Rhodium-catalysed reductive amination for the synthesis of tertiary amines

A procedure for the synthesis of tertiary amines via reductive amination of aldehydes with molecular hydrogen as a reducing agent using homogeneous rhodium catalysis is presented. Using an amine to aldehyde ratio of 4/1 enabled the synthesis of tertiary amines from nine different aldehydes and nine different secondary amines with selectivities up to 99% and turnover frequencies (TOF) up to 7200 h−1. The reaction showed a high tolerance against alcohol and ester functions allowing the formation of multifunctional molecules. In addition, secondary amines can also be produced by this synthesis. For all compounds, activities were determined by hydrogen gas-uptake. In order to increase the sustainability and efficiency of the procedure, a dosing strategy has been successfully developed. Using the determined reaction indicators enabled the stoichiometric use of aldehydes and amines without significant loss of selectivity

Divergent occurrences of juvenile and adult trees are explained by both environmental change and ontogenetic effects

Recent climate warming has fueled interest into climate-driven range shifts of tree species. A common approach to detect range shifts is to compare the divergent occurrences between juvenile and adult trees along environmental gradients using static data. Divergent occurrences between life stages can, however, also be caused by ontogenetic effects. These include shifts of the viable environmental conditions throughout development (?ontogenetic niche shift') as well as demographic dependencies that constrain the possible occurrence of subsequent life stages. Whether ontogenetic effects are an important driver of divergent occurrences between juvenile and adult trees along large-scale climatic gradients is largely unknown. It is, however, critical in evaluating whether impacts of environmental change can be inferred from static data on life stage occurrences. Here, we first show theoretically, using a two-life stage simulation model, how both temporal range shift and ontogenetic effects can lead to similar divergent occurrences between adults and juveniles (juvenile divergence). We further demonstrate that juvenile divergence can unambiguously be attributed to ontogenetic effects, when juveniles diverge from adults in opposite direction to their temporal shift along the environmental gradient. Second, to empirically test whether ontogenetic effects are an important driver of divergent occurrences across Europe, we use repeated national forest inventories from Sweden, Germany and Spain to assess juvenile divergence and temporal shift for 40 tree species along large-scale climatic gradients. About half of the species-country combinations had significant juvenile divergences along heat sum and water availability gradients. Only a quarter of the tree species had significant detectable temporal shifts within the observation period. Furthermore, significant juvenile divergences were frequently associated with opposite temporal shifts, indicating that ontogenetic effects are a relevant cause of divergent occurrences between life stages. Our study furthers the understanding of ontogenetic effects and challenges the practice of inferring climate change impacts from static data.Universidad de AlcaláMinisterio de Ciencia e InnovaciónAgencia Estatal de Investigació

Glycinergic interneurons are functionally integrated into the inspiratory network of mouse medullary slices

Neuronal activity in the respiratory network is functionally dependent on inhibitory synaptic transmission. Using two-photon excitation microscopy, we analyzed the integration of glycinergic neurons in the isolated inspiratory pre-Bötzinger complex-driven network of the rhythmic slice preparation. Inspiratory (96%) and ‘tonic’ expiratory neurons (4%) were identified via an increase or decrease, respectively, of the cytosolic free calcium concentration during the inspiratory-related respiratory burst. Furthermore, in BAC-transgenic mice expressing EGFP under the control of the GlyT2-promoter, 50% of calcium-imaged inspiratory neurons were glycinergic. Inspiratory bursting of glycinergic neurons in the slice was confirmed by whole-cell recording. We also found glycinergic neurons that receive phasic inhibition from other glycinergic neurons. Our calcium imaging data show that glycinergic neurons comprise a large population of inspiratory neurons in the pre-Bötzinger complex-driven network of the rhythmic slice preparation

The Intelligent Coaching Space: A Demonstration

de Kok I, Hülsmann F, Waltemate T, et al. The Intelligent Coaching Space: A Demonstration. In: Beskow J, Peters C, Castellano G, O'Sullivan C, Leite I, Kopp S, eds. Intelligent Virtual Agents: 17th International Conference on Intelligent Virtual Agents from August 27th to 30th in Stockholm, Sweden. Lecture Notes in Computer Science. Vol 10498. Cham: Springer; 2017: 105-108

Aspects of Explanations for Optimization-Based Energy System Models

The transition towards a renewable energy system presents numerous challenges, demanding extensive decision-making processes. Optimization-based energy system models (ESMs) are valuable tools to facilitate these decisions. However, these models often prove too intricate and expansive for decision-makers, such as CEOs, politicians, or citizens, who typically lack expertise in ESMs. Consequently, there is a pressing need for explanations to bridge the gap between the complexity of ESM results and decision-makers comprehension, allowing them to discern potential disparities between their objectives and the model’s assumptions. This thesis focuses on various explanations for optimization-based ESMs. Initially, we explore explanations from psychological and philosophical perspectives to identify the fundamental concepts necessary for creating comprehensive explanations and elucidate the key factors essential for these explanations to be deemed adequate. Armed with these foundational concepts, we assess the current state-of-the-art in explaining ESMs, identifying existing shortcomings in explanation methodologies. We draw parallels between the challenges faced by the ESM domain and the field of machine learning, particularly in the domain of explainable artificial intelligence (XAI), which is dedicated to developing methods to enhance the explainability of machine learning models. This thesis delves into three distinct approaches from the abovementioned domains to address these challenges and enhance explanations for optimization-based ESMs. Firstly, we adopt an approach from XAI to ESMs to overcome two prevalent shortcomings in ESM explanations: elucidating the impact of high-dimensional input data and tailoring explanation complexities to different target audiences. Given the key role of causality in crafting explanations, we explore the utilization of causal graphical models for explaining ESMs. Finally, we design an interactive approach to facilitate hands-on learning of ESMs, focusing on the example of energy transition, and evaluate the efficacy of this approach within the context of a graduate-level university course

A Natural Language Interface for an Energy System Model

Energy system models are widely used for operation and expansion planning, scaling from single houses up to supranational energy grids. They can provide essential input for decision makers. These are, however, often non-technical persons and thus unfamiliar with mathematical modeling, which makes them reliant on others to explain the model results to them. In order to make energy system models more directly accessible, we introduce a chatbot that enables also non-expert users to interact with an energy system model through natural language. Built with state-of-the-art natural language processing tools, it allows to manipulate the model inputs and can interactively answer questions about the results, both in free-form text and via structured plots. We present example interactions for a model of the German energy transition