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Environmental monitoring involves the quantification of microscopic cells and particles such as algae, plant cells, pollen, or fungal spores. Traditional methods using conventional microscopy require expert knowledge, are time-intensive and not well-suited for automated high throughput. Multispectral imaging flow cytometry (MIFC) allows measurement of up to 5000 particles per second from a fluid suspension and can simultaneously capture up to 12 images of every single particle for brightfield and different spectral ranges, with up to 60x magnification. The high throughput of MIFC has high potential for increasing the amount and accuracy of environmental monitoring, such as for plant-pollinator interactions, fossil samples, air, water or food quality that currently rely on manual microscopic methods. Automated recognition of particles and cells is also possible, when MIFC is combined with deep-learning computational techniques. Furthermore, various fluorescence dyes can be used to stain specific parts of the cell to highlight physiological and chemical features including: vitality of pollen or algae, allergen content of individual pollen, surface chemical composition (carbohydrate coating) of cells, DNA- or enzyme-activity staining. Here, we outline the great potential for MIFC in environmental research for a variety of research fields and focal organisms. In addition, we provide best practice recommendations.
The immense advances in computer power achieved in the last decades have had a significant impact in Earth science, providing valuable research outputs that allow the simulation of complex natural processes and systems, and generating improved forecasts. The development and implementation of innovative geoscientific software is currently evolving towards a sustainable and efficient development by integrating models of different aspects of the Earth system. This will set the foundation for a future digital twin of the Earth. The codification and update of this software require great effort from research groups and therefore, it needs to be preserved for its reuse by future generations of geoscientists. Here, we report on Geo-Soft-CoRe, a Geoscientific Software & Code Repository, hosted at the archive DIGITAL.CSIC. This is an open source, multidisciplinary and multiscale collection of software and code developed to analyze different aspects of the Earth system, encompassing tools to: 1) analyze climate variability; 2) assess hazards, and 3) characterize the structure and dynamics of the solid Earth. Due to the broad range of applications of these software packages, this collection is useful not only for basic research in Earth science, but also for applied research and educational purposes, reducing the gap between the geosciences and the society. By providing each software and code with a permanent identifier (DOI), we ensure its self-sustainability and accomplish the FAIR (Findable, Accessible, Interoperable and Reusable) principles. Therefore, we aim for a more transparent science, transferring knowledge in an easier way to the geoscience community, and encouraging an integrated use of computational infrastructure.
Crop model intercomparison studies have mostly focused on the assessment of predictive capabilities for crop development using weather and basic soil data from the same location. Still challenging is the model performance when considering complex interrelations between soil and crop dynamics under a changing climate. The objective of this study was to test the agronomic crop and environmental flux-related performance of a set of crop models. The aim was to predict weighing lysimeter-based crop (i.e., agronomic) and water-related flux or state data (i.e., environmental) obtained for the same soil monoliths that were taken from their original environment and translocated to regions with different climatic conditions, after model calibration at the original site. Eleven models were deployed in the study. The lysimeter data (2014-2018) were from the Dedelow (Dd), Bad Lauchstadt (BL), and Selhausen (Se) sites of the TERENO (TERrestrial ENvironmental Observatories) SOILCan network. Soil monoliths from Dd were transferred to the drier and warmer BL site and the wetter and warmer Se site, which allowed a comparison of similar soil and crop under varying climatic conditions. The model parameters were calibrated using an identical set of crop- and soil-related data from Dd. Environmental fluxes and crop growth of Dd soil were predicted for conditions at BL and Se sites using the calibrated models. The comparison of predicted and measured data of Dd lysimeters at BL and Se revealed differences among models. At site BL, the crop models predicted agronomic and environmental components similarly well. Model performance values indicate that the environmental components at site Se were better predicted than agronomic ones. The multi-model mean was for most observations the better predictor compared with those of individual models. For Se site conditions, crop models failed to predict site-specific crop development indicating that climatic conditions (i.e., heat stress) were outside the range of variation in the data sets considered for model calibration. For improving predictive ability of crop models (i.e., productivity and fluxes), more attention should be paid to soil-related data (i.e., water fluxes and system states) when simulating soil-crop-climate interrelations in changing climatic conditions.
Metabolic alterations precede cardiometabolic disease onset. Here we present ceramide- and dihydroceramide-profiling data from a nested case-cohort (type 2 diabetes [T2D, n = 775]; cardiovascular disease [CVD, n = 551]; random subcohort [n = 1137]) in the prospective EPIC-Potsdam study. We apply the novel NetCoupler-algorithm to link a data-driven (dihydro)ceramide network to T2D and CVD risk. Controlling for confounding by other (dihydro)ceramides, ceramides C18:0 and C22:0 and dihydroceramides C20:0 and C22:2 are associated with higher and ceramide C20:0 and dihydroceramide C26:1 with lower T2D risk. Ceramide C16:0 and dihydroceramide C22:2 are associated with higher CVD risk. Genome-wide association studies and Mendelian randomization analyses support a role of ceramide C22:0 in T2D etiology. Our results also suggest that (dh)ceramides partly mediate the putative adverse effect of high red meat consumption and benefits of coffee consumption on T2D risk. Thus, (dihydro)ceramides may play a critical role in linking genetic predisposition and dietary habits to cardiometabolic disease risk.
“Ick bin een Berlina”
(2024)
Background: Robots are increasingly used as interaction partners with humans. Social robots are designed to follow expected behavioral norms when engaging with humans and are available with different voices and even accents. Some studies suggest that people prefer robots to speak in the user’s dialect, while others indicate a preference for different dialects.
Methods: Our study examined the impact of the Berlin dialect on perceived trustworthiness and competence of a robot. One hundred and twenty German native speakers (Mage = 32 years, SD = 12 years) watched an online video featuring a NAO robot speaking either in the Berlin dialect or standard German and assessed its trustworthiness and competence.
Results: We found a positive relationship between participants’ self-reported Berlin dialect proficiency and trustworthiness in the dialect-speaking robot. Only when controlled for demographic factors, there was a positive association between participants’ dialect proficiency, dialect performance and their assessment of robot’s competence for the standard German-speaking robot. Participants’ age, gender, length of residency in Berlin, and device used to respond also influenced assessments. Finally, the robot’s competence positively predicted its trustworthiness.
Discussion: Our results inform the design of social robots and emphasize the importance of device control in online experiments.
Germany’s relatively stable party system faces a new left-authoritarian challenger: Sahra Wagenknecht’s Bündnis Sahra Wagenknecht (BSW) party. First polls indicate that for the BSW, election results above 10% are within reach. While Wagenknecht’s positions in economic and cultural terms have already been discussed, this article elaborates on another highly relevant feature of Wagenknecht, namely her populist communication. Exploring Wagenknecht’s and BSW’s populist appeal helps us to understand why the party is said to also have potential among seemingly different voter groups coming from the far right Alternative for Germany (AfD) and far left Die Linke, which share high levels of populist attitudes. To analyse the role that populist communication plays for Wagenknecht and the BSW, this article combines quantitative and qualitative methods. The quantitative analysis covers all speeches (10,000) and press releases (19,000) published by Die Linke members of Parliament (MPs; 2005–2023). The results show that Wagenknecht is the (former) Die Linke MP with the highest share of populist communication. Furthermore, she was also able to convince a group of populist MPs to join the BSW. The article closes with a qualitative analysis of BSW’s manifesto that reveals how populist framing plays a major role in this document, in which the political and economic elites are accused of working against the interest of “the majority”. Based on this analysis, the classification of the BSW as a populist party seems to be appropriate.
We use worldwide gridded satellite data to analyse how population size and density affect urban PM 2.5 pollution. We find that more populated and denser grid cells are more exposed to pollution. However, across urban areas, exposure increases with cities’ population size but decreases with density. Moreover, the population effect is driven mostly by population commuting to core cities rather than the core city population itself. We analyse heterogeneity by geography and income levels. A counterfactual simulation shows that exposure could fall by up to 40% if population size were equalized across all cities within countries, but the relocation of population from large to small cities that maximizes welfare would be small.
The Final-over-Final Condition has emerged as a robust and explanatory generalization for a wide range of phenomena (Biberauer, Holmberg, and Roberts 2014, Sheehan et al. 2017).
In this article, we argue that it also holds in another domain, nominalization.
In languages that show overt nominalization of VPs, one word order is routinely unattested, namely, a head-initial VP with a suffixal nominalizer.
This typological gap can be accounted for by the Final-over-Final Condition, if we allow it to hold within mixed extended projections.
This view also makes correct predictions about agentive nominalizations and nominalized serial verb constructions.
Motivational profiles across domains and academic choices within Eccles et al.’s situated expectancy
(2021)
This longitudinal person-centered study aimed to identify profiles of subjective task values and ability self-concepts of adolescents in the domain of mathematics, English, biology, and physics in Grades 10 and 12. We were interested in gendered changes of profile membership, and in relations between profile membership and educational and occupational outcomes in adulthood. Data were drawn from the Michigan Study of Adolescent and Adult Life Transitions. We focused on students who participated in the data collection in Grades 10 and 12 (N = 911; 56.1% female; M-age = 16.49, SD = .63; 91.2% European American, 4.6% African American, and 2.1% other ethnic groups such as Hispanic, Asian, Native American). Data on subsequent college majors were assessed 2, 6, and 10 years after finishing high school and data on occupational outcomes was assessed up to 22 years after high school. Using Latent Profile Analyses, our findings revealed five profiles in grade 10 and four profiles in grade 12, which were meaningfully related to student gender. Latent Transition Analyses showed that motivational beliefs became more hierarchical over time. Gendered changes in profile membership occurred, with boys experiencing a process of specialization into mathematics domains. We were also able to show that gender-specific intraindividual hierarchies of motivational beliefs were related to gender-specific specialization processes in adolescence and to subsequent gendered choices throughout the life course.
Saturn is permanently surrounded by 6 discrete proton radiation belts that are rigidly separated by the orbits of its inner moons and dense rings. These radiation belts are ideal environments to study the details of radial diffusion and the CRAND source process, yet progress has been hindered by the fact that the energy spectra are not known with certainty: Reanalysis of the response functions of the LEMMS instrument on-board the Cassini orbiter has shown that measurements of less than or similar to 10 MeV protons may be easily contaminated by greater than or similar to 10 MeV protons and that many available measurements characterize a very broad energy range, so that the calculation of an energy-resolved spectrum is not as straightforward as previously assumed. Here we use forward modeling of the measurements based on the instrument response and combine this technique where useful with numerical modeling of the proton belt physics in order to determine Saturn's spectra with higher certainty. We find significant proton intensities up to approximate to 1 GeV. While earlier studies reported on proton spectra roughly following a power law with exponent approximate to -2, our more advanced analysis shows harder spectra with exponent approximate to -1. The observed spectra provide independent confirmation that Saturn's proton belts are sourced by CRAND and are consistent with the provided protons being subsequently cooled in the tenuous gas originating from Saturn or Enceladus. The intensities at Saturn are found to be lower than at Jupiter and Earth, which is also consistent with the source of Saturn being exclusively CRAND, while the other planets can draw from additional processes. Our new spectra can be used in the future to further our understanding of Saturn's proton belts and the respective physical processes that occur at other magnetized planets in general. Also, the spectra have applications for several topics of planetary science, such as space weathering of Saturn's moons and rings, and can be useful to constrain properties of the main rings through their production of secondary particles.
The martensitic transformation is a fundamental physical phenomenon at the origin of important industrial applications. However, the underlying microscopic mechanism, which is of critical importance to explain the outstanding mechanical properties of martensitic materials, is still not fully understood. This is because for most martensitic materials the transformation is a fast process that makes in situ studies extremely challenging. Noble solids krypton and xenon undergo a progressive pressure-induced face-centered cubic (fcc) to hexagonal close-packed (hcp) martensitic transition with a very wide coexistence domain. Here, we took advantage of this unique feature to study the detailed transformation progress at the atomic level by employing in situ x-ray diffraction and absorption spectroscopy. We evidenced a four-stage pathway and suggest that the lattice mismatch between the fcc and hcp forms plays a key role in the generation of strain. We also determined precisely the effect of the transformation on the compression behavior of these materials.
Raman spectroscopic quantification of tetrahedral boron in synthetic aluminum-rich tourmaline
(2021)
The Raman spectra of five B-[4]-bearing tourmalines of different composition synthesized at 700 degrees C/4.0 GPa (including first-time synthesis of Na-Li-B-[4]-tourmaline, Ca-Li-B-[4]-tourmaline, and Ca-bearing square-B-[4]-tourmaline) reveal a strong correlation between the tetrahedral boron content and the summed relative intensity of all OH-stretching bands between 3300-3430 cm(-1). The band shift to low wavenumbers is explained by strong O3-H center dot center dot center dot O5 hydrogen bridge bonding. Applying the regression equation to natural B-[4]-bearing tourmaline from the Koralpe (Austria) reproduces the EMPA-derived value perfectly [EMPA: 0.67(12) B-[4] pfu vs. Raman: 0.66(13) B-[4] pfu]. This demonstrates that Raman spectroscopy provides a fast and easy-to-use tool for the quantification of tetrahedral boron in tourmaline. The knowledge of the amount of tetrahedral boron in tourmaline has important implications for the better understanding and modeling of B-isotope fractionation between tourmaline and fluid/melt, widely used as a tracer of mass transfer processes.
Dysfunctional islets of Langerhans are a hallmark of type 2 diabetes (T2D). We hypothesize that differences in islet gene expression alternative splicing which can contribute to altered protein function also participate in islet dysfunction. RNA sequencing (RNAseq) data from islets of obese diabetes-resistant and diabetes-susceptible mice were analyzed for alternative splicing and its putative genetic and epigenetic modulators. We focused on the expression levels of chromatin modifiers and SNPs in regulatory sequences. We identified alternative splicing events in islets of diabetes-susceptible mice amongst others in genes linked to insulin secretion, endocytosis or ubiquitin-mediated proteolysis pathways. The expression pattern of 54 histones and chromatin modifiers, which may modulate splicing, were markedly downregulated in islets of diabetic animals. Furthermore, diabetes-susceptible mice carry SNPs in RNA-binding protein motifs and in splice sites potentially responsible for alternative splicing events. They also exhibit a larger exon skipping rate, e.g., in the diabetes gene Abcc8, which might affect protein function. Expression of the neuronal splicing factor Srrm4 which mediates inclusion of microexons in mRNA transcripts was markedly lower in islets of diabetes-prone compared to diabetes-resistant mice, correlating with a preferential skipping of SRRM4 target exons. The repression of Srrm4 expression is presumably mediated via a higher expression of miR-326-3p and miR-3547-3p in islets of diabetic mice. Thus, our study suggests that an altered splicing pattern in islets of diabetes-susceptible mice may contribute to an elevated T2D risk.
In this study, we investigate numerically the hydro-mechanical behavior of fractured crystalline rock due to one of the five hydraulic stimulations at the Pohang Enhanced Geothermal site in South Korea. We use the commercial code FracMan (Golder Associates) that enables studying hydro-mechanical coupled processes in fractured media in three dimensions combining the finite element method with a discrete fracture network. The software is used to simulate fluid pressure perturbation at fractures during hydraulic stimulation. Our numerical simulation shows that pressure history matching can be obtained by partitioning the treatment into separate phases. This results in adjusted stress-aperture relationships. The evolution of aperture adjustment implies that the stimulation mechanism could be a combination of hydraulic fracturing and shearing. The simulated extent of the 0.01 MPa overpressure contour at the end of the treatment equals to similar to 180 m around the injection point.
Moderate and temporary heat stresses prime plants to tolerate, and survive, a subsequent severe heat stress. Such acquired thermotolerance can be maintained for several days under normal growth conditions, and can create a heat stress memory. We recently demonstrated that plastid-localized small heat shock protein 21 ( HSP21) is a key component of heat stress memory in Arabidopsis thaliana. A sustained high abundance of HSP21 during the heat stress recovery phase extends heat stress memory. The level of HSP21 is negatively controlled by plastid-localized metalloprotease FtsH6 during heat stress recovery. Here, we demonstrate that autophagy, a cellular recycling mechanism, exerts additional control over HSP21 degradation. Genetic and chemical disruption of both metalloprotease activity and autophagy trigger superior HSP21 accumulation, thereby improving memory. Furthermore, we provide evidence that autophagy cargo receptor ATG8-INTERACTING PROTEIN1 (ATI1) is associated with heat stress memory. ATI1 bodies co-localize with both autophagosomes and HSP21, and their abundance and transport to the vacuole increase during heat stress recovery. Together, our results provide new insights into the module for control of the regulation of heat stress memory, in which two distinct protein degradation pathways act in concert to degrade HSP21, thereby enabling cells to recover from the heat stress effect at the cost of reducing the heat stress memory.
Using the Space Telescope Imaging Spectrograph, we have obtained ultraviolet spectra from similar to 1200 to 2000 angstrom of known Lyman continuum (LyC) emitting galaxies at low redshift (z similar to 0.3-0.4) with varying absolute LyC escape fractions ( f(esc) similar to 0.01-0.72). Our observations include in particular the galaxy J1243+4646, which has the highest known LyC escape fraction at low redshift. While all galaxies are known Lyman alpha emitters, we consistently detect an inventory of additional emission lines, including C IV lambda 1550, He II lambda 1640, O III] lambda 1666, and C III] lambda 1909, whose origin is presumably essentially nebular. C IV lambda 1550 emission is detected above 4 sigma in six out of eight galaxies, with equivalent widths of EW(C IV) = 12-15 angstrom for two galaxies, which exceeds the previously reported maximum emission in low-z star-forming galaxies. We detect C IV lambda 1550 emission in all LyC emitters with escape fractions f(esc) > 0.1 and find a tentative increase in the flux ratio C IV lambda 1550 /C III] lambda 1909 with f(esc). Based on the data, we propose a new criterion to select and classify strong leakers (galaxies with f(esc) > 0.1): C IV lambda 1550 /C III] lambda 1909 greater than or similar to 0.75. Finally, we also find He II lambda 1640 emission in all the strong leakers with equivalent widths from 3 to 8 angstrom rest frame. These are among the highest values observed in star-forming galaxies and are primarily due to a high rate of ionizing photon production. The nebular He II lambda 1640 emission of the strong LyC emitters does not require harder ionizing spectra at >54 eV compared to those of typical star-forming galaxies at similarly low metallicity.
Objective: Hypertension before and during early pregnancy has been associated with an increased risk of gestational diabetes mellitus (GDM) in retrospective analyses. We aimed to investigate the prospective blood pressure trackings in a population-based cohort of pregnant women, who were stratified according to their metabolic status in early third trimester. Methods: We recorded blood pressure longitudinally during pregnancy in 1230 women from the Odense Child Cohort, Denmark. Fasting glucose and insulin were measured at gestational weeks 28-30. Metabolic status was evaluated according to the WHO 2013 threshold for GDM (GDM-WHO: fasting plasma glucose >= 5.1 mmol/l), insulin and homeostatic model assessment of insulin resistance (HOMA-IR). Relationships between metabolic status in third trimester and blood pressure trajectories were evaluated with adjusted linear mixed models. Trajectory was defined as blood pressure records in pregnancy per 4 weeks interval. Results: Prevalence of GDM-WHO was 40% (498/1230). GDM-WHO was associated with 1.46 (0.22-2.70) mmHg higher SBP and 1.04 (0.07-2.01) mmHg higher DBP trajectories in the overall cohort. The associations were driven by differences in the overweight group, with 3.14 (1.05-5.25) mmHg higher SBP and 1.94 (0.42-3.47) mmHg higher DBP per 4 weeks in women with GDM-WHO compared with women without GDM-WHO. GDM-WHO was not associated with blood pressure in women with normal weight. Blood pressure trajectories were elevated across quartiles of insulin resistance. Conclusion: GDM-WHO is associated with higher blood pressure in pregnancy, and there appears to be a stronger effect in overweight women.
Mobile data collection of cognitive-behavioral tasks in substance use disorders: Where are we now?
(2022)
Introduction: Over the last decades, our understanding of the cognitive, motivational, and neural processes involved in addictive behavior has increased enormously. A plethora of laboratory-based and cross-sectional studies has linked cognitive-behavioral measures to between-subject differences in drinking behavior. However, such laboratory-based studies inevitably suffer from small sample sizes and the inability to link temporal fluctuations in task measures to fluctuations in real-life substance use. To overcome these problems, several existing behavioral tasks have been transferred to smartphones to allow studying cognition in the field. Method: In this narrative review, we first summarize studies that used existing behavioral tasks in the laboratory and self-reports of substance use with ecological momentary assessment (EMA) in the field. Next, we review studies on psychometric properties of smartphone-based behavioral tasks. Finally, we review studies that used both smartphone-based tasks and self-reports with EMA in the field. Results: Overall, studies were scarce and heterogenous both in tasks and in study outcomes. Nevertheless, existing findings are promising and point toward several methodological recommendations: concerning psychometrics, studies show that - although more systematic studies are necessary - task validity and reliability can be improved, for example, by analyzing several measurement sessions at once rather than analyzing sessions separately. Studies that use tasks in the field, moreover, show that power can be improved by choosing sampling schemes that combine time-based with event-based sampling, rather than relying on time-based sampling alone. Increasing sampling frequency can further increase power. However, as this also increases the burden to participants, more research is necessary to determine the ideal sampling frequency for each task. Conclusion: Although more research is necessary to systematically study both the psychometrics of smartphone-based tasks and the frequency at which task measures fluctuate, existing studies are promising and reveal important methodological recommendations useful for researchers interested in implementing behavioral tasks in EMA studies.
Comets evolve due to sublimation of ices embedded inside porous dust, triggering dust emission (that is, erosion) followed by mass loss, mass redistribution and surface modifications. Surface changes were revealed by the Deep Impact and Stardust NExT missions for comet 9P/Tempel 1 (ref.(1)), and a full inventory of the processes modifying cometary nuclei was provided by Rosetta while it escorted comet 67P/Churyumov-Gerasimenko for approximately two years(2-4). Such observations also showed puzzling water-ice-rich spots that stood out as patches optically brighter and spectrally bluer than the average cometary surfaces(5-9). These are up to tens of metres large and indicate macroscopic compositional dishomogeneities apparently in contrast with the structural homogeneity above centimetre scales of pebble-made nuclei(10). Here we show that the occurrence of blue patches determines the seasonal variability of the nucleus colour(4,11,12) and gives insight into the internal structure of comets. We define a new model that links the centimetre-sized pebbles composing the nucleus(10) and driving cometary activity(13,14) to metre-sized water-ice-enriched blocks embedded in a drier matrix. The emergence of blue patches is due to the matrix erosion driven by CO2-ice sublimation that exposes the water-ice-enriched blocks, which in turn are eroded by water-ice sublimation when exposed to sunlight. Our model explains the observed seasonal evolution of the nucleus and reconciles the available data at micro (sub-centimetre) and macro (metre) scales.