defects on the very-high-cycle fatigue (VHCF) behavior of LPBF 316L stainless steel is also studied. The specimens printed with artificial defects in the center are tested under VHCF using an ultrasonic machine.
Crack initiation is accompanied by the formation of a fine granular area (FGA), typical of VHCF. Despite the presence of relatively large artificial defects, FGA formation is observed around accidental natural printing defects closer to the surface, which can still be considered as internal. The causes for this occurrence are discussed.
Plant cell walls are versatile materials that can adopt a wide range of mechanical properties through controlled deposition of cellulose fibrils. Wall integrity requires a sufficiently homogeneous fibril distribution to cope effectively with wall stresses. Additionally, specific conditions, such as the negative pressure in water transporting xylem vessels, may require more complex wall patterns, e.g., bands in protoxylem.
The orientation and patterning of cellulose fibrils are guided by dynamic cortical microtubules.
New microtubules are predominantly nucleated from parent microtubules causing positive feedback on local microtubule density with the potential to yield highly inhomogeneous patterns. Inhomogeneity indeed appears in all current cortical array simulations that include microtubule-based nucleation, suggesting that plant cells must possess an as-yet unknown balancing mechanism to prevent it.
Here, in a combined simulation and experimental approach, we show that a limited local recruitment of nucleation complexes to microtubules can counter the positive feedback, whereas local tubulin depletion cannot.
We observe that nucleation complexes preferentially appear at the plasma membrane near microtubules. By incorporating our experimental findings in stochastic simulations, we find that the spatial behavior of nucleation complexes delicately balances the positive feedback, such that differences in local microtubule dynamics-as in developing protoxylem-can quickly turn a homogeneous array into a banded one. Our results provide insight into how the plant cytoskeleton has evolved to meet diverse mechanical requirements and greatly increase the predictive power of computational cell biology studies.
Spacing repeated study phases across multiple sessions instead of studying and restudying the learning material in one session only is an effective strategy to promote lasting learning. However, most studies demonstrating the spacing effect were conducted in the laboratory, using simple verbal material. Learning in educational contexts differs regarding the complexity and coherence of the learning material and concerning the role of motivational and affective learner characteristics. Studies conducted in educational contexts suggest that the spacing effect is not as robust here. For example, acquiring mathematical skills or nonrepeated, consecutive information does not reliably benefit from spacing. After an overview of studies addressing the spacing effect in the laboratory and in educational contexts, we discuss various open questions that need to be addressed by future research before recommending spacing as a learning strategy to promote meaningful and lasting learning at schools and universities.
As society paves its way towards device miniaturization and precision medicine, microscale actuation and transport become increasingly prominent research fields with high impact in both technological and clinical contexts.
In order to accomplish movement of micron-sized objects towards specific target sites, active biohybrid transport systems, such as motile living cells that act as smart biochemically powered microcarriers, have been suggested as an alternative to synthetic microrobots.
Inspired by the motility of leukocytes, we propose the amoeboid crawling of eukaryotic cells as a promising mechanism for transport of micron-sized cargoes and present an in-depth study of this type of composite active matter.
Its transport properties result from the interactions of an active element (cell) and a passive one (cargo) and reveal an optimal cargo size that enhances the locomotion of the load-carrying cells, even exceeding their motility in the absence of cargo.
The experimental findings are rationalized in terms of a biohybrid active particle model that describes the emergent cell-cargo dynamics and enables us to derive the long-time diffusive transport of amoeboid microcarriers.
As amoeboid locomotion is commonly observed for mammalian cells such as leukocytes, our results lay the foundations for the study of transport performance of other medically relevant cell types and for extending our findings to more advanced transport tasks in complex environments, such as tissues.
This pre-registered study examined the prevalence and correlates of sexual aggression in a sample of 530 Iranians (322 women, 208 men) with a behaviorally specific questionnaire distinguishing between different coercive strategies, victim-perpetrator relationships, and sexual acts. Significantly more women (63.0%) than men (51.0%) experienced at least one incident of sexual aggression victimization since the age of 15 years, and significantly more men (37.0%) than women (13.4%) reported at least one incident of sexual aggression perpetration. In women and men, the experience of child sexual abuse predicted sexual victimization and sexual aggression perpetration after the age of 15 years, both directly and indirectly through higher engagement in risky sexual behavior. Greater endorsement of hostile masculinity among men explained additional variance in the prediction of sexual aggression perpetration. This research is a first step towards documenting and explaining high rates of sexual aggression victimization and perpetration among Iranian women and men, providing important information for sex education as well for the prevention of sexual aggression. However, to achieve these goals, we highlight the need for systematic actions in all educational, social, and legal sectors of Iranian society.
During a survey of aquatic fungi from Anzali Lagoon in Iran, several fungal specimens were isolated from freshwater habitats. Morphological evidence and comparing sequencing based on rDNA (ITS and LSU) and protein-coding genes (TEF1 and TUB2) showed that some isolates belong to undescribed fungal species.
These isolates belong to Arthrobotrys and Sarocladium, two ascomycetes genera. Arthrobotrys hyrcanus, sp. nov., differs from closely related species such as A. dianchiensis by its larger conidia and septation of primary conidia. Sarocladium pseudokiliense, sp. nov., was similar to S. kiliense, but distinguished by its conidial shape and the absence of adelophialides and chlamydospores.
Morphological descriptions, illustrations and multilocus phylogenetic analysis for both new species are provided.
Here, we establish different ways of light-triggered droplet manipulation such as reversible wetting, splitting, merging, and transport.
The unique features of our approach are that the changes in the wetting properties of microscopic droplets of isotropic (oil) or anisotropic (liquid crystalline) liquids adsorbed on photoswitchable films can be triggered just by application of soft optical stimuli, which lead to dynamical, reversible changes in the local morphology of the structured surfaces.
The adaptive films consist of an azobenzene-containing surfactant ionically attached to oppositely charged polymer chains. Under exposure to irradiation with light, the azobenzene photoisomerizes between two states, nonpolar trans -isomer and polar cis-isomer, resulting in the corresponding changes in the surface energy and orientation of the surfactant tails at the interface.
Additionally, the local increase in the surface temperature due to absorption of light by the azobenzene groups enables diverse processes of manipulation of the adsorbed small droplets, such as the reversible increase of the droplet basal area up to 5 times, anisotropic wetting during irradiation with modulated light, and precise partition of the droplet into many small pieces, which can then be merged on demand to the desired number of larger droplets.
Moreover, using a moving focused light spot, we experimentally demonstrate and theoretically explain the locomotion of the droplet over macroscopic distances with a velocity of up to 150 mu m center dot s-1.
Our findings could lead to the ultimate application of a programmable workbench for manipulating and operating an ensemble of droplets, just using simple and gentle optical stimuli.
Meropenem is one of the most frequently used antibiotics to treat life-threatening infections in critically ill patients.
This study aimed to develop a meropenem dosing algorithm for the treatment of Gram-negative infections based on intensive care unit (ICU)-specific resistance data. Antimicrobial susceptibility testing of Gram-negative bacteria obtained from critically ill patients was carried out from 2016 to 2020 at a tertiary care hospital.
Based on the observed MIC distribution, stochastic simulations (n = 1,000) of an evaluated pharmacokinetic meropenem model, and a defined pharmacokinetic/pharmacodynamic target (100%T->4xMIC while minimum concentrations were <44.5 mg/L), dosing recommendations for patients with varying renal function were derived.
Pathogen-specific MIC distributions were used to calculate the cumulative fraction of response (CFR), and the overall MIC distribution was used to calculate the local pathogen-independent mean fraction of response (LPIFR) for the investigated dosing regimens.
A CFR/LPIFR of >90% was considered adequate. The observed MIC distribution significantly differed from the EUCAST database. Based on the 6,520 MIC values included, a three-level dosing algorithm was developed.
If the pathogen causing the infection is unknown (level 1), known (level 2), known to be neither Pseudomonas aeruginosa nor Acinetobacrer baumannii, or classified as susceptible (level 3), a continuous infusion of 1.5 g daily reached sufficient target attainment independent of renal function.
In all other cases, dosing needs to be adjusted based on renal function. ICU-specific susceptibility data should be assessed regularly and integrated into dosing decisions. The presented workflow may serve as a blueprint for other antimicrobial settings.
Devising optimal interventions for constraining stochastic systems is a challenging endeavor that has to confront the interplay between randomness and dynamical nonlinearity.
Existing intervention methods that employ stochastic path sampling scale poorly with increasing system dimension and are slow to converge.
Here we propose a generally applicable and practically feasible methodology that computes the optimal interventions in a noniterative scheme.
We formulate the optimal dynamical adjustments in terms of deterministically sampled probability flows approximated by an interacting particle system.
Applied to several biologically inspired models, we demonstrate that our method provides the necessary optimal controls in settings with terminal, transient, or generalized collective state constraints and arbitrary system dynamics.
Unspecific peroxygenases (UPOs, EC 1.11.2.1) are fungal enzymes that catalyze the oxyfunctionalization of non-activated hydrocarbons, making them valuable biocatalysts. Despite the increasing interest in UPOs that has led to the identification of thousands of putative UPO genes, only a few of these have been successfully expressed and characterized.
There is currently no universal expression system in place to explore their full potential. Cell-free protein synthesis has proven to be a sophisticated technique for the synthesis of difficult-to-express proteins.
In this work, we aimed to establish an insect-based cell-free protein synthesis (CFPS) platform to produce UPOs. CFPS relies on translationally active cell lysates rather than living cells.
The system parameters can thus be directly manipulated without having to account for cell viability, thereby making it highly adaptable.
The insect-based lysate contains translocationally active, ER-derived vesicles, called microsomes.
These microsomes have been shown to allow efficient translocation of proteins into their lumen, promoting post-translational modifications such as disulfide bridge formation and N-glycosylations.
In this study the ability of a redox optimized, vesicle-based, eukaryotic CFPS system to synthesize functional UPOs was explored. The influence of different reaction parameters as well as the influence of translocation on enzyme activity was evaluated for a short UPO from Marasmius rotula and a long UPO from Agrocybe aegerita.
The capability of the CFPS system described here was demonstrated by the successful synthesis of a novel UPO from Podospora anserina, thus qualifying CFPS as a promising tool for the identification and evaluation of novel UPOs and variants thereof.
Quantifying the influence of pollen aging on the adhesive
properties of Hypochaeris radicata pollen
(2022)
Simple Summary Pollination is the transfer of pollen from a plant's male part (anther) to the corresponding female part (stigma). It is a fundamental biological process that ensures plant reproduction. Most studies investigate pollination from a biological perspective, but the underlying physical processes are poorly understood. Many plants rely on insects to transport pollen and the forces with which pollen adhere to insects and floral surfaces are fundamental for successful pollination.
We quantified pollen adhesion by measuring the forces necessary to detach Hypochaeris radicata (catsear, a common insect-pollinated plant) pollen from glass and studied for the first time how the adhesion forces change with pollen aging.
Our results show that newly formed adhesion bonds between H. radicata pollen and glass are stronger for fresh pollen than for old ones. On the other hand, when H. radicata pollen age in contact with glass, the adhesion between pollen and glass strengthens over time. These effects are probably caused by the viscous liquid covering most pollen (pollenkitt) changing its viscoelastic properties as it dries.
Although pollination is one of the most crucial biological processes that ensures plant reproduction, its mechanisms are poorly understood. Especially in insect-mediated pollination, a pollen undergoes several attachment and detachment cycles when being transferred from anther to insect and from insect to stigma. The influence of the properties of pollen, insect and floral surfaces on the adhesion forces that mediate pollen transfer have been poorly studied.
Here, we investigate the adhesive properties of Hypochaeris radicata pollen and their dependence on pollen aging by quantifying the pull-off forces from glass slides using centrifugation and atomic force microscopy. We found that the properties of the pollenkitt-the viscous, lipid liquid on the surface of most pollen grains-influences the forces necessary to detach a pollen from hydrophilic surfaces.
Our results show that aged H. radicata pollen form weaker adhesions to hydrophilic glass than fresh ones. On the other hand, when a pollen grain ages in contact with glass, the adhesion between the two surfaces increases over time.
This study shows for the first time the pollen aging effect on the pollination mechanism.
Volatile organic compounds (VOCs) are involved in microbial interspecies communication and in the mode of action of various antagonistic interactions. They are important for balancing host-microbe interactions and provide the basis for developing biological control strategies to control plant pathogens.
We studied the interactions between the bacterial antagonist Serratia plymuthica HRO-C48 and three fungal plant pathogens Rhizoctonia solani, Leptosphaeria maculans and Verticillium longisporum. Significant differences in fungal growth inhibition by the Serratia-emitted VOCs in pairwise dual culture assays and changes in the transcriptome of the bacterium and in the volatilomes of both interacting partners were observed. Even though the rate of fungal growth inhibition by Serratia was variable, the confrontation of the bacterium with the VOCs of all three fungi changed the levels of expression of the genes involved in stress response, biofilm formation, and the production of antimicrobial VOCs. Pairwise interacting microorganisms switched between defense (downregulation of gene expression) and attack (upregulation of gene expression and metabolism followed by growth inhibition of the interacting partner) modes, subject to the combinations of microorganisms that were interacting.
In the attack mode HRO-C48 significantly inhibited the growth of R. solani while simultaneously boosting its own metabolism; by contrast, its metabolism was downregulated when HRO-C48 went into a defense mode that was induced by the L. maculans and V. longisporum VOCs. L. maculans growth was slightly reduced by the one bacterial VOC methyl acetate that induced a strong downregulation of expression of genes involved in almost all metabolic functions in S. plymuthica.
Similarly, the interaction between S. plymuthica and V. longisporum resulted in an insignificant growth reduction of the fungus and repressed the rate of bacterial metabolism on the transcriptional level, accompanied by an intense volatile dialogue. Overall, our results indicate that VOCs substantially contribute to the highly break species-specific interactions between pathogens and their natural antagonists and thus deserving of increased consideration for pathogen control.
Floodplain wetlands are critical for sustaining various ecological and hydrological functions in a riverine environment. Severe anthropogenic alterations and human occupation of floodplains have threatened these wetlands in several parts of the world. A major handicap in designing sustainable restoration and monitoring strategies for these wetlands is the lack of scientific process-based understanding and information on the basin-scale controls of their degradation. Here, we offer a novel approach to integrate the connectivity of the wetlands with the surrounding landscape along with other attributes such as stream density, hydrometeorological parameters, and groundwater dynamics to explain their degradation and then to prioritise them for restoration and monitoring.
We hypothesise that the best possible connectivity scenario for the existence of a wetland would be if (a) the wetland has a high connectivity with its upslope area, and (b) the wetland has a low connectivity with its downslope region.
The first condition ensures the flow of water into the wetland and the second condition allows longer water residence time in the wetland. Accordingly, we define four connectivity-based wetland health scenarios-good, no impact, bad, and worst.
We have implemented the proposed method in 3226 wetlands in the Ramganga Basin in north India. Further, we have applied specific selection criteria, such as distance from the nearest stream and stream density, to prioritise the wetlands for restoration and monitoring.
We conclude that the connectivity analysis offers a quick process-based assessment of wetlands' health status and serves as an important criterion to prioritise the wetlands for developing appropriate management strategies.
We consider the case of scattering by several obstacles in Rd for d ≥ 2.
In this setting, the absolutely continuous part of the Laplace operator Δ with Dirichlet boundary conditions and the free Laplace operator Δ0 are unitarily equivalent.
For suitable functions that decay sufficiently fast, we have that the difference g(Δ) - g(Δ0) is a trace-class operator and its trace is described by the Krein spectral shift function.
In this article, we study the contribution to the trace (and hence the Krein spectral shift function) that arises from assembling several obstacles relative to a setting where the obstacles are completely separated. In the case of two obstacles, we consider the Laplace operators Δ1 and Δ2 obtained by imposing Dirichlet boundary conditions only on one of the objects.
Our main result in this case states that then g(Δ) - g(Δ1) - g(Δ2) C g(Δ0) is a trace-class operator for a much larger class of functions (including functions of polynomial growth) and that this trace may still be computed by a modification of the Birman–Krein formula. In case g(x) D x 2 , 1 the relative trace has a physical meaning as the vacuum energy of the massless scalar field and is expressible as an integral involving boundary layer operators.
Such integrals have been derived in the physics literature using nonrigorous path integral derivations and our formula provides both a rigorous justification as well as a generalization.
Dark field scattering microscopy can create large hyperspectral data sets that contain a wealth of information on the properties and the molecular environment of noble metal nanoparticles.
For a quick screening of samples of microscopic dimensions that contain many different types of plasmonic nanostructures, we propose a multivariate analysis of data sets of thousands to several hundreds of thousands of scattering spectra.
By using non-negative matrix factorization for decomposing the spectra, components are identified that represent individual plasmon resonances and relative contributions of these resonances to particular microscopic focal volumes in the mapping data sets. Using data from silver and gold nanoparticles in the presence of different molecules, including gold nanoparticle-protein agglomerates or silver nanoparticles forming aggregates in the presence of acrylamide, plasmonic properties are observed that differ from those of the original nanoparticles.
For the case of acrylamide, we show that the plasmon resonances of the silver nanoparticles are ideally suited to support surface enhanced Raman scattering (SERS) and the two-photon excited process of surface enhanced hyper Raman scattering (SEHRS). Both vibrational tools give complementary information on the in situ formed polyacrylamide and the molecular composition at the nanoparticle surface.
Despite faster-than-expected progress in clean energy technology deployment, global annual CO2 emissions have increased from 2020 to 2023. The feasibility of limiting warming to 1.5 °C is therefore questioned. Here we present a model intercomparison study that accounts for emissions trends until 2023 and compares cost-effective scenarios to alternative scenarios with institutional, geophysical and technological feasibility constraints and enablers informed by previous literature. Our results show that the most ambitious mitigation trajectories with updated climate information still manage to limit peak warming to below 1.6 °C (‘low overshoot’) with around 50% likelihood. However, feasibility constraints, especially in the institutional dimension, decrease this maximum likelihood considerably to 5–45%. Accelerated energy demand transformation can reduce costs for staying below 2 °C but have only a limited impact on further increasing the likelihood of limiting warming to 1.6 °C. Our study helps to establish a new benchmark of mitigation scenarios that goes beyond the dominant cost-effective scenario design.
This research demonstrated the application of hydrochemical data and stable water isotopes of delta O-18 and delta D (or delta 2H) for evaluating the relationship between surface water in Lake Bosumtwi and the underlying groundwater system.
It aimed at determining the presence or absence of a hydraulic relationship and for evaluating the possible direction of flow at the interface between the two reservoirs. The study also estimated evaporative losses of infiltrating rainwater as it transits the unsaturated zone and provided important information on the hydrological processes prevailing in the area.
The results of Q-Mode hierarchical cluster analysis (HCA) clearly differentiate the lake water from the groundwater based on their spatial relationship.
These results indicated that groundwater recharge occurs on the hilltops of the crater, where it is slightly acidic with low levels of dissolved ions, characterised by short residence time and rapid unrestricted vertical infiltration and recharge.
The groundwater becomes more mineralized with longer contact times and deeper circulation with the host rock, while it flows from the recharge areas towards the lake at lower elevations.
Analyses of delta O-18 and delta D showed a high evaporation rate on the lake surface (90%) with a significant evaporative enrichment, whereas groundwater showed no significant isotopic variations.
Thus suggesting that the aquifers have been recharged by recent meteoric water that has undergone some evaporative enrichment since the study established an evaporation rate of water infiltrating the unsaturated zone ranging from 54 to 60%. Both reservoirs do not appear to be hydraulically connected, and where such a connection exists, it is expected to favour the lake.
Enzymatic hydrolysis holds great promise for plastic waste recycling and upcycling.
The interfacial catalysis mode, and the variability of polymer specimen properties under different degradation conditions, add to the complexity and difficulty of understanding polymer cleavage and engineering better biocatalysts.
We present a systemic approach to studying the enzyme-catalyzed surface erosion of poly(ethylene terephthalate) (PET) while monitoring/controlling operating conditions in real time with simultaneous detection of mass loss and changes in viscoelastic behavior.
PET nanofilms placed on water showed a porous morphology and a thicknessdependent glass transition temperature (T-g) between 40 degrees C and 44 degrees C, which is >20 degrees C lower than the T-g of bulk amorphous PET.
Hydrolysis by a dual-enzyme system containing thermostabilized variants of Ideonella sakaiensis PETase and MHETase resulted in a maximum depolymerization of 70% in 1 h at 50 degrees C.
We demonstrate that increased accessible surface area, amorphization, and T-g reduction speed up PET degradation while simultaneously lowering the threshold for degradation-induced crystallization.
In this increasingly data-rich world, visual recordings of human behavior are often unable to be shared due to concerns about privacy.
Consequently, data sharing in fields such as behavioral science, multimodal communication, and human movement research is often limited.
In addition, in legal and other non-scientific contexts, privacy-related concerns may preclude the sharing of video recordings and thus remove the rich multimodal context that humans recruit to communicate.
Minimizing the risk of identity exposure while preserving critical behavioral information would maximize utility of public resources (e.g., research grants) and time invested in audio-visual research.
Here we present an open-source computer vision tool that masks the identities of humans while maintaining rich information about communicative body movements. Furthermore, this masking tool can be easily applied to many videos, leveraging computational tools to augment the reproducibility and accessibility of behavioral research.
The tool is designed for researchers and practitioners engaged in kinematic and affective research. Application areas include teaching/education, communication and human movement research, CCTV, and legal contexts.
Ciliates represent a crucial link between phytoplankton and bacteria and mesozooplankton in pelagic food webs, but little is known about the processes influencing the dynamics of individual species.
Using long-term, high-frequency observations, we compared the diversity and the temporal variability in biomass and species composition of the ciliate community in large, deep, mesotrophic Lake Constance to that of the phytoplankton and rotifer communities in the same lake.
Furthermore, we used boosted regression trees to evaluate possible environmental predictors (temperature, three prey groups, four predator/competitor groups) influencing ciliate net growth.
The biomass of all ciliate species showed a common, recurrent seasonal pattern, often with peaks in spring and summer.
The ciliate community was more diverse than the rotifer community, exhibited highly synchronous dynamics and its species were regularly encountered during the season. The top-down control by copepods likely contributes to the ciliates' synchronized decline prior to the clear-water phase when food concentration is still high.
The high temporal autocorrelation of the ciliate biomasses together with the inter-annual recurrent seasonal patterns and the low explanatory power of the environmental predictors suggest that the dynamics of individual ciliate species are strictly controlled, yet it remains difficult to determine the responsible factors.
Objective:
Hypertension has long been recognized as one of the most important predisposing factors for cardiovascular diseases and mortality.
In recent years, machine learning methods have shown potential in diagnostic and predictive approaches in chronic diseases.
Electronic health records (EHRs) have emerged as a reliable source of longitudinal data. The aim of this study is to predict the onset of hypertension using modern deep learning (DL) architectures, specifically long short-term memory (LSTM) networks, and longitudinal EHRs.
Materials and Methods:
We compare this approach to the best performing models reported from previous works, particularly XGboost, applied to aggregated features.
Our work is based on data from 233 895 adult patients from a large health system in the United States. We divided our population into 2 distinct longitudinal datasets based on the diagnosis date.
To ensure generalization to unseen data, we trained our models on the first dataset (dataset A "train and validation") using cross-validation, and then applied the models to a second dataset (dataset B "test") to assess their performance.
We also experimented with 2 different time-windows before the onset of hypertension and evaluated the impact on model performance.
Results:
With the LSTM network, we were able to achieve an area under the receiver operating characteristic curve value of 0.98 in the "train and validation" dataset A and 0.94 in the "test" dataset B for a prediction time window of 1 year. Lipid disorders, type 2 diabetes, and renal disorders are found to be associated with incident hypertension.
Conclusion:
These findings show that DL models based on temporal EHR data can improve the identification of patients at high risk of hypertension and corresponding driving factors. In the long term, this work may support identifying individuals who are at high risk for developing hypertension and facilitate earlier intervention to prevent the future development of hypertension.
Our original target article highlighted some significant shortcomings in the current state of child language research: a large skew in our evidential base towards English and a handful of other Indo-European languages that partly has its origins in a lack of researcher diversity.
In this article, we respond to the 21 commentaries on our original article.
The commentaries highlighted both the importance of attention to typological features of languages and the environments and contexts in which languages are acquired, with many commentators providing concrete suggestions on how we address the data skew.
In this response, we synthesise the main themes of the commentaries and make suggestions for how the field can move towards both improving data coverage and opening up to traditionally under-represented researchers.
The mechanisms underlying increased dual-task costs in the comparison of modality compatible stimulus -response mappings (e.g., visual-manual, auditory-vocal) and modality incompatible mappings (e.g., visual -vocal, auditory-manual) remain elusive.
To investigate whether additional control mechanisms are at work in simultaneously processing two modality incompatible mappings, we applied a transfer logic between both types of dual-task mappings in the context of a mental fatigue induction.
We expected an increase in dual-task costs for both modality mappings after a fatigue induction with modality compatible tasks. In contrast, we expected an additional, selective increase in modality incompatible dual-task costs after a fatigue induction with modality incompatible tasks.
We tested a group of 45young individuals (19-30 years) in an online pre-post design, in which participants were assigned to one of three groups. The two fatigue groups completed a 90-min time-on -task intervention with a dual task comprising either compatible or incompatible modality mappings.
The third group paused for 90 min as a passive control group. Pre and post-session contained single and dual tasks in both modality mappings for all participants. In addition to behavioral performance measurements, seven subjective items (effort, focus, subjective fatigue, motivation, frustration, mental and physical capacity) were analyzed.
Mean dual-task performance during and after the intervention indicated a practice effect instead of the presumed fatigue effect for all three groups. The modality incompatible intervention group showed a selective performance improvement for the modality incompatible mapping but no transfer to the modality compatible dual task. In contrast, the compatible intervention group showed moderately improved performance in both modality map-pings.
Still, participants reported increased subjective fatigue and reduced motivation after the fatigue inter-vention.
This dynamic interplay of training and fatigue effects suggests that high control demands were involved in the prolonged performance of a modality incompatible dual task, which are separable from modality compatible dual-task demands.
Hyperbolic random graphs (HRGs) and geometric inhomogeneous random graphs (GIRGs) are two similar generative network models that were designed to resemble complex real-world networks.
In particular, they have a power-law degree distribution with controllable exponent beta and high clustering that can be controlled via the temperature T.
We present the first implementation of an efficient GIRG generator running in expected linear time.
Besides varying temperatures, it also supports underlying geometries of higher dimensions. It is capable of generating graphs with ten million edges in under a second on commodity hardware. The algorithm can be adapted to HRGs.
Our resulting implementation is the fastest sequential HRG generator, despite the fact that we support non-zero temperatures. Though non-zero temperatures are crucial for many applications, most existing generators are restricted to T = 0 .
We also support parallelization, although this is not the focus of this paper.
Moreover, we note that our generators draw from the correct probability distribution, that is, they involve no approximation.
Besides the generators themselves, we also provide an efficient algorithm to determine the non-trivial dependency between the average degree of the resulting graph and the input parameters of the GIRG model.
This makes it possible to specify the desired expected average degree as input. Moreover, we investigate the differences between HRGs and GIRGs, shedding new light on the nature of the relation between the two models. Although HRGs represent, in a certain sense, a special case of the GIRG model, we find that a straightforward inclusion does not hold in practice.
However, the difference is negligible for most use cases.
Hepatobiliary involvement is a hallmark in cystic fibrosis (CF), as the causative CF Transmembrane Conductance Regulator (CFTR) defect is expressed in the biliary tree. However, bile acid (BA) compositions in regard to pancreatic insufficiency, which is present at an early stage in about 85% of CF patients, have not been satisfactorily understood.
We assess the pattern of serum BAs in people with CF (pwCF) without CFTR modulator therapy in regard to pancreatic insufficiency and the CFTR genotype.
In 47 pwCF, 10 free and 12 taurine- and glycine-conjugated BAs in serum were prospectively assessed.
Findings were related to genotype, pancreatic insufficiency prevalence (PIP)-score, and hepatic involvement indicated by serum liver enzymes, as well as clinical and ultrasound criteria for CF-related liver disease.
Serum concentrations of total primary BAs and free cholic acid (CA) were significantly higher in pwCF with higher PIP-scores (p = 0.025, p = 0.009, respectively). Higher total BAs were seen in pwCF with PIP-scores >= 0.88 (p = 0.033) and with pancreatic insufficiency (p = 0.034).
Free CA was higher in patients with CF-related liver involvement without cirrhosis, compared to pwCF without liver disease (2.3-fold, p = 0.036). pwCF with severe CFTR genotypes, as assessed by the PIP-score, reveals more toxic BA compositions in serum. Subsequent studies assessing changes in BA homeostasis during new highly effective CFTR-modulating therapies are of high interest.
Hybrid nanophotonic elements, fabricated by organic and inorganic materials, are going to be key components of modern devices.
Coupled systems of photoemitters with a plasmonic waveguide serve the demand for nanoscopic frequency converters.
However, processes like the degradation of the photoemitters via photobleaching occur and need to be monitored and controlled, to realize future successful devices.
We introduce a hybrid perylene-diimide / silver nanowire as plasmon frequency converter. A versatile method is presented to monitor and analyze the bleaching process. It is based on a time series of photoluminescence images, during the operation of a single converter.
An analytical model is applied on the data and unveils that the photobleaching rate is constant and independent of the operation of the plasmon converter.
A circular, single-contig Methanobacterium sp. metagenome-assembled genome (MAG) was recovered from high-CO2 enrichments inoculated with drill core material from the tectonic Eger Rift terrestrial subsurface.
Annotation of the recovered MAG highlighted putative methanogenesis genes, providing valuable information on archaeal activity in the deep biosphere.
Refractive index provides fundamental insights into the electronic structure of materials. At high pressure, however, the determination of refractive index and its wavelength dispersion is challenging, which limits our understanding of how physical properties of even simple materials, such as MgO, evolve with pressure.
Here, we report on the measurement of room-temperature refractive index of MgO up to similar to 140 GPa.
The refractive index of MgO at 600 nm decreases by similar to 2.4% from similar to 1.737 at 1 atm to similar to 1.696 (+/- 0.017) at similar to 140 GPa.
Despite the index at 600 nm is essentially pressure independent, the absolute wavelength dispersion of the refractive index at 550-870 nm decreases by similar to 28% from similar to 0.015 at 1 atm to similar to 0.011 (+/- 8.04 x 10(-4)) at similar to 103 GPa.
Single-effective-oscillator analysis of our refractive index data suggests that the bandgap of MgO increases by similar to 1.1 eV from 7.4 eV at 1 atm to similar to 8.5 (+/- 0.6) eV at similar to 103 GPa.
We have investigated the self-assembly of the graphene nanoribbon molecular precursor 10,10'-dibromo-9,9'-bianthryl (DBBA) on Au(111) with frequency modulation scanning force microscopy (FM-SFM) at room temperature combined with ab initio calculations.
For low molecular coverages, the molecules aggregate along the substrate herringbone reconstruction main directions while remaining mobile.
At intermediate coverage, two phases coexist, zigzag stripes of monomer chains and decorated herringbones. For high coverage, the molecules assemble in a dimer-striped phase.
The adsorption behaviour of DBBA molecules and their interactions are discussed and compared with the results from ab initio calculations.
The Gram-negative bacterium Paenalcaligenes niemegkensis NGK35(T) was isolated from plastic debris in an abandoned landfill.
It has the ability to grow on polyethylene and hexadecane as the sole carbon sources. Here, we report the corresponding draft genome, which contains 3.66 Mbp and is characterized by a G+C content of 52.1%.
International migration patterns, at the global level, can to a large extent be explained through economic factors in origin and destination countries.
On the other hand, it has been shown that global climate change is likely to affect economic development over the coming decades.
Here, we demonstrate how these future climate impacts on national income levels could alter the global migration landscape.
Using an empirically calibrated global migration model, we investigate two separate mechanisms. The first is through destination-country income, which has been shown consistently to have a positive effect on immigration.
As countries' income levels relative to each other are projected to change in the future both due to different rates of economic growth and due to different levels of climate change impacts, the relative distribution of immigration across destination countries also changes as a result, all else being equal.
Second, emigration rates have been found to have a complex, inverted U-shaped dependence on origin-country income.
Given the available migration flow data, it is unclear whether this dependence-found in spatio-temporal panel data-also pertains to changes in a given migration flow over time. If it does, then climate change will additionally affect migration patterns through origin countries' emigration rates, as the relative and absolute positions of countries on the migration "hump" change.
We illustrate these different possibilities, and the corresponding effects of 3 degrees C global warming (above pre-industrial) on global migration patterns, using climate model projections and two different methods for estimating climate change effects on macroeconomic development.
Teacher collaboration is an important feature of job satisfaction and self-efficacy for teachers.
Moreover, the collaboration of teachers is important for adopting professional changes as professional development (PD) activities that include opportunities for collaboration have been shown to support teachers in improving classroom practice.
This may even lead to higher student performance.
Situated in the context of the Advanced Placement (AP) reform in the United States, we investigated the perceived importance of opportunities to collaborate with colleagues as a rationale to participate in PD (N = 3,725 teachers).
The opportunity to collaborate with colleagues was a primary rationale why teachers selected PD activities.
While this rationale is only slightly related to school and teacher characteristics, it was related to PD characteristics.
Specifically, opportunities to collaborate with colleagues were important to teachers in selecting informal face-to-face (FtF) PD activities.
We conclude that collaborative structures benefit all forms of teacher professional development.
We present the extension of the Kalmag model, proposed as a candidate for IGRF-13, to the twentieth century.
The dataset serving its derivation has been complemented by new measurements coming from satellites, ground-based observatories and land, marine and airborne surveys.
As its predecessor, this version is derived from a combination of a Kalman filter and a smoothing algorithm, providing mean models and associated uncertainties. These quantities permit a precise estimation of locations where mean solutions can be considered as reliable or not.
The temporal resolution of the core field and the secular variation was set to 0.1 year over the 122 years the model is spanning.
Nevertheless, it can be shown through ensembles a posteriori sampled, that this resolution can be effectively achieved only by a limited amount of spatial scales and during certain time periods.
Unsurprisingly, highest accuracy in both space and time of the core field and the secular variation is achieved during the CHAMP and Swarm era. In this version of Kalmag, a particular effort was made for resolving the small-scale lithospheric field.
Under specific statistical assumptions, the latter was modeled up to spherical harmonic degree and order 1000, and signal from both satellite and survey measurements contributed to its development.
External and induced fields were jointly estimated with the rest of the model. We show that their large scales could be accurately extracted from direct measurements whenever the latter exhibit a sufficiently high temporal coverage.
Temporally resolving these fields down to 3 hours during the CHAMP and Swarm missions, gave us access to the link between induced and magnetospheric fields. In particular, the period dependence of the driving signal on the induced one could be directly observed.
The model is available through various physical and statistical quantities on a dedicated website at https://ionocovar.agnld.uni-potsdam.de/Kalmag/.
The diffusion process of water in swelling (expansive) soil often deviates from normal Fick diffusion and belongs to anomalous diffusion.
The process of water adsorption by swelling soil often changes with time, in which the microstructure evolves with time and the absorption rate changes along a fractal dimension gradient function.
Thus, based on the material coordinate theory, this paper proposes a variable order derivative fractal model to describe the cumulative adsorption of water in the expansive soil, and the variable order is time dependent linearly.
The cumulative adsorption is a power law function of the anomalous sorptivity, and patterns of the variable order.
The variable-order fractal derivative model is tested to describe the cumulative adsorption in chernozemic surface soil, Wunnamurra clay and sandy loam.
The results show that the fractal derivative model with linearly time dependent variable-order has much better accuracy than the fractal derivative model with a constant derivative order and the integer order model in the application cases.
The derivative order can be used to distinguish the evolution of the anomalous adsorption process. The variable-order fractal derivative model can serve as an alternative approach to describe water anomalous adsorption in swelling soil.