Pyrroloquinoline Quinone Aza-Crown Ether Complexes as Biomimetics for Lanthanide and Calcium Dependent Alcohol Dehydrogenases**

Understanding the role of metal ions in biology can lead to the development of new catalysts for several industrially important transformations. Lanthanides are the most recent group of metal ions that have been shown to be important in biology, that is, in quinone-dependent methanol dehydrogenases (MDH). Here we evaluate a literature-known pyrroloquinoline quinone (PQQ) and 1-aza-15-crown-5 based ligand platform as scaffold for Ca$^{2+}$, Ba$^{2+}$, La$^{3+}$ and Lu$^{3+}$ biomimetics of MDH and we evaluate the importance of ligand design, charge, size, counterions and base for the alcohol oxidation reaction using NMR spectroscopy. In addition, we report a new straightforward synthetic route (3 steps instead of 11 and 33 % instead of 0.6 % yield) for biomimetic ligands based on PQQ. We show that when studying biomimetics for MDH, larger metal ions and those with lower charge in this case promote the dehydrogenation reaction more effectively and that this is likely an effect of the ligand design which must be considered when studying biomimetics. To gain more information on the structures and impact of counterions of the complexes, we performed collision induced dissociation (CID) experiments and observe that the nitrates are more tightly bound than the triflates. To resolve the structure of the complexes in the gas phase we combined DFT-calculations and ion mobility measurements (IMS). Furthermore, we characterized the obtained complexes and reaction mixtures using Electron Paramagnetic Resonance (EPR) spectroscopy and show the presence of a small amount of quinone-based radical

A Semantic Reasoning Method Towards Ontological Model for Automated Learning Analysis

Semantic reasoning can help solve the problem of regulating the evolving and static measures of knowledge at theoretical and technological levels. The technique has been proven to enhance the capability of process models by making inferences, retaining and applying what they have learned as well as discovery of new processes. The work in this paper propose a semantic rule-based approach directed towards discovering learners interaction patterns within a learning knowledge base, and then respond by making decision based on adaptive rules centred on captured user profiles. The method applies semantic rules and description logic queries to build ontology model capable of automatically computing the various learning activities within a Learning Knowledge-Base, and to check the consistency of learning object/data types. The approach is grounded on inductive and deductive logic descriptions that allows the use of a Reasoner to check that all definitions within the learning model are consistent and can also recognise which concepts that fit within each defined class. Inductive reasoning is practically applied in order to discover sets of inferred learner categories, while deductive approach is used to prove and enhance the discovered rules and logic expressions. Thus, this work applies effective reasoning methods to make inferences over a Learning Process Knowledge-Base that leads to automated discovery of learning patterns/behaviour

Teachers as Educational Innovators in Inquiry-Based Science Teaching and Learning

This chapter describes inquiry-based science teaching and learning (IBST/L) pilots designed by teachers during a professional development programme. There is research-based evidence that IBSL/T may promote students’ learning and their motivation to learn science, and therefore it is beneficial to familiarise the teachers with this approach. Building on teachers’ existing expertise in designing their teaching, the programme introduced theoretical aspects of the IBST/L approach and its research-based benefits for students’ motivation, interest and science learning. The course aimed to support teachers as educational innovators in the process of designing and testing IBST/L pilots, during which they collaboratively reflected on and revised their existing practices. The data of this piece of research consists of the teachers’ poster presentations of their IBST/L pilots and a video recording of the reflection session. The content analysis revealed that the pilots’ structure seemed traditional but encompassed some IBST/L features. It is concluded that teacher educators need to understand teachers’ views of IBST/L in order to more effectively support planning and reflection.This chapter describes inquiry-based science teaching and learning (IBST/L) pilots designed by teachers during a professional development programme. There is research-based evidence that IBSL/T may promote students’ learning and their motivation to learn science, and therefore it is beneficial to familiarise the teachers with this approach. Building on teachers’ existing expertise in designing their teaching, the programme introduced theoretical aspects of the IBST/L approach and its research-based benefits for students’ motivation, interest and science learning. The course aimed to support teachers as educational innovators in the process of designing and testing IBST/L pilots, during which they collaboratively reflected on and revised their existing practices. The data of this piece of research consists of the teachers’ poster presentations of their IBST/L pilots and a video recording of the reflection session. The content analysis revealed that the pilots’ structure seemed traditional but encompassed some IBST/L features. It is concluded that teacher educators need to understand teachers’ views of IBST/L in order to more effectively support planning and reflection.Peer reviewe

Updated merged SAGE-CCI-OMPS+ dataset for the evaluation of ozone trends in the stratosphere

In this paper, we present the updated SAGE-CCI-OMPS+ climate data record of monthly zonal mean ozone profiles. This dataset covers the stratosphere and combines measurements by nine limb and occultation satellite instruments – SAGE II (Stratospheric Aerosol and Gases Experiment II), OSIRIS (Optical Spectrograph and InfraRed Imaging System), MIPAS (Michelson Interferometer for Passive Atmospheric Sounding), SCIAMACHY (SCanning Imaging Spectrometer for Atmospheric CHartographY), GOMOS (Global Ozone Monitoring by Occultation of Stars), ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer), OMPS-LP (Ozone Monitor Profiling Suite Limb Profiler), POAM (Polar Ozone and Aerosol Measurement) III, and SAGE III/ISS (Stratospheric Aerosol and Gases Experiment III on the International Space Station). Compared to the original version of the SAGE-CCI-OMPS dataset (Sofieva et al., 2017b), the update includes new versions of MIPAS, ACE-FTS, and OSIRIS datasets and introduces data from additional sensors (POAM III and SAGE III/ISS) and retrieval processors (OMPS-LP). In this paper, we show detailed intercomparisons of ozone profiles from different instruments and data versions, with a focus on the detection of possible drifts in the datasets. The SAGE-CCI-OMPS+ dataset has a better coverage of polar regions and of the upper troposphere and the lower stratosphere (UTLS) than the previous dataset. We also studied the influence of including new datasets on ozone trends, which are estimated using multiple linear regression. The changes in the merged dataset do not change the overall morphology of post-1997 ozone trends; statistically significant trends are observed in the upper stratosphere. The largest changes in ozone trends are observed in polar regions, especially in the Southern Hemisphere. The updated SAGE-CCI-OMPS+ dataset contains profiles of deseasonalized anomalies and ozone concentrations from 1984 to 2021, in 10∘ latitude bins from 90∘ S to 90∘ N and in the altitude range from 10 to 50 km. The dataset is open access and available at https://climate.esa.int/en/projects/ozone/data/ (last access: 9 March 2023) and at ftp://[email protected]/esacci (ESA Climate Office; last access: 9 March 2023).</p

Overview and update of the SPARC Data Initiative: comparison of stratospheric composition measurements from satellite limb sounders

The Stratosphere-troposphere Processes and their Role in Climate (SPARC) Data Initiative (SPARC, 2017) performed the first comprehensive assessment of currently available stratospheric composition measurements obtained from an international suite of space-based limb sounders. The initiative's main objectives were (1) to assess the state of data availability, (2) to compile time series of vertically resolved, zonal monthly mean trace gas and aerosol fields, and (3) to perform a detailed intercomparison of these time series, summarizing useful information and highlighting differences among datasets. The datasets extend over the region from the upper troposphere to the lower mesosphere (300–0.1 hPa) and are provided on a common latitude–pressure grid. They cover 26 different atmospheric constituents including the stratospheric trace gases of primary interest, ozone (O3) and water vapor (H2O), major long-lived trace gases (SF6, N2O, HF, CCl3F, CCl2F2, NOy), trace gases with intermediate lifetimes (HCl, CH4, CO, HNO3), and shorter-lived trace gases important to stratospheric chemistry including nitrogen-containing species (NO, NO2, NOx, N2O5, HNO4), halogens (BrO, ClO, ClONO2, HOCl), and other minor species (OH, HO2, CH2O, CH3CN), and aerosol. This overview of the SPARC Data Initiative introduces the updated versions of the SPARC Data Initiative time series for the extended time period 1979–2018 and provides information on the satellite instruments included in the assessment: LIMS, SAGE I/II/III, HALOE, UARS-MLS, POAM II/III, OSIRIS, SMR, MIPAS, GOMOS, SCIAMACHY, ACE-FTS, ACE-MAESTRO, Aura-MLS, HIRDLS, SMILES, and OMPS-LP. It describes the Data Initiative's top-down climatological validation approach to compare stratospheric composition measurements based on zonal monthly mean fields, which provides upper bounds to relative inter-instrument biases and an assessment of how well the instruments are able to capture geophysical features of the stratosphere. An update to previously published evaluations of O3 and H2O monthly mean time series is provided. In addition, example trace gas evaluations of methane (CH4), carbon monoxide (CO), a set of nitrogen species (NO, NO2, and HNO3), the reactive nitrogen family (NOy), and hydroperoxyl (HO2) are presented. The results highlight the quality, strengths and weaknesses, and representativeness of the different datasets. As a summary, the current state of our knowledge of stratospheric composition and variability is provided based on the overall consistency between the datasets. As such, the SPARC Data Initiative datasets and evaluations can serve as an atlas or reference of stratospheric composition and variability during the “golden age” of atmospheric limb sounding. The updated SPARC Data Initiative zonal monthly mean time series for each instrument are publicly available and accessible via the Zenodo data archive (Hegglin et al., 2020)