Formic Acid Dehydrogenation by a Cyclometalated κ3-CNN Ruthenium Complex

Hydrogen utilization as a sustainable energy vector is of growing interest. We report herein a cyclometalated ruthenium complex [Ru(κ3-CNN)(dppb)Cl], originally described by Baratta, to be active in the selective dehydrogenation (DH) of formic acid (FA) to H2 and CO2. TON's of more than 10000 were achieved under best conditions without observation of CO (detection limit 10 ppm). The distinguished behavior of the catalyst was explored varying the starting conditions. Our observation revealed the complex [Ru(κ3-CNN)(dppb)(OOCH)] as key species in the catalytic cycle. © 2020 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA

Genetic population structure of the monogenean parasite Gyrodactylus thymalli and its host European grayling (Thymallus thymallus) in a large Norwegian lake

Understanding how populations are structured in space and time is a central question in evolutionary biology. Parasites and their hosts are assumed to evolve together, however, detailed understanding of mechanisms leading to genetic structuring of parasites and their hosts are lacking. As a parasite depends on its host, studying the genetic structure of both parasite and host can reveal important insights into these mechanisms. Here, genetic structure of the monogenean parasite Gyrodactylus thymalli and its host the European grayling (Thymallus thymallus) was investigated in 10 tributaries draining into the large Lake Mjøsa in Norway. The population genetic structure of spawning grayling was studied using microsatellite genotyping, while G. thymalli was studied by sequencing a mitochondrial DNA gene (dehydrogenase subunit 5). Two main genetic clusters were revealed in grayling, one cluster comprising grayling from the largest spawning population, while the remaining tributaries formed the second cluster. For both taxa, some genetic differentiation was observed among tributaries, but there was no clear isolation-by-distance signature. The structuring was stronger for the host than for the parasite. These results imply that moderate to high levels of gene flow occur among the sub-populations of both taxa. The high parasite exchange among tributaries could result from a lack of strong homing behavior in grayling as well as interactions among individual fish outside of the spawning season, leading to frequent mixing of both host and parasite.publishedVersio

Developing effective catalyst for mine methane conversion to hydrogen-containing gas

The Ni/Ce[1-x]La[x]O[y] and Ni/Ce[1-x]La[x]O[y]/Al[2]O[3] catalysts (x=0-1) were prepared for the mine methane conversion to hydrogen-containing gas. The influence of the support composition on the physicochemical characteristics of the catalysts and their activity in autothermal reforming of methane (ATR of CH[4]) was studied. It was shown that the dispersion of the Ni active component was enhanced with growth of molar ratio of La in the support composition that leads to the increase in catalyst stability in ATR of CH[4]. The Ni/Ce[1-x]La[x]O[y]/Al[2]O[3] catalysts in comparison to the Ni/Ce[1]-xLa[x]O[y] provide higher H[2] yield: at 850oC it is equal to 65-75%

Morphology, Optical Properties and Photocatalytic Activity of Photo- and Plasma-Deposited Au and Au/Ag Core/Shell Nanoparticles on Titania Layers

Titania is a promising material for numerous photocatalytic reactions such as water splitting and the degradation of organic compounds (e.g., methanol, phenol). Its catalytic performance can be significantly increased by the addition of co-catalysts. In this study, Au and Au/Ag nanoparticles were deposited onto mesoporous titania thin films using photo-deposition (Au) and magnetron-sputtering (Au and Au/Ag). All samples underwent comprehensive structural characterization by grazing incidence X-ray diffraction (XRD), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). Nanoparticle distributions and nanoparticle size distributions were correlated to the deposition methods. Light absorption measurements showed features related to diffuse scattering, the band gap of titania and the local surface plasmon resonance of the noble metal nanoparticles. Further, the photocatalytic activities were measured using methanol as a hole scavenger. All nanoparticle-decorated thin films showed significant performance increases in hydrogen evolution under UV illumination compared to pure titania, with an evolution rate of up to 372 μL H2 h−1 cm−2 representing a promising approximately 12-fold increase compared to pure titania

Holographic optogenetic stimulation with calcium imaging as an all optical tool for cardiac electrophysiology

All optical approaches to control and read out the electrical activity in a cardiac syncytium can improve our understanding of cardiac electrophysiology. Here, we demonstrate optogenetic stimulation of cardiomyocytes with high spatial precision using light foci generated with a ferroelectric spatial light modulator. Computer generated holograms binarized by bidirectional error diffusion create multiple foci with more even intensity distribution compared with thresholding approach. We evoke the electrical activity of cardiac HL1 cells expressing the channelrhodopsin-2 variant, ChR2(H134R) using single and multiple light foci and at the same time visualize the action potential using a calcium sensitive indicator called Cal-630. We show that localized regions in the cardiac monolayer can be stimulated enabling us to initiate signal propagation from a precise location. Furthermore, we demonstrate that probing the cardiac cells with multiple light foci enhances the excitability of the cardiac network. This approach opens new applications in manipulating and visualizing the electrical activity in a cardiac syncytium

Automated Medical Coding on MIMIC-III and MIMIC-IV: A Critical Review and Replicability Study

Medical coding is the task of assigning medical codes to clinical free-text documentation. Healthcare professionals manually assign such codes to track patient diagnoses and treatments. Automated medical coding can considerably alleviate this administrative burden. In this paper, we reproduce, compare, and analyze state-of-the-art automated medical coding machine learning models. We show that several models underperform due to weak configurations, poorly sampled train-test splits, and insufficient evaluation. In previous work, the macro F1 score has been calculated sub-optimally, and our correction doubles it. We contribute a revised model comparison using stratified sampling and identical experimental setups, including hyperparameters and decision boundary tuning. We analyze prediction errors to validate and falsify assumptions of previous works. The analysis confirms that all models struggle with rare codes, while long documents only have a negligible impact. Finally, we present the first comprehensive results on the newly released MIMIC-IV dataset using the reproduced models. We release our code, model parameters, and new MIMIC-III and MIMIC-IV training and evaluation pipelines to accommodate fair future comparisons.Comment: 11 pages, 6 figures, to be published in Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '23), July 23--27, 2023, Taipei, Taiwa

Efficient implementation of atom-density representations

Physically motivated and mathematically robust atom-centered representations of molecular structures are key to the success of modern atomistic machine learning. They lie at the foundation of a wide range of methods to predict the properties of both materials and molecules and to explore and visualize their chemical structures and compositions. Recently, it has become clear that many of the most effective representations share a fundamental formal connection. They can all be expressed as a discretization of n-body correlation functions of the local atom density, suggesting the opportunity of standardizing and, more importantly, optimizing their evaluation. We present an implementation, named librascal, whose modular design lends itself both to developing refinements to the density-based formalism and to rapid prototyping for new developments of rotationally equivariant atomistic representations. As an example, we discuss smooth overlap of atomic position (SOAP) features, perhaps the most widely used member of this family of representations, to show how the expansion of the local density can be optimized for any choice of radial basis sets. We discuss the representation in the context of a kernel ridge regression model, commonly used with SOAP features, and analyze how the computational effort scales for each of the individual steps of the calculation. By applying data reduction techniques in feature space, we show how to reduce the total computational cost by a factor of up to 4 without affecting the model’s symmetry properties and without significantly impacting its accuracy