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Aminolysis induced functionalization of (RAFT) polymer-dithioester with thiols and disulfides
(2020)
A series of polystyrene- and poly(methyl methacrylate)-dithioesters was subjected to aminolysis under ambient atmospheric conditions, i.e., in the presence of oxygen. Polymer disulfide coupling by oxidation occurred within tens of minutes and the yield of disulfide-coupled polymer increased with decreasing polymer molar mass. Oxidation of thiolates is usually an unwanted side reaction, here it is employed to obtain exclusively polymeric mixed disulfides through in situ aminolysis/functionalization in the presence of a thiol. The in situ aminolysis/functionalization in the presence of a disulfide, Ellman's reagent or polymer disulfide, resulted in the exclusive formation of polymer-dithionitrobenzoic acid, which can be further reacted with a thiol to exchange the terminal functionality, or block copolymer with dynamic disulfide linker, respectively.
Ammonium salts are a reservoir of nitrogen on a cometary nucleus and possibly on some asteroids
(2020)
The measured nitrogen-to-carbon ratio in comets is lower than for the Sun, a discrepancy which could be alleviated if there is an unknown reservoir of nitrogen in comets. The nucleus of comet 67P/Churyumov-Gerasimenko exhibits an unidentified broad spectral reflectance feature around 3.2 micrometers, which is ubiquitous across its surface. On the basis of laboratory experiments, we attribute this absorption band to ammonium salts mixed with dust on the surface. The depth of the band indicates that semivolatile ammonium salts are a substantial reservoir of nitrogen in the comet, potentially dominating over refractory organic matter and more volatile species. Similar absorption features appear in the spectra of some asteroids, implying a compositional link between asteroids, comets, and the parent interstellar cloud.
Foraging is risky and involves balancing the benefits of resource acquisition with costs of predation. Optimal foraging theory predicts where, when and how long to forage in a given spatiotemporal distribution of risks and resources. However, significant variation in foraging behaviour and resource exploitation remain unexplained. Using single foragers in artificial landscapes of perceived risks and resources with diminishing returns, we aimed to test whether foraging behaviour and resource exploitation are adjusted to risk level, vary with risk during different components of foraging, and (co)vary among individuals. We quantified foraging behaviour and resource exploitation for 21 common voles (Microtus arvalis). By manipulating ground cover, we created simple landscapes of two food patches varying in perceived risk during feeding in a patch and/or while travelling between patches. Foraging of individuals was variable and adjusted to risk level and type. High risk during feeding reduced feeding duration and food consumption more strongly than risk while travelling. Risk during travelling modified the risk effects of feeding for changes between patches and resulting evenness of resource exploitation. Across risk conditions individuals differed consistently in when and how long they exploited resources and exposed themselves to risk. These among-individual differences in foraging behaviour were associated with consistent patterns of resource exploitation. Thus, different strategies in foraging-under-risk ultimately lead to unequal payoffs and might affect lower trophic levels in food webs. Inter-individual differences in foraging behaviour, i.e. foraging personalities, are an integral part of foraging behaviour and need to be fully integrated into optimal foraging theory.
A biosensor for phenolic compounds based on a chemically modified laccase from Coriolus hirsula immobilized on functionalized screen-printed carbon electrodes (SPCEs) was achieved. Different enzyme modifications and immobilization strategies were analyzed. The electrochemical response of the immobilized laccase on SPCEs modified with carboxyl functionalized multi-walled carbon nanotubes (COOH-MWCNT) was the highest when laccase was aminated prior to the adsorption onto the working electrode. The developed lactase biosensor sensitivity toward different phenolic compounds was assessed to determine the biosensor response with several phenolic compounds. The highest response was obtained for ABTS with a saturation value of I-max = 27.94 mu A. The electrocatalytic efficiency (I-max/K-m(app)) was the highest for ABTS (5588 mu A mu M-1) followed by syringaldazine (3014 mu A.mu M-1). The sensors were considerably stable, whereby 99.5, 82 and 77% of the catalytic response using catechol as substrate was retained after 4, 8 and 10 successive cycles of reuse respectively, with response time average of 5 s for 12 cycles. No loss of activity was observed after 20 days of storage.
A multi-component particle system was developed that combines the properties of white color, white light emission and strong magnetism on the macroscopic and microscopic scale. The system is constituted by combination of an inorganic white core with either hard or soft magnetic properties and a white light emitting MOF. The key towards this achievement is the supraparticulate character constituted by a magnetic core, of either magnetite or alpha-Fe, surrounded by titania and silica nanoparticles of a certain size in a loose structural shell-arrangement as white components and finally the white light emitting metal-organic framework (MOF) EuTb@IFP-1 as building blocks of a core-shell structure. The supraparticles are created by forced assembly of the inorganic compounds and by combining spray-drying and postsynthetic modification by solvothermal chemistry. Thereby, the gap is bridged that homogenous compounds are either strongly magnetic, white in appearance or white light emitting. The composites presented herein inherit these properties intrinsically as electronic properties. The white characteristics are based on all optical properties that enable white: light reflection, refraction, and light emission. This work shifts the paradigm that strong magnetic materials are always expected to be intrinsically dark.
The regional patterns and timing of the Younger Dryas cooling in the North Atlantic realm were complex and are mechanistically incompletely understood. To enhance understanding of regional climate patterns, we present molecular biomarker records at subannual to annual resolution by mass spectrometry imaging (MSI) of sediments from the Lake Meerfelder Maar covering the Allerod-Younger Dryas transition. These analyses are supported by conventional extraction-based molecular-isotopic analyses, which both validate the imaging results and constrain the sources of the target compounds. The targeted fatty acid biomarkers serve as a gauge of the response of the local aquatic and terrestrial ecosystem to climate change. Based on the comparison of our data with existing data from Meerfelder Maar, we analyse the short-term environmental evolution in Western Europe during the studied time interval and confirm the previously reported delayed hydrological response to Greenland cooling. However, despite a detected delay of Western European environmental change of similar to 135 years, our biomarker data show statistically significant correlation with deuterium excess in Greenland ice core at - annual resolution during this time-transgressive cooling. This suggests a coherent atmospheric forcing across the North Atlantic realm during this transition. We propose that Western European cooling was postponed due to major reorganization of the westerlies that were intermittently forcing warmer and wetter air masses from lower latitudes to Western Europe and thus resulted in delayed cooling relative to Greenland.
This paper aims to investigate the possibility to include aspects of forgetting into business process modeling. To date, there is no possibility to model forgotten or to-be- forgotten elements beyond the mere deletion. On a first attempt, we focus on the individual level and model knowledge transformation within a single person. Using the Knowledge Model Description Language, we propose ways to include different forms of forgetting into the realm of modeling tools. Using data from an experimental setting within an assembly line production environment, the usability of those new modeling tools is tested. So far, the applicability of modeling features for forgetting on the individual level is mostly restricted to a research context. However, clear requirements to transfer the tools onto the team- and organizational level are set out.
Droughts in tropical South America have an imminent and severe impact on the Amazon rainforest and affect the livelihoods of millions of people. Extremely dry conditions in Amazonia have been previously linked to sea surface temperature (SST) anomalies in the adjacent tropical oceans. Although the sources and impacts of such droughts have been widely studied, establishing reliable multi-year lead statistical forecasts of their occurrence is still an ongoing challenge. Here, we further investigate the relationship between SST and rainfall anomalies using a complex network approach. We identify four ocean regions which exhibit the strongest overall SST correlations with central Amazon rainfall, including two particularly prominent regions in the northern and southern tropical Atlantic. Based on the time-dependent correlation between SST anomalies in these two regions alone, we establish a new early-warning method for droughts in the central Amazon basin and demonstrate its robustness in hindcasting past major drought events with lead-times up to 18 months.
An effective strategy for combining variance- and distribution-based global sensitivity analysis
(2020)
We present a new strategy for performing global sensitivity analysis capable to estimate main and interaction effects from a generic sampling design. The new strategy is based on a meaningful combination of varianceand distribution-based approaches. The strategy is tested on four analytic functions and on a hydrological model. Results show that the analysis is consistent with the state-of-the-art Saltelli/Jansen formula but to better quantify the interaction effect between the input factors when the output distribution is skewed. Moreover, the estimation of the sensitivity indices is much more robust requiring a smaller number of simulations runs. Specific settings and alternative methods that can be integrated in the new strategy are also discussed. Overall, the strategy is considered as a new simple and effective tool for performing global sensitivity analysis that can be easily integrated in any environmental modelling framework.