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In his essay, Mel Ainscow looks at inclusion and equity from an international perspective and makes suggestions on how to develop inclusive education in a ‘whole-system approach’. After discussing different conceptions of inclusion and equity, he describes international policies which address them. From this international macro-level, Ainscow zooms in to the meso-level of the school and its immediate environment, defining dimensions to be considered for an inclusive school development. One of these dimensions is the ‘use of evidence’. In my comment, I want to focus on this dimension and discuss its scope and the potential to apply it in inclusive education development. As a first and important precondition, Ainscow explains that different circumstances lead to different linguistic uses of the term ‘inclusive education’. Thus, the term ‘inclusive education’ does not refer to an identical set of objectives across countries, and neither does the term ‘equity’.
Broad and unspecific use of antibiotics accelerates spread of resistances. Sensitive and robust pathogen detection is thus important for a more targeted application. Bacteriophages contain a large repertoire of pathogen-binding proteins. These tailspike proteins (TSP) often bind surface glycans and represent a promising design platform for specific pathogen sensors. We analysed bacteriophage Sf6 TSP that recognizes the O-polysaccharide of dysentery-causing Shigella flexneri to develop variants with increased sensitivity for sensor applications. Ligand polyrhamnose backbone conformations were obtained from 2D H-1,H-1-trNOESY NMR utilizing methine-methine and methine-methyl correlations. They agreed well with conformations obtained from molecular dynamics (MD), validating the method for further predictions. In a set of mutants, MD predicted ligand flexibilities that were in good correlation with binding strength as confirmed on immobilized S. flexneri O-polysaccharide (PS) with surface plasmon resonance. In silico approaches combined with rapid screening on PS surfaces hence provide valuable strategies for TSP-based pathogen sensor design.
Glycosylphosphatidylinositols (GPIs) are highly complex glycolipids that serve as membrane anchors to a large variety of eukaryotic proteins. These are covalently attached to a group of peripheral proteins called GPI-anchored proteins (GPI-APs) through a post-translational modification in the endoplasmic reticulum. The GPI anchor is a unique structure composed of a glycan, with phospholipid tail at one end and a phosphoethanolamine linker at the other where the protein attaches. The glycan part of the GPI comprises a conserved pseudopentasaccharide core that could branch out to carry additional glycosyl or phosphoethanolamine units. GPI-APs are involved in a diverse range of cellular processes, few of which are signal transduction, protein trafficking, pathogenesis by protozoan parasites like the malaria- causing parasite Plasmodium falciparum. GPIs can also exist freely on the membrane surface without an attached protein such as those found in parasites like Toxoplasma gondii, the causative agent of Toxoplasmosis. These molecules are both structurally and functionally diverse, however, their structure-function relationship is still poorly understood. This is mainly because no clear picture exists regarding how the protein and the glycan arrange with respect to the lipid layer. Direct experimental evidence is rather scarce, due to which inconclusive pictures have emerged, especially regarding the orientation of GPIs and GPI-APs on membrane surfaces and the role of GPIs in membrane organization. It appears that computational modelling through molecular dynamics simulations would be a useful method to make progress. In this thesis, we attempt to explore characteristics of GPI anchors and GPI-APs embedded in lipid bilayers by constructing molecular models at two different resolutions – all-atom and coarse-grained.
First, we show how to construct a modular molecular model of GPIs and GPI-anchored proteins that can be readily extended to a broad variety of systems, addressing the micro-heterogeneity of GPIs. We do so by creating a hybrid link to which GPIs of diverse branching and lipid tails of varying saturation with their optimized force fields, GLYCAM06 and Lipid14 respectively, can be attached. Using microsecond simulations, we demonstrate that GPI prefers to “flop-down” on the membrane, thereby, strongly interacting with the lipid heads, over standing upright like a “lollipop”. Secondly, we extend the model of the GPI core to carry out a systematic study of the structural aspects of GPIs carrying different side chains (parasitic and human GPI variants) inserted in lipid bilayers. Our results demonstrate the importance of the side branch residues as these are the most accessible, and thereby, recognizable epitopes. This finding qualitatively agrees with experimental observations that highlight the role of the side branches in immunogenicity of GPIs and the specificity thereof. The overall flop-down orientation of the GPIs with respect to the bilayer surface presents the side chain residues to face the solvent. Upon attaching the green fluorescent protein (GFP) to the GPI, it is seen to lie in close proximity to the bilayer, interacting both with the lipid heads and glycan part of the GPI. However the orientation of GFP is sensitive to the type of GPI it is attached to. Finally, we construct a coarse-grained model of the GPI and GPI-anchored GFP using a modified version of the MARTINI force-field, using which the timescale is enhanced by at least an order of magnitude compared to the atomistic system.
This study provides a theoretical perspective on the conformational behavior of the GPI core and some of its branched variations in presence of lipid bilayers, as well as draws comparisons with experimental observations. Our modular atomistic model of GPI can be further employed to study GPIs of variable branching, and thereby, aid in designing future experiments especially in the area of vaccines and drug therapies. Our coarse-grained model can be used to study dynamic aspects of GPIs and GPI-APs w.r.t plasma membrane organization. Furthermore, the backmapping technique of converting coarse-grained trajectory back to the atomistic model would enable in-depth structural analysis with ample conformational sampling.
Birds of a feather?
(2020)
The International Monetary Fund and the World Bank ascribe to impartiality in their mandates. At the same time, scholarship indicates that their decisions are disproportionately influenced by powerful member states. Impartiality is seen as crucial in determining International Organizations' (IOs) effectiveness and legitimacy in the literature. However, we know little about whether key interlocutors in national governments perceive the International Financial Institutions as biased actors who do the bidding for powerful member states or as impartial executors of policy. In order to better understand these perceptions, we surveyed high-level civil servants who are chiefly responsible for four policy areas from more than 100 countries. We found substantial variations in impartiality perceptions. What explains these variations? By developing an argument of selective awareness, we extend rationalist and ideational perspectives on IO impartiality to explain domestic perceptions. Using novel survey data, we test whether staffing underrepresentation, voting underrepresentation, alignment to the major shareholders and overlapping economic policy paradigms are associated with impartiality perceptions. We find substantial evidence that shared economic policy paradigms influence impartiality perceptions. The findings imply that by diversifying their ideational culture, IOs can increase the likelihood that domestic stakeholders view them as impartial.
Do all roads lead to Rome?
(2020)
Content website providers have two main goals: They seek to attract consumers and to keep them on their websites as long as possible. To reach potential consumers, they can utilize several online channels, such as paid search results or advertisements on social media, all of which usually require a substantial marketing budget. However, with rising user numbers of online communication tools, website providers increasingly integrate social sharing buttons on their websites to encourage existing consumers to facilitate referrals to their social networks. While little is known about this social form of guiding consumers to a content website, the study proposes that the way in which consumers reach a website is related to their stickiness to the website and their propensity to refer content to others. By using a unique clickstream data set of a video-on-demand website, the study compares consumers referred by their social network to those consumers arriving at the website via organic search or social media advertisements in terms of stickiness to the website (e.g., visit length, number of page views, video starts) and referral likelihood. The results show that consumers referred through social referrals spend more time on the website, view more pages, and start more videos than consumers who respond to social media advertisements, but less than those coming through organic search. Concerning referral propensity, the results indicate that consumers attracted to a website through social referrals are more likely to refer content to others than those who came through organic search or social media advertisements. The study offers direct insights to managers and recommends an increase in their efforts to promote social referrals on their websites.
This article explores the structural diversity of intraministerial organization over time. Based on organization theory, it proposes a generic typology for intraministerial units applicable to any hierarchically structured government organization. We empirically investigate the critical case of the German federal bureaucracy. By classifying its subunits, we analyze the longitudinal development of structural differentiation and its correspondence to denominational variety. The data stem from a novel international dataset, covering all ministries between 1980 and 2015. We find that intraministerial structure differentiates over time, across and within ministries. A stable core of traditional Weberian structure is complemented by structurally innovative intraministerial units. We conclude that the German federal bureaucracy is more diverse than suggested in previous literature. Our findings indicate that less Weberian bureaucracies are at least as structurally diverse and that more reform-driven bureaucracies will have experienced at least as many changes in structural diversity.
Organizations incorporate the institutional demands from their environment in order to be deemed legitimate and survive. Yet, complexifying societies promulgate multiple and sometimes inconsistent institutional prescriptions. When these prescriptions collide, organizations are said to face “institutional complexity”. How does an organization then incorporate incompatible demands? What are the consequences of institutional complexity for an organization? The literature provides contradictory conceptual and empirical insights on the matter. A central assumption, however, remains that internal incompatibilities generate tensions that, under certain conditions, can escalate into intractable conflicts, resulting in dysfunctionality and loss of legitimacy. The present research is an inquiry into what happens inside an organization when it incorporates complex institutional demands.
To answer this question, I focus on how individuals inside an organization interpret a complex institutional prescription. I examine how members of the French Development Agency interpret ‘results-based management’, a central but complex concept of organizing in the field of development aid. I use an inductive mixed methods design to systematically explore how different interpretations of results-based management relate to one another and to the organizational context in which they are embedded.
The results reveal that results-based management is a contested concept in the French Development Agency. I find multiple interpretations of the concept, which are attached to partly incompatible rationales about “who we are” and “what we do as an organization”. These rationales nevertheless coexist as balanced forces, without escalating into open conflict. The analysis points to four reasons for this peaceful coexistence of diverging rationales inside one and the same organization: 1) individuals’ capacity to manipulate different interpretations of a complex institutional demand, 2) the nature of interpretations, which makes them more or less prone to conflict, 3) the balanced distribution of rationales across the organizational sub-contexts and 4) the shared rules of interpretation provided by the larger socio-cultural context.
This research shows that an organization that incorporates institutional complexity comes to represent different, partly incompatible things to its members without being at war with itself. In doing so, it contributes to our knowledge of institutional complexity and organizational hybridity. It also advances our understanding of internal organizational legitimacy and of the translation of managerial concepts in organizations.
This master’s thesis examined the internet content regulation in Germany from a perspective of Public-Private Partnerships. In the European Union, there has been a latest trend of initiatives aiming for combating illegal content online under the self-regulatory regime. Yet, concerns of this trend were that transparency cannot be ensured properly to safeguard the freedom of expression, and that the private intermediaries are not able to carry out effective regulation under the non-binding regulatory process. Due to these issues, Germany has legislated the Network Enforcement Act in 2017. This thesis used Mixed Methods within a Case Study Research, in order to identify the PPP type of the NetzDG, and to understand its link on transparency and effectiveness, as well as the relationship of these two dimensions. By taking an Exploratory Sequential Design, the German internet content regulation under the NetzDG was explored to understand its co-regulatory regime and to develop an instrument to measure the aspects of transparency and effectiveness. Then, the three big social media platforms, YouTube, Twitter, and Facebook, were examined according to the developed indicators. This thesis concluded as follow: First, the enactment of the NetzDG brought the shift of the regulatory paradigm from the self-regulatory to the co-regulatory. Yet, the actor-inclusive institutional arrangement of the NetzDG did not successfully result in the actual inclusion of actors in decision-making, but only improved the result transparency in the disclosure of take-down actions. Second, the level of effective regulation was not consistent across the three social media platforms under this regime. Despite these limitations, this study showed that the transparency and the effectiveness of the social media platforms’ implementation gradually improved together, instead of having a negative correlation to one another.
Inorganic perovskites with cesium (Cs+) as the cation have great potential as photovoltaic materials if their phase purity and stability can be addressed. Herein, a series of inorganic perovskites is studied, and it is found that the power conversion efficiency of solar cells with compositions CsPbI1.8Br1.2, CsPbI2.0Br1.0, and CsPbI2.2Br0.8 exhibits a high dependence on the initial annealing step that is found to significantly affect the crystallization and texture behavior of the final perovskite film. At its optimized annealing temperature, CsPbI1.8Br1.2 exhibits a pure orthorhombic phase and only one crystal orientation of the (110) plane. Consequently, this allows for the best efficiency of up to 14.6% and the longest operational lifetime, T-S80, of approximate to 300 h, averaged of over six solar cells, during the maximum power point tracking measurement under continuous light illumination and nitrogen atmosphere. This work provides essential progress on the enhancement of photovoltaic performance and stability of CsPbI3 - xBrx perovskite solar cells.
Motivation: Corruption is often cited as a central reason why development projects fail. The article tests this claim by assessing whether World Bank projects perform worse in implementation environments with a higher corruption level. The article focuses specifically on bribery between public officials and firms during the procurement of needed goods and services. Approach and Methods: I use data from the World Bank's Enterprise Surveys to avoid the often-criticized corruption perception indices and to allow for an assessment of effects at the subnational level. The analysis builds on an assessment of the performance ratings of 1,228 World Bank projects and covers 87 different countries. Finding: Overall, the article finds a small but statistically significant correlation between the corruption level and project performance. This result indicates that the corruption level of recipient countries should be considered during the design and implementation of projects. Policy Implications: Nonetheless, the relatively small correlation and the low pseudo R-squareds advise not overestimating the relevance of corruption for project performance. At least for the project level, the article finds no indication that corruption is a primary obstacle to aid effectiveness.
Although many studies have shown that victims of child abuse have an increased vulnerability to revictimization in intimate relationships, the underlying mechanisms are not yet sufficiently well understood. Therefore, this study aimed at examining this relationship for both sexual and physical forms of violence as well as investigating the potential mediating role of attitudes toward sexual and physical intimate partner violence (IPV). Also, the potential moderating role of gender was explored. Sexual and physical child abuse and IPV victimization in adulthood as well as attitudes toward the respective form of IPV were assessed among 716 participants (448 female) in an online survey. The path analyses showed that child sexual abuse was positively linked to sexual IPV victimization among both women and men, whereas child physical abuse was positively associated with physical IPV victimization among women only. Furthermore, the relationship between both forms of child abuse and IPV victimization was mediated through more supportive attitudes toward the respective forms of IPV, but only among men. This study provides novel insights regarding the links between sexual and physical child abuse and revictimization in adulthood, suggesting that supporting attitudes toward IPV may be seen as vulnerability factor for revictimization. The moderating role of gender is especially discussed.
As research on sexual aggression has been growing, methodological issues in assessing prevalence rates have received increased attention. Building on work by Abbey and colleagues about effects of question format, participants in this study (1,253; 621 female; 632 male) were randomly assigned to one of two versions of the Sexual Aggression and Victimization Scale (SAV-S). In Version 1, the coercive tactic (use/threat of physical force, exploitation of the inability to resist, verbal pressure) was presented first, and sexual acts (sexual touch, attempted and completed sexual intercourse, other sexual acts) were presented as subsequent questions. In Version 2, sexual acts were presented first, and coercive tactics as subsequent questions. No version effects emerged for overall perpetration rates reported by men and women. The overall victimization rate across all items was significantly higher in the tactic-first than in the sexual-act-first conditions for women, but not for men. Classifying participants by their most severe experience of sexual victimization showed that fewer women were in the nonvictim category and more men were in the nonconsensual sexual contact category when the coercive tactic was presented first. Sexual experience background did not moderate the findings. The implications for the measurement of self-reported sexual aggression victimization and perpetration are discussed.
Perovskite photovoltaic (PV) cells have demonstrated power conversion efficiencies (PCE) that are close to those of monocrystalline silicon cells; however, in contrast to silicon PV, perovskites are not limited by Auger recombination under 1-sun illumination. Nevertheless, compared to GaAs and monocrystalline silicon PV, perovskite cells have significantly lower fill factors due to a combination of resistive and non-radiative recombination losses. This necessitates a deeper understanding of the underlying loss mechanisms and in particular the ideality factor of the cell. By measuring the intensity dependence of the external open-circuit voltage and the internal quasi-Fermi level splitting (QFLS), the transport resistance-free efficiency of the complete cell as well as the efficiency potential of any neat perovskite film with or without attached transport layers are quantified. Moreover, intensity-dependent QFLS measurements on different perovskite compositions allows for disentangling of the impact of the interfaces and the perovskite surface on the non-radiative fill factor and open-circuit voltage loss. It is found that potassium-passivated triple cation perovskite films stand out by their exceptionally high implied PCEs > 28%, which could be achieved with ideal transport layers. Finally, strategies are presented to reduce both the ideality factor and transport losses to push the efficiency to the thermodynamic limit.
Sexual aggression is a problem among college students worldwide, and a growing body of research has identified variables associated with an increased risk of victimization and perpetration. Among these, sexuality-related cognitions, such as sexual scripts, sexual self-esteem, perceived realism of pornography, and acceptance of sexual coercion, play a major role. The current experimental study aimed to show that these cognitive risk factors of sexual aggression victimization and perpetration are amenable to change, which is a critical condition for evidence-based intervention efforts. College students in Germany (N = 324) were randomly assigned to one of three groups: a treatment group designed to change participants' sexual scripts for consensual sex with regard to the role of alcohol consumption, casual sex, and ambiguous communication of sexual intentions as risk factors for sexual aggression (EG1), a treatment group designed to promote sexual self-esteem, challenge the perceived realism of pornography, and reduce the acceptance of sexual coercion (EG2), and a non-treatment control group (CG). Baseline (T1), post-experimental (T2), and follow-up (T3) measures were taken across an eight-week period. Sexual scripts contained fewer risk factors for sexual aggression in EG1 than in EG2 and CG at T3. Sexual self-esteem was enhanced in EG2 at T2 relative to the other two groups. Acceptance of sexual coercion was lower in EG2 than in EG1 and CG at T2 and T3. No effect was found for perceived realism of pornography. The findings are discussed in terms of targeting cognitive risk factors as a basis for intervention programs.
The plasmasphere is a dynamic region of cold, dense plasma surrounding the Earth. Its shape and size are highly susceptible to variations in solar and geomagnetic conditions. Having an accurate model of plasma density in the plasmasphere is important for GNSS navigation and for predicting hazardous effects of radiation in space on spacecraft. The distribution of cold plasma and its dynamic dependence on solar wind and geomagnetic conditions remain, however, poorly quantified. Existing empirical models of plasma density tend to be oversimplified as they are based on statistical averages over static parameters. Understanding the global dynamics of the plasmasphere using observations from space remains a challenge, as existing density measurements are sparse and limited to locations where satellites can provide in-situ observations. In this dissertation, we demonstrate how such sparse electron density measurements can be used to reconstruct the global electron density distribution in the plasmasphere and capture its dynamic dependence on solar wind and geomagnetic conditions.
First, we develop an automated algorithm to determine the electron density from in-situ measurements of the electric field on the Van Allen Probes spacecraft. In particular, we design a neural network to infer the upper hybrid resonance frequency from the dynamic spectrograms obtained with the Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) instrumentation suite, which is then used to calculate the electron number density. The developed Neural-network-based Upper hybrid Resonance Determination (NURD) algorithm is applied to more than four years of EMFISIS measurements to produce the publicly available electron density data set.
We utilize the obtained electron density data set to develop a new global model of plasma density by employing a neural network-based modeling approach. In addition to the location, the model takes the time history of geomagnetic indices and location as inputs, and produces electron density in the equatorial plane as an output. It is extensively validated using in-situ density measurements from the Van Allen Probes mission, and also by comparing the predicted global evolution of the plasmasphere with the global IMAGE EUV images of He+ distribution. The model successfully reproduces erosion of the plasmasphere on the night side as well as plume formation and evolution, and agrees well with data.
The performance of neural networks strongly depends on the availability of training data, which is limited during intervals of high geomagnetic activity. In order to provide reliable density predictions during such intervals, we can employ physics-based modeling. We develop a new approach for optimally combining the neural network- and physics-based models of the plasmasphere by means of data assimilation. The developed approach utilizes advantages of both neural network- and physics-based modeling and produces reliable global plasma density reconstructions for quiet, disturbed, and extreme geomagnetic conditions.
Finally, we extend the developed machine learning-based tools and apply them to another important problem in the field of space weather, the prediction of the geomagnetic index Kp. The Kp index is one of the most widely used indicators for space weather alerts and serves as input to various models, such as for the thermosphere, the radiation belts and the plasmasphere. It is therefore crucial to predict the Kp index accurately. Previous work in this area has mostly employed artificial neural networks to nowcast and make short-term predictions of Kp, basing their inferences on the recent history of Kp and solar wind measurements at L1. We analyze how the performance of neural networks compares to other machine learning algorithms for nowcasting and forecasting Kp for up to 12 hours ahead. Additionally, we investigate several machine learning and information theory methods for selecting the optimal inputs to a predictive model of Kp. The developed tools for feature selection can also be applied to other problems in space physics in order to reduce the input dimensionality and identify the most important drivers.
Research outlined in this dissertation clearly demonstrates that machine learning tools can be used to develop empirical models from sparse data and also can be used to understand the underlying physical processes. Combining machine learning, physics-based modeling and data assimilation allows us to develop novel methods benefiting from these different approaches.
The Earth's inner magnetosphere is a very dynamic system, mostly driven by the external solar wind forcing exerted upon the magnetic field of our planet. Disturbances in the solar wind, such as coronal mass ejections and co-rotating interaction regions, cause geomagnetic storms, which lead to prominent changes in charged particle populations of the inner magnetosphere - the plasmasphere, ring current, and radiation belts. Satellites operating in the regions of elevated energetic and relativistic electron fluxes can be damaged by deep dielectric or surface charging during severe space weather events. Predicting the dynamics of the charged particles and mitigating their effects on the infrastructure is of particular importance, due to our increasing reliance on space technologies.
The dynamics of particles in the plasmasphere, ring current, and radiation belts are strongly coupled by means of collisions and collisionless interactions with electromagnetic fields induced by the motion of charged particles. Multidimensional numerical models simplify the treatment of transport, acceleration, and loss processes of these particles, and allow us to predict how the near-Earth space environment responds to solar storms. The models inevitably rely on a number of simplifications and assumptions that affect model accuracy and complicate the interpretation of the results. In this dissertation, we quantify the processes that control electron dynamics in the inner magnetosphere, paying particular attention to the uncertainties of the employed numerical codes and tools.
We use a set of convenient analytical solutions for advection and diffusion equations to test the accuracy and stability of the four-dimensional Versatile Electron Radiation Belt (VERB-4D) code. We show that numerical schemes implemented in the code converge to the analytical solutions and that the VERB-4D code demonstrates stable behavior independent of the assumed time step. The order of the numerical scheme for the convection equation is demonstrated to affect results of ring current and radiation belt simulations, and it is crucially important to use high-order numerical schemes to decrease numerical errors in the model.
Using the thoroughly tested VERB-4D code, we model the dynamics of the ring current electrons during the 17 March 2013 storm. The discrepancies between the model and observations above 4.5 Earth's radii can be explained by uncertainties in the outer boundary conditions. Simulation results indicate that the electrons were transported from the geostationary orbit towards the Earth by the global-scale electric and magnetic fields.
We investigate how simulation results depend on the input models and parameters. The model is shown to be particularly sensitive to the global electric field and electron lifetimes below 4.5 Earth's radii. The effects of radial diffusion and subauroral polarization streams are also quantified.
We developed a data-assimilative code that blends together a convection model of energetic electron transport and loss and Van Allen Probes satellite data by means of the Kalman filter. We show that the Kalman filter can correct model uncertainties in the convection electric field, electron lifetimes, and boundary conditions. It is also demonstrated how the innovation vector - the difference between observations and model prediction - can be used to identify physical processes missing in the model of energetic electron dynamics.
We computed radial profiles of phase space density of ultrarelativistic electrons, using Van Allen Probes measurements. We analyze the shape of the profiles during geomagnetically quiet and disturbed times and show that the formation of new local minimums in the radial profiles coincides with the ground observations of electromagnetic ion-cyclotron (EMIC) waves. This correlation indicates that EMIC waves are responsible for the loss of ultrarelativistic electrons from the heart of the outer radiation belt into the Earth's atmosphere.
The Cluster mission has produced a large data set of electron flux measurements in the Earth's magnetosphere since its launch in late 2000. Electron fluxes are measured using Research with Adaptive Particle Imaging Detector (RAPID)/Imaging Electron Spectrometer (IES) detector as a function of energy, pitch angle, spacecraft position, and time. However, no adiabatic invariants have been calculated for Cluster so far. In this paper we present a step-by-step guide to calculations of adiabatic invariants and conversion of the electron flux to phase space density (PSD) in these coordinates. The electron flux is measured in two RAPID/IES energy channels providing pitch angle distribution at energies 39.2-50.5 and 68.1-94.5 keV in nominal mode since 2004. A fitting method allows to expand the conversion of the differential fluxes to the range from 40 to 150 keV. Best data coverage for phase space density in adiabatic invariant coordinates can be obtained for values of second adiabatic invariant, K, similar to 10(2), and values of the first adiabatic invariant mu in the range approximate to 5-20 MeV/G. Furthermore, we describe the production of a new data product "LSTAR," equivalent to the third adiabatic invariant, available through the Cluster Science Archive for years 2001-2018 with 1-min resolution. The produced data set adds to the availability of observations in Earth's radiation belts region and can be used for long-term statistical purposes.
The Cheb Basin (CZ) is a shallow Neogene intracontinental basin located in the western Eger Rift. The Cheb Basin is characterized by active seismicity and diffuse degassing of mantle-derived CO2 in mofette fields. Within the Cheb Basin, the Hartoušov mofette field shows a daily CO2 flux of 23–97 tons. More than 99% of CO2 released over an area of 0.35 km2. Seismic active periods have been observed in 2000 and 2014 in the Hartoušov mofette field. Due to the active geodynamic processes, the Cheb Basin is considered to be an ideal region for the continental deep biosphere research focussing on the interaction of biological processes with geological processes.
To study the influence of CO2 degassing on microbial community in the surface and subsurface environments, two 3-m shallow drillings and a 108.5-m deep scientific drilling were conducted in 2015 and 2016 respectively. Additionally, the fluid retrieved from the deep drilling borehole was also recovered. The different ecosystems were compared regarding their geochemical properties, microbial abundances, and microbial community structures. The geochemistry of the mofette is characterized by low pH, high TOC, and sulfate contents while the subsurface environment shows a neutral pH, and various TOC and sulfate contents in different lithological settings. Striking differences in the microbial community highlight the substantial impact of elevated CO2 concentrations and high saline groundwater on microbial processes. In general, the microorganisms had low abundance in the deep subsurface sediment compared with the shallow mofette. However, within the mofette and the deep subsurface sediment, the abundance of microbes does not show a typical decrease with depth, indicating that the uprising CO2-rich groundwater has a strong influence on the microbial communities via providing sufficient substrate for anaerobic chemolithoautotrophic microorganisms. Illumina MiSeq sequencing of the 16S rRNA genes and multivariate statistics reveals that the pH strongly influences the microbial community composition in the mofette, while the subsurface microbial community is significantly influenced by the groundwater which motivated by the degassing CO2. Acidophilic microorganisms show a much higher relative abundance in the mofette. Meanwhile, the OTUs assigned to family Comamonadaceae are the dominant taxa which characterize the subsurface communities. Additionally, taxa involved in sulfur cycling characterizing the microbial communities in both mofette and CO2 dominated subsurface environments.
Another investigated important geo–bio interaction is the influence of the seismic activity. During seismic events, released H2 may serve as the electron donor for microbial hydrogenotrophic processes, such as methanogenesis. To determine whether the seismic events can potentially trigger methanogenesis by the elevated geogenic H2 concentration, we performed laboratory simulation experiments with sediments retrieved from the drillings. The simulation results indicate that after the addition of hydrogen, substantial amounts of methane were produced in incubated mofette sediments and deep subsurface sediments. The methanogenic hydrogenotrophic genera Methanobacterium was highly enriched during the incubation. The modeling of the in-situ observation of the earthquake swarm period in 2000 at the Novy Kostel focal area/Czech Republic and our laboratory simulation experiments reveals a close relation between seismic activities and microbial methane production via earthquake-induced H2 release. We thus conclude that H2 – which is released during seismic activity – can potentially trigger methanogenic activity in the deep subsurface. Based on this conclusion, we further hypothesize that the hydrogenotrophic early life on Earth was boosted by the Late Heavy Bombardment induced seismic activity in approximately 4.2 to 3.8 Ga.
Polynucleobacter asymbioticus strain QLW-P1DMWA-1T represents a group of highly successful heterotrophic ultramicrobacteria that is frequently very abundant (up to 70% of total bacterioplankton) in freshwater habitats across all seven continents. This strain was originally isolated from a shallow Alpine pond characterized by rapid changes in water temperature and elevated UV radiation due to its location at an altitude of 1300 m. To elucidate the strain’s adjustment to fluctuating environmental conditions, we recorded changes occurring in its transcriptomic and proteomic profiles under contrasting experimental conditions by simulating thermal conditions in winter and summer as well as high UV irradiation. To analyze the potential connection between gene expression and regulation via methyl group modification of the genome, we also analyzed its methylome. The methylation pattern differed between the three treatments, pointing to its potential role in differential gene expression. An adaptive process due to evolutionary pressure in the genus was deduced by calculating the ratios of non-synonymous to synonymous substitution rates for 20 Polynucleobacter spp. genomes obtained from geographically diverse isolates. The results indicate purifying selection.
New Methods, New Concepts
(2020)
Microbial interactions play an essential role in aquatic ecosystems and are of the great interest for both marine and freshwater ecologists. Recent development of new technologies and methods allowed to reveal many functional mechanisms and create new concepts. Yet, many fundamental aspects of microbial interactions have been almost exclusively studied for marine pelagic and benthic ecosystems. These studies resulted in a formulation of the Black Queen Hypothesis, a development of the phycosphere concept for pelagic communities, and a realization of microbial communication as a key mechanism for microbial interactions. In freshwater ecosystems, especially for periphyton communities, studies focus mainly on physiology, biodiversity, biological indication, and assessment, but the many aspects of microbial interactions are neglected to a large extent. Since periphyton plays a great role for aquatic nutrient cycling, provides the basis for water purification, and can be regarded as a hotspot of microbial biodiversity, we highlight that more in-depth studies on microbial interactions in periphyton are needed to improve our understanding on functioning of freshwater ecosystems. In this paper we first present an overview on recent concepts (e.g., the “Black Queen Hypothesis”) derived from state-of-the-art OMICS methods including metagenomics, metatranscriptomics, and metabolomics. We then point to the avenues how these methods can be applied for future studies on biodiversity and the ecological role of freshwater periphyton, a yet largely neglected component of many freshwater ecosystems.