Cationic zinc enolates as highly active catalysts for acrylate polymerization

Unprecedented cationic zinc enolates have been generated by a novel activation route involving the amido to imino ligand transformation with B(C6F5)3, structurally characterized, and utilized as highly active catalysts for the production of high molecular weight polyacrylates at ambient temperature

The Possibility of Consensus Regarding Climate Change Adaptation Policies in Agriculture and Forestry among Stakeholder Groups in the Czech Republic

As ongoing research efforts contribute to elucidating the consequences of climate change as well as adaptation and mitigation options, aligning the current research knowledge with stakeholder opinions and perceptions remains critical for adopting effective climate change policies. This paper utilizes an interactive survey to (1) address the aforementioned gap in studies involving three groups of stakeholders and opinion makers and (2) perform a comparative primary study of the climate change assumptions, risk perceptions, policy preferences, observations, and knowledge of Czech farmers, governmental policy-makers and researchers. This study shows that the stakeholder groups agree that the climate is clearly changing, attribute this change mostly to man-made causes and expect the negative effects to either prevail or be unevenly geographically distributed. The large majority of all three groups consider unmitigated climate change a major threat even by 2050 and agree that preparing in advance is the best sectoral strategy. Importantly, while investment in adaptation measures is considered the most efficient tool for accelerating the implementation of adaptation measures, the CAP and EU rules (as valid in 2016) are believed to hinder such measures. The results of this study have ramifications for the wider region of Central Europe

Synthesis of mixed alkali-metal-zinc enolate complexes derived from 2,4,6-trimethylacetophenone: new inverse crown structures

The solution and solid-state characterization of two new mixed alkali-metal−zinc enolate compounds is reported. These compounds are prepared by reaction of the relevant mixed-metal base [MZn(HMDS)3] (M = Na, K; HMDS = 1,1,1,3,3,3-hexamethyldisilazide) with a stoichiometric amount of the sterically demanding ketone 2,4,6-trimethylacetophenone. Thus, the new mixed-metal enolate compounds [Na2Zn2{OC(=CH2)Mes}6{OC(CH3)Mes}2] (2) and [K2Zn2{OC(=CH2)Mes}6(CH3Ph)2] (3) are obtained for M = Na, K, respectively. X-ray crystallographic studies reveal that both compounds adopt the same structural motif, which define them as inverse crown complexes, a cationic eight-membered [(MOZnO)2]2+ ring which hosts in its core two additional enolate ligands. Each Zn center is bonded to four anionic enolate ligands framing the structure, whereas the alkali metals form much weaker interactions with the oxygen atoms and complete their coodination sphere by bonding to a neutral molecule, an unenolised ketone for M = Na or toluene for M = K

Variability in the water footprint of arable crop production across European regions

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Performance of 13 crop simulation models and their ensemble for simulating four field crops in Central Europe

The main aim of the current study was to present the abilities of widely used crop models to simulate four different field crops (winter wheat, spring barley, silage maize and winter oilseed rape). The 13 models were tested under Central European conditions represented by three locations in the Czech Republic, selected using temperature and precipitation gradients for the target crops in this region. Based on observed crop phenology and yield from 1991 to 2010, performances of individual models and their ensemble were analyzed. Modelling of anthesis and maturity was generally best simulated by the ensemble median (EnsMED) compared to the ensemble mean and individual models. The yield was better simulated by the best models than estimated by an ensemble. Higher accuracy was achieved for spring crops, with the best results for silage maize, while the lowest accuracy was for winter oilseed rape according to the index of agreement (IA). Based on EnsMED, the root mean square errors (RMSEs) for yield was 1365 kg/ha for winter wheat, 1105 kg/ha for spring barley, 1861 kg/ha for silage maize and 969 kg/ha for winter oilseed rape. The AQUACROP and EPIC models performed best in terms of spread around the line of best fit (RMSE, IA). In some cases, the individual models failed. For crop rotation simulations, only models with reasonable accuracy (i.e. without failures) across all included crops within the target environment should be selected. Application crop models ensemble is one way to increase the accuracy of predictions, but lower variability of ensemble outputs was confirmed