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Over the years, we developed highly selective fluorescent probes for K+ in water, which show K+-induced fluorescence intensity enhancements, lifetime changes, or a ratiometric behavior at two emission wavelengths (cf. Scheme 1, K1-K4). In this paper, we introduce selective fluorescent probes for Na+ in water, which also show Na+ induced signal changes, which are analyzed by diverse fluorescence techniques. Initially, we synthesized the fluorescent probes 2, 4, 5, 6 and 10 for a fluorescence analysis by intensity enhancements at one wavelength by varying the Na+ responsive ionophore unit and the fluorophore moiety to adjust different K-d values for an intra- or extracellular Na+ analysis. Thus, we found that 2, 4 and 5 are Na+ selective fluorescent tools, which are able to measure physiologically important Na+ levels at wavelengths higher than 500 nm. Secondly, we developed the fluorescent probes 7 and 8 to analyze precise Na+ levels by fluorescence lifetime changes. Herein, only 8 (K-d=106 mm) is a capable fluorescent tool to measure Na+ levels in blood samples by lifetime changes. Finally, the fluorescent probe 9 was designed to show a Na+ induced ratiometric fluorescence behavior at two emission wavelengths. As desired, 9 (K-d=78 mm) showed a ratiometric fluorescence response towards Na+ ions and is a suitable tool to measure physiologically relevant Na+ levels by the intensity change of two emission wavelengths at 404 nm and 492 nm.
The novel space-borne Global Navigation Satellite System Reflectometry (GNSS-R) technique has recently shown promise in monitoring the ocean state and surface wind speed with high spatial coverage and unprecedented sampling rate. The L-band signals of GNSS are structurally able to provide a higher quality of observations from areas covered by dense clouds and under intense precipitation, compared to those signals at higher frequencies from conventional ocean scatterometers. As a result, studying the inner core of cyclones and improvement of severe weather forecasting and cyclone tracking have turned into the main objectives of GNSS-R satellite missions such as Cyclone Global Navigation Satellite System (CYGNSS). Nevertheless, the rain attenuation impact on GNSS-R wind speed products is not yet well documented. Evaluating the rain attenuation effects on this technique is significant since a small change in the GNSS-R can potentially cause a considerable bias in the resultant wind products at intense wind speeds. Based on both empirical evidence and theory, wind speed is inversely proportional to derived bistatic radar cross section with a natural logarithmic relation, which introduces high condition numbers (similar to ill-posed conditions) at the inversions to high wind speeds. This paper presents an evaluation of the rain signal attenuation impact on the bistatic radar cross section and the derived wind speed. This study is conducted simulating GNSS-R delay-Doppler maps at different rain rates and reflection geometries, considering that an empirical data analysis at extreme wind intensities and rain rates is impossible due to the insufficient number of observations from these severe conditions. Finally, the study demonstrates that at a wind speed of 30 m/s and incidence angle of 30 degrees, rain at rates of 10, 15, and 20 mm/h might cause overestimation as large as approximate to 0.65 m/s (2%), 1.00 m/s (3%), and 1.3 m/s (4%), respectively, which are still smaller than the CYGNSS required uncertainty threshold. The simulations are conducted in a pessimistic condition (severe continuous rainfall below the freezing height and over the entire glistening zone) and the bias is expected to be smaller in size in real environments.
Peroxisome biogenesis disorders (PBDs) are nontreatable hereditary diseases with a broad range of severity. Approximately 65% of patients are affected by mutations in the peroxins Pex1 and Pex6. The proteins form the heteromeric Pex1/Pex6 complex, which is important for protein import into peroxisomes. To date, no structural data are available for this AAA+ ATPase complex. However, a wealth of information can be transferred from low-resolution structures of the yeast scPex1/scPex6 complex and homologous, well-characterized AAA+ ATPases. We review the abundant records of missense mutations described in PBD patients with the aim to classify and rationalize them by mapping them onto a homology model of the human Pex1/Pex6 complex. Several mutations concern functionally conserved residues that are implied in ATP hydrolysis and substrate processing. Contrary to fold destabilizing mutations, patients suffering from function-impairing mutations may not benefit from stabilizing agents, which have been reported as potential therapeutics for PBD patients.
During the last few decades, the rapid separation of the Small Aral Sea from the isolated basin has changed its hydrological and ecological conditions tremendously. In the present study, we developed and validated the hybrid model for the Syr Darya River basin based on a combination of state-of-the-art hydrological and machine learning models. Climate change impact on freshwater inflow into the Small Aral Sea for the projection period 2007–2099 has been quantified based on the developed hybrid model and bias corrected and downscaled meteorological projections simulated by four General Circulation Models (GCM) for each of three Representative Concentration Pathway scenarios (RCP). The developed hybrid model reliably simulates freshwater inflow for the historical period with a Nash–Sutcliffe efficiency of 0.72 and a Kling–Gupta efficiency of 0.77. Results of the climate change impact assessment showed that the freshwater inflow projections produced by different GCMs are misleading by providing contradictory results for the projection period. However, we identified that the relative runoff changes are expected to be more pronounced in the case of more aggressive RCP scenarios. The simulated projections of freshwater inflow provide a basis for further assessment of climate change impacts on hydrological and ecological conditions of the Small Aral Sea in the 21st Century.
The Postmasburg Manganese Field (PMF), Northern Cape Province, South Africa, once represented one of the largest sources of manganese ore worldwide. Two belts of manganese ore deposits have been distinguished in the PMF, namely the Western Belt of ferruginous manganese ores and the Eastern Belt of siliceous manganese ores. Prevailing models of ore formation in these two belts invoke karstification of manganese-rich dolomites and residual accumulation of manganese wad which later underwent diagenetic and low-grade metamorphic processes. For the most part, the role of hydrothermal processes and metasomatic alteration towards ore formation has not been adequately discussed. Here we report an abundance of common and some rare Al-, Na-, K- and Ba-bearing minerals, particularly aegirine, albite, microcline, banalsite, sérandite-pectolite, paragonite and natrolite in Mn ores of the PMF, indicative of hydrothermal influence. Enrichments in Na, K and/or Ba in the ores are generally on a percentage level for most samples analysed through bulk-rock techniques. The presence of As-rich tokyoite also suggests the presence of As and V in the hydrothermal fluid. The fluid was likely oxidized and alkaline in nature, akin to a mature basinal brine. Various replacement textures, particularly of Na- and K- rich minerals by Ba-bearing phases, suggest sequential deposition of gangue as well as ore-minerals from the hydrothermal fluid, with Ba phases being deposited at a later stage. The stratigraphic variability of the studied ores and their deviation from the strict classification of ferruginous and siliceous ores in the literature, suggests that a re-evaluation of genetic models is warranted. New Ar-Ar ages for K-feldspars suggest a late Neoproterozoic timing for hydrothermal activity. This corroborates previous geochronological evidence for regional hydrothermal activity that affected Mn ores at the PMF but also, possibly, the high-grade Mn ores of the Kalahari Manganese Field to the north. A revised, all-encompassing model for the development of the manganese deposits of the PMF is then proposed, whereby the source of metals is attributed to underlying carbonate rocks beyond the Reivilo Formation of the Campbellrand Subgroup. The main process by which metals are primarily accumulated is attributed to karstification of the dolomitic substrate. The overlying Asbestos Hills Subgroup banded iron formation (BIF) is suggested as a potential source of alkali metals, which also provides a mechanism for leaching of these BIFs to form high-grade residual iron ore deposits.
Lanthanide-doped upconverting nanoparticles (UCNP) are being extensively studied for bioapplications due to their unique photoluminescence properties and low toxicity. Interest in RET applications involving UCNP is also increasing, but due to factors such as large sizes, ion emission distributions within the particles, and complicated energy transfer processes within the UCNP, there are still many questions to be answered. In this study, four types of core and core-shell NaYF4-based UCNP co-doped with Yb3+ and Tm3+ as sensitizer and activator, respectively, were investigated as donors for the Methyl 5-(8-decanoylbenzo[1,2-d:4,5-d ']bis([1,3]dioxole)-4-yl)-5-oxopentanoate (DBD-6) dye. The possibility of resonance energy transfer (RET) between UCNP and the DBD-6 attached to their surface was demonstrated based on the comparison of luminescence intensities, band ratios, and decay kinetics. The architecture of UCNP influenced both the luminescence properties and the energy transfer to the dye: UCNP with an inert shell were the brightest, but their RET efficiency was the lowest (17%). Nanoparticles with Tm3+ only in the shell have revealed the highest RET efficiencies (up to 51%) despite the compromised luminescence due to surface quenching.
Arboreal epiphytes (plants residing in forest canopies) are present across all major climate zones and play important roles in forest biogeochemistry. The substantial water storage capacity per unit area of the epiphyte “bucket” is a key attribute underlying their capability to influence forest hydrological processes and their related mass and energy flows. It is commonly assumed that the epiphyte bucket remains saturated, or near-saturated, most of the time; thus, epiphytes (particularly vascular epiphytes) can store little precipitation, limiting their impact on the forest canopy water budget. We present evidence that contradicts this common assumption from (i) an examination of past research; (ii) new datasets on vascular epiphyte and epi-soil water relations at a tropical montane cloud forest (Monteverde, Costa Rica); and (iii) a global evaluation of non-vascular epiphyte saturation state using a process-based vegetation model, LiBry. All analyses found that the external and internal water storage capacity of epiphyte communities is highly dynamic and frequently available to intercept precipitation. Globally, non-vascular epiphytes spend <20% of their time near saturation and regionally, including the humid tropics, model results found that non-vascular epiphytes spend ~1/3 of their time in the dry state (0–10% of water storage capacity). Even data from Costa Rican cloud forest sites found the epiphyte community was saturated only 1/3 of the time and that internal leaf water storage was temporally dynamic enough to aid in precipitation interception. Analysis of the epi-soils associated with epiphytes further revealed the extent to which the epiphyte bucket emptied—as even the canopy soils were often <50% saturated (29–53% of all days observed). Results clearly show that the epiphyte bucket is more dynamic than currently assumed, meriting further research on epiphyte roles in precipitation interception, redistribution to the surface and chemical composition of “net” precipitation waters reaching the surface.
Fractures serve as highly conductive preferential flow paths for fluids in rocks, which are difficult to exactly reconstruct in numerical models. Especially, in low-conductive rocks, fractures are often the only pathways for advection of solutes and heat. The presented study compares the results from hydraulic and tracer tomography applied to invert a theoretical discrete fracture network (DFN) that is based on data from synthetic cross-well testing. For hydraulic tomography, pressure pulses in various injection intervals are induced and the pressure responses in the monitoring intervals of a nearby observation well are recorded. For tracer tomography, a conservative tracer is injected in different well levels and the depth-dependent breakthrough of the tracer is monitored. A recently introduced transdimensional Bayesian inversion procedure is applied for both tomographical methods, which adjusts the fracture positions, orientations, and numbers based on given geometrical fracture statistics. The used Metropolis-Hastings-Green algorithm is refined by the simultaneous estimation of the measurement error’s variance, that is, the measurement noise. Based on the presented application to invert the two-dimensional cross-section between source and the receiver well, the hydraulic tomography reveals itself to be more suitable for reconstructing the original DFN. This is based on a probabilistic representation of the inverted results by means of fracture probabilities.
Surface modification by polyzwitterions of the sulfabetaine-type, and their resistance to biofouling
(2019)
Films of zwitterionic polymers are increasingly explored for conferring fouling resistance to materials. Yet, the structural diversity of polyzwitterions is rather limited so far, and clear structure-property relationships are missing. Therefore, we synthesized a series of new polyzwitterions combining ammonium and sulfate groups in their betaine moieties, so-called poly(sulfabetaine)s. Their chemical structures were varied systematically, the monomers carrying methacrylate, methacrylamide, or styrene moieties as polymerizable groups. High molar mass homopolymers were obtained by free radical polymerization. Although their solubilities in most solvents were very low, brine and lower fluorinated alcohols were effective solvents in most cases. A set of sulfabetaine copolymers containing about 1 mol % (based on the repeat units) of reactive benzophenone methacrylate was prepared, spin-coated onto solid substrates, and photo-cured. The resistance of these films against the nonspecific adsorption by two model proteins (bovine serum albumin—BSA, fibrinogen) was explored, and directly compared with a set of references. The various polyzwitterions reduced protein adsorption strongly compared to films of poly(n-butyl methacrylate) that were used as a negative control. The poly(sulfabetaine)s showed generally even somewhat higher anti-fouling activity than their poly(sulfobetaine) analogues, though detailed efficacies depended on the individual polymer–protein pairs. Best samples approach the excellent performance of a poly(oligo(ethylene oxide) methacrylate) reference.
The success of the ensemble Kalman filter has triggered a strong interest in expanding its scope beyond classical state estimation problems. In this paper, we focus on continuous-time data assimilation where the model and measurement errors are correlated and both states and parameters need to be identified. Such scenarios arise from noisy and partial observations of Lagrangian particles which move under a stochastic velocity field involving unknown parameters. We take an appropriate class of McKean–Vlasov equations as the starting point to derive ensemble Kalman–Bucy filter algorithms for combined state and parameter estimation. We demonstrate their performance through a series of increasingly complex multi-scale model systems.
Local observations indicate that climate change and shifting disturbance regimes are causing permafrost degradation. However, the occurrence and distribution of permafrost region disturbances (PRDs) remain poorly resolved across the Arctic and Subarctic. Here we quantify the abundance and distribution of three primary PRDs using time-series analysis of 30-m resolution Landsat imagery from 1999 to 2014. Our dataset spans four continental-scale transects in North America and Eurasia, covering ~10% of the permafrost region. Lake area loss (−1.45%) dominated the study domain with enhanced losses occurring at the boundary between discontinuous and continuous permafrost regions. Fires were the most extensive PRD across boreal regions (6.59%), but in tundra regions (0.63%) limited to Alaska. Retrogressive thaw slumps were abundant but highly localized (<10−5%). Our analysis synergizes the global-scale importance of PRDs. The findings highlight the need to include PRDs in next-generation land surface models to project the permafrost carbon feedback.
The transition from pollinator-mediated outbreeding to selfing has occurred many times in angiosperms. This is generally accompanied by a reduction in traits attracting pollinators, including reduced emission of floral scent. In Capsella, emission of benzaldehyde as a main component of floral scent has been lost in selfing C. rubella by mutation of cinnamate-CoA ligase CNL1. However, the biochemical basis and evolutionary history of this loss remain unknown, as does the reason for the absence of benzaldehyde emission in the independently derived selfer Capsella orientalis. We used plant transformation, in vitro enzyme assays, population genetics and quantitative genetics to address these questions. CNL1 has been inactivated twice independently by point mutations in C. rubella, causing a loss of enzymatic activity. Both inactive haplotypes are found within and outside of Greece, the centre of origin of C. rubella, indicating that they arose before its geographical spread. By contrast, the loss of benzaldehyde emission in C. orientalis is not due to an inactivating mutation in CNL1. CNL1 represents a hotspot for mutations that eliminate benzaldehyde emission, potentially reflecting the limited pleiotropy and large effect of its inactivation. Nevertheless, even closely related species have followed different evolutionary routes in reducing floral scent.
Today's perovskite solar cells (PSCs) are limited mainly by their open‐circuit voltage (VOC) due to nonradiative recombination. Therefore, a comprehensive understanding of the relevant recombination pathways is needed. Here, intensity‐dependent measurements of the quasi‐Fermi level splitting (QFLS) and of the VOC on the very same devices, including pin‐type PSCs with efficiencies above 20%, are performed. It is found that the QFLS in the perovskite lies significantly below its radiative limit for all intensities but also that the VOC is generally lower than the QFLS, violating one main assumption of the Shockley‐Queisser theory. This has far‐reaching implications for the applicability of some well‐established techniques, which use the VOC as a measure of the carrier densities in the absorber. By performing drift‐diffusion simulations, the intensity dependence of the QFLS, the QFLS‐VOC offset and the ideality factor are consistently explained by trap‐assisted recombination and energetic misalignment at the interfaces. Additionally, it is found that the saturation of the VOC at high intensities is caused by insufficient contact selectivity while heating effects are of minor importance. It is concluded that the analysis of the VOC does not provide reliable conclusions of the recombination pathways and that the knowledge of the QFLS‐VOC relation is of great importance.
The in‐depth understanding of charge carrier photogeneration and recombination mechanisms in organic solar cells is still an ongoing effort. In donor:acceptor (bulk) heterojunction organic solar cells, charge photogeneration and recombination are inter‐related via the kinetics of charge transfer states—being singlet or triplet states. Although high‐charge‐photogeneration quantum yields are achieved in many donor:acceptor systems, only very few systems show significantly reduced bimolecular recombination relative to the rate of free carrier encounters, in low‐mobility systems. This is a serious limitation for the industrialization of organic solar cells, in particular when aiming at thick active layers. Herein, a meta‐analysis of the device performance of numerous bulk heterojunction organic solar cells is presented for which field‐dependent photogeneration, charge carrier mobility, and fill factor are determined. Herein, a “spin‐related factor” that is dependent on the ratio of back electron transfer of the triplet charge transfer (CT) states to the decay rate of the singlet CT states is introduced. It is shown that this factor links the recombination reduction factor to charge‐generation efficiency. As a consequence, it is only in the systems with very efficient charge generation and very fast CT dissociation that free carrier recombination is strongly suppressed, regardless of the spin‐related factor.
Perovskite solar cells combine high carrier mobilities with long carrier lifetimes and high radiative efficiencies. Despite this, full devices suffer from significant nonradiative recombination losses, limiting their VOC to values well below the Shockley–Queisser limit. Here, recent advances in understanding nonradiative recombination in perovskite solar cells from picoseconds to steady state are presented, with an emphasis on the interfaces between the perovskite absorber and the charge transport layers. Quantification of the quasi‐Fermi level splitting in perovskite films with and without attached transport layers allows to identify the origin of nonradiative recombination, and to explain the VOC of operational devices. These measurements prove that in state‐of‐the‐art solar cells, nonradiative recombination at the interfaces between the perovskite and the transport layers is more important than processes in the bulk or at grain boundaries. Optical pump‐probe techniques give complementary access to the interfacial recombination pathways and provide quantitative information on transfer rates and recombination velocities. Promising optimization strategies are also highlighted, in particular in view of the role of energy level alignment and the importance of surface passivation. Recent record perovskite solar cells with low nonradiative losses are presented where interfacial recombination is effectively overcome—paving the way to the thermodynamic efficiency limit.
There has been much research regarding the perceptions, preferences, behaviour, and responses of people exposed to flooding and other nat- ural hazards. Cross-sectional surveys have been the predominant method applied in such research. While cross-sectional data can provide a snapshot of a respondent’s behaviour and perceptions, it cannot be assumed that the respondent’s perceptions are constant over time. As a result, many important research questions relating to dynamic processes, such as changes in risk perceptions, adaptation behaviour, and resilience cannot be fully addressed by cross-sectional surveys. To overcome these shortcomings, there has been a call for developing longitudinal (or panel) datasets in research on natural hazards, vulnerabilities, and risks. However, experiences with implementing longitudinal surveys in the flood risk domain (FRD), which pose distinct methodological challenges, are largely lacking. The key problems are sample recruitment, attrition rate, and attrition bias. We present a review of the few existing longitudinal surveys in the FRD. In addition, we investigate the potential attrition bias and attrition rates in a panel dataset of flood-affected households in Germany. We find little potential for attrition bias to occur. High attrition rates across longitudinal survey waves are the larger concern. A high attrition rate rapidly depletes the longitudinal sample. To overcome high attrition, longitudinal data should be collected as part of a multisector partnership to allow for sufficient resources to implement sample retention strategies. If flood-specific panels are developed, different sample retention strategies should be applied and evaluated in future research to understand how much-needed longitudinal surveying techniques can be successfully applied to the study of individuals threatened by flooding.
On a smooth complete Riemannian spin manifold with smooth compact boundary, we demonstrate that Atiyah-Singer Dirac operator in depends Riesz continuously on perturbations of local boundary conditions The Lipschitz bound for the map depends on Lipschitz smoothness and ellipticity of and bounds on Ricci curvature and its first derivatives as well as a lower bound on injectivity radius away from a compact neighbourhood of the boundary. More generally, we prove perturbation estimates for functional calculi of elliptic operators on manifolds with local boundary conditions.
Extreme weather resilience has been defined as being based on three pillars: resistance (the ability to lower impacts), recovery (the ability to bounce back), and adaptive capacity (the ability to learn and improve). These resilience pillars are important both before and after the occurrence of extreme weather events. Extreme weather insurance can influence these pillars of resilience depending on how particular insurance mechanisms are structured. We explore how the lessons learnt from the current best insurance practices can improve resilience to extreme weather events. We employ an extensive inventory of private property and agricultural crop insurance mechanisms to conduct a multi-criteria analysis of insurance market outcomes. We draw conclusions regarding the patterns in the best practice from six European countries to increase resilience. We suggest that requirements to buy a bundle extreme weather event insurance with general insurance packages are strengthened and supported with structures to financing losses through public-private partnerships. Moreover, support for low income households through income vouchers could be provided. Similarly, for the agricultural sector we propose moving towards comprehensive crop yield insurance linked to general agricultural subsidies. In both cases a nationally representative body can coordinate the various stakeholders into acting in concert.
We show that the codifference is a useful tool in studying the ergodicity breaking and non-Gaussianity properties of stochastic time series. While the codifference is a measure of dependence that was previously studied mainly in the context of stable processes, we here extend its range of applicability to random-parameter and diffusing-diffusivity models which are important in contemporary physics, biology and financial engineering. We prove that the codifference detects forms of dependence and ergodicity breaking which are not visible from analysing the covariance and correlation functions. We also discuss a related measure of dispersion, which is a nonlinear analogue of the mean squared displacement.
We show that the codifference is a useful tool in studying the ergodicity breaking and non-Gaussianity properties of stochastic time series. While the codifference is a measure of dependence that was previously studied mainly in the context of stable processes, we here extend its range of applicability to random-parameter and diffusing-diffusivity models which are important in contemporary physics, biology and financial engineering. We prove that the codifference detects forms of dependence and ergodicity breaking which are not visible from analysing the covariance and correlation functions. We also discuss a related measure of dispersion, which is a nonlinear analogue of the mean squared displacement.