Neuromorphic intermediate representation: A unified instruction set for interoperable brain-inspired computing.

Spiking neural networks and neuromorphic hardware platforms that simulate neuronal dynamics are getting wide attention and are being applied to many relevant problems using Machine Learning. Despite a well-established mathematical foundation for neural dynamics, there exists numerous software and hardware solutions and stacks whose variability makes it difficult to reproduce findings. Here, we establish a common reference frame for computations in digital neuromorphic systems, titled Neuromorphic Intermediate Representation (NIR). NIR defines a set of computational and composable model primitives as hybrid systems combining continuous-time dynamics and discrete events. By abstracting away assumptions around discretization and hardware constraints, NIR faithfully captures the computational model, while bridging differences between the evaluated implementation and the underlying mathematical formalism. NIR supports an unprecedented number of neuromorphic systems, which we demonstrate by reproducing three spiking neural network models of different complexity across 7 neuromorphic simulators and 4 digital hardware platforms. NIR decouples the development of neuromorphic hardware and software, enabling interoperability between platforms and improving accessibility to multiple neuromorphic technologies. We believe that NIR is a key next step in brain-inspired hardware-software co-evolution, enabling research towards the implementation of energy efficient computational principles of nervous systems. NIR is available at neuroir.org.

Mechanical testing dataset of cast copper alloys for the purpose of digitalization.

This data article presents a set of primary, analyzed, and digitalized mechanical testing datasets for nine copper alloys. The mechanical testing methods including the Brinell and Vickers hardness, tensile, stress relaxation, and low-cycle fatigue (LCF) testing were performed according to the DIN/ISO standards. The obtained primary testing data (84 files) mainly contain the raw measured data along with the testing metadata of the processes, materials, and testing machines. Five secondary datasets were also provided for each testing method by collecting the main meta- and measurement data from the primary data and the outputs of data analyses. These datasets give materials scientists beneficial data for comparative material selection analyses by clarifying the wide range of mechanical properties of copper alloys, including Brinell and Vickers hardness, yield and tensile strengths, elongation, reduction of area, relaxed and residual stresses, and LCF fatigue life. Furthermore, both the primary and secondary datasets were digitalized by the approach introduced in the research article entitled "Toward a digital materials mechanical testing lab" [1]. The resulting open-linked data are the machine-processable semantic descriptions of data and their generation processes and can be easily queried by semantic searches to enable advanced data-driven materials research.

Multi-year aboveground data of minirhizotron facilities in Selhausen.

Improved understanding of crops' response to soil water stress is important to advance soil-plant system models and to support crop breeding, crop and varietal selection, and management decisions to minimize negative impacts. Studies on eco-physiological crop characteristics from leaf to canopy for different soil water conditions and crops are often carried out at controlled conditions. In-field measurements under realistic field conditions and data of plant water potential, its links with CO2 and H2O gas fluxes, and crop growth processes are rare. Here, we presented a comprehensive data set collected from leaf to canopy using sophisticated and comprehensive sensing techniques (leaf chlorophyll, stomatal conductance and photosynthesis, canopy CO2 exchange, sap flow, and canopy temperature) including detailed crop growth characteristics based on destructive methods (crop height, leaf area index, aboveground biomass, and yield). Data were acquired under field conditions with contrasting soil types, water treatments, and different cultivars of wheat and maize. The data from 2016 up to now will be made available for studying soil/water-plant relations and improving soil-plant-atmospheric continuum models.

Seedling root system adaptation to water availability during maize domestication and global expansion.

The maize root system has been reshaped by indirect selection during global adaptation to new agricultural environments. In this study, we characterized the root systems of more than 9,000 global maize accessions and its wild relatives, defining the geographical signature and genomic basis of variation in seminal root number. We demonstrate that seminal root number has increased during maize domestication followed by a decrease in response to limited water availability in locally adapted varieties. By combining environmental and phenotypic association analyses with linkage mapping, we identified genes linking environmental variation and seminal root number. Functional characterization of the transcription factor ZmHb77 and in silico root modeling provides evidence that reshaping root system architecture by reducing the number of seminal roots and promoting lateral root density is beneficial for the resilience of maize seedlings to drought.

Metal- and solvent-free domino reaction of 2-isocyanophenol esters to benzoxazines: long-range 1,5-acyl migration on 1,4-diazabutatriene.

The first example of intramolecular nucleophilic addition of 1,4-diazabutatriene to ester is disclosed. This approach provides a facile and versatile synthesis for functionalized 2H-1,4-benzoxazines under metal-, reagent-, and solvent-free conditions. Experimental and computational studies revealed the pivotal role of 1,5-acyl migration as the self-catalytic step in the reaction selectivity.

Rhodium-Catalyzed Enantioselective Cyclization of 2-Allenylbenzoxazoles.

The enantioselective rhodium-catalyzed cyclization of 2-allenylbenzoxazoles to the corresponding vinyl-functionalized, fused heterocyclic structures is reported. The presented method offers several advantages, including the use of low catalyst loadings, commercially available catalyst precursors, and mild reaction conditions. Due to its broad scope, scalability, and valuable products, we consider this methodology to be a useful tool for the construction of benzoxazole-containing building blocks.

Inorganic Bottlebrush and Comb Polymers as a Platform for Supersoft, Solvent-Free Elastomers.

Due to their unique rheological and mechanical properties, bottlebrush polymers are inimitable components of biological and synthetic systems such as cartilage and ultrasoft elastomers. However, while their rheological properties can be precisely controlled through their macromolecular structures, the current chemical spectrum available is limited to a handful of synthetic polymers with aliphatic carbon backbones. Herein we design and synthesize a series of inorganic bottlebrush polymers based on a unique combination of polydimethylsiloxane (PDMS) and polyphosphazene (PPz) chemistry. This non-carbon-based platform allows for simple variation of the significant architectural dimensions of bottlebrush-polymer-based elastomers. Grafting PDMS to PPz and vice versa also allows us to further exploit the unique properties of these polymers combined in a single material. These novel hybrid bottlebrush polymers were cured to give supersoft, solvent-free elastomers. We systematically studied the effect of architectural parameters and chemical functionality on their rheological properties. Besides forming supersoft elastomers, the energy dissipation characteristics of the elastomers were observed to be considerably higher than those for PDMS-based elastomers. Hence this work introduces a robust synthetic platform for solvent-free supersoft elastomers with potential applications as biomimetic damping materials.

A Tandem Hydroformylation-Organocatalyzed Friedel-Crafts Reaction for the Synthesis of Diindolylmethanes.

Herein, we present an efficient and atom-economic tandem hydroformylation organocatalyzed Friedel-Crafts reaction sequence for the synthesis of diindolylmethanes. Classic syntheses have relied on (Lewis) acid activation of aldehydes, which are often not commercially available and rather sensitive in handling. In contrast, the combination of rhodium-catalyzed hydroformylation and subsequent organocatalytic activation of the in-situ formed aldehydes allows the use of readily available and stable alkenes with various functional groups while avoiding acidic conditions to expand the range of available diindolylmethanes. A broad scope of diindolylmethanes was prepared in yields up to 85 % demonstrates the utility of the presented method.

Carbonylation as a Key Step in New Tandem Reactions - A Route to BODIPYs.

Herein, a highly efficient five-step reaction sequence to BODIPYs is presented. The key step is the combination of transition metal-catalyzed in-situ generation of aldehydes and their subsequent organocatalytic activation to yield dipyrromethanes, which are further converted to the corresponding BODIPY. Classic syntheses towards BODIPYs have relied on aldehydes or acid chlorides, which are often not commercially available and rather sensitive to handle. The presented approach starts from readily available and stable alkenes or aryl-bromides, which allows to extend the range of readily available BODIPYs that can be tailored for their specific use. The synthesis of 55 derivatives with overall yields of up to 78 % demonstrates the wide applicability and advantages of the presented method.

Rhodium-Catalyzed Allylic Addition as an Atom-Efficient Approach in Total Synthesis.

ConspectusFinding efficient synthetic methods for the asymmetric synthesis of complex molecules has always been of interest to organic chemists. Creating and controlling the stereochemistry of stereogenic centers bearing branched allylic moieties in organic molecules using a catalytic process is an attractive and successful method for the synthesis of several natural products and medicinally important compounds. Remarkable progress toward their synthesis has been achieved via transition-metal catalysis, especially in the case of allylic substitution and allylic C-H oxidation chemistry. However, for allylic substitution the preinstallation of a leaving group is essential, and for allylic C-H oxidation, stoichiometric amounts of oxidant are required. Besides that, the control of regioselectivity with these methods is often problematic because the linear product can be produced as a major isomer. Our research group has developed a regioselective, enantioselective, and atom economic route toward the more valuable branched product via a Rh-catalyzed coupling of easily accessible alkynes or the double-bond isomeric allenes with pronucleophiles. It was demonstrated that, using this new approach, it is possible to add different pronucleophiles to alkynes or allenes to form branched allylic moieties through C-C and C-heteroatom bond formation. Since new organic reactions offer new opportunities in chemical synthesis and the benchmark for new synthetic methods is their application in target-oriented synthesis, we have demonstrated several successful syntheses of natural products and medicinally relevant targets. For example, in the total syntheses of Quercuslactones, Helicascolides A-C, Epothilone D, Homolargazole, and Thailandepsin B, the Rh-catalyzed hydro-oxycarbonylation of allenes was used as key step via C-O bond formation. Remarkably, the Rh-catalyzed C2-symmetric dimerization strategy was used to synthesize the complex molecules Clavosolide A and Vermiculine, leading to an extreme increase in structural complexity within a single step. For the total syntheses of Centrolobine, Pitavastatin, and Rosuvastatin, C-O bond formation was achieved through the addition of a hydroxy function to the allene moiety. The potential of the addition of nitrogen pronucleophiles to allenes was demonstrated in the total syntheses of Cusparein, Angusterein, Cermicin C, Senepodin G, Homoproline, Pipecolinol, Coniceine, Coniine, Ruxolitinib, Sitagliptin, Abacavir, Glucokinase activators, and Chaetominine. All of these examples testify to the wide applicability of the Rh-catalyzed addition of pronucleophiles to allenes or alkynes in target-oriented synthesis, and in this Account we summarize our contribution.

Multi-year belowground data of minirhizotron facilities in Selhausen.

The production of crops secure the human food supply, but climate change is bringing new challenges. Dynamic plant growth and corresponding environmental data are required to uncover phenotypic crop responses to the changing environment. There are many datasets on above-ground organs of crops, but roots and the surrounding soil are rarely the subject of longer term studies. Here, we present what we believe to be the first comprehensive collection of root and soil data, obtained at two minirhizotron facilities located close together that have the same local climate but differ in soil type. Both facilities have 7m-long horizontal tubes at several depths that were used for crosshole ground-penetrating radar and minirhizotron camera systems. Soil sensors provide observations at a high temporal and spatial resolution. The ongoing measurements cover five years of maize and wheat trials, including drought stress treatments and crop mixtures. We make the processed data available for use in investigating the processes within the soil-plant continuum and the root images to develop and compare image analysis methods.

Acenaphthoimidazolylidene-Ligated Palladacycle Enabled Suzuki-Miyaura Cross-Coupling Employing Equimolar Organoboron for Tri-Ortho-Substituted Bi(hetero)aryls and Teraryls.

The Pd-catalyzed Suzuki-Miyaura cross-couplings (SMRs) are utilized as the most practical method to construct C-C bond, especial for biaryls. However, a major disadvantage of current protocols is the requirement of excess organoboron coupling partner (1.5-3.0 equiv.). Herein, a novel palladacyclic 1,3-bis(2,6-diisopropylphenyl)acenaphthoimidazol-2-ylidene (AnIPr) precatalyst possessing a chiral oxazoline was designed, which enabled a general protocol towards bulky tri-ortho-substituted biaryls, ternaphthalenes and diarylanthracenes via the Pd-catalyzed SMR employing equimolar organoborons and aryl bromides. A remarkable scope of substrates with various functional groups and heterocycles were well compatible with an adaptability to synthesize useful ligands.

EXODUS: Stable and efficient training of spiking neural networks.

Introduction: Spiking Neural Networks (SNNs) are gaining significant traction in machine learning tasks where energy-efficiency is of utmost importance. Training such networks using the state-of-the-art back-propagation through time (BPTT) is, however, very time-consuming. Previous work employs an efficient GPU-accelerated backpropagation algorithm called SLAYER, which speeds up training considerably. SLAYER, however, does not take into account the neuron reset mechanism while computing the gradients, which we argue to be the source of numerical instability. To counteract this, SLAYER introduces a gradient scale hyper parameter across layers, which needs manual tuning. Methods: In this paper, we modify SLAYER and design an algorithm called EXODUS, that accounts for the neuron reset mechanism and applies the Implicit Function Theorem (IFT) to calculate the correct gradients (equivalent to those computed by BPTT). We furthermore eliminate the need for ad-hoc scaling of gradients, thus, reducing the training complexity tremendously. Results: We demonstrate, via computer simulations, that EXODUS is numerically stable and achieves comparable or better performance than SLAYER especially in various tasks with SNNs that rely on temporal features.

A Diastereoselective Cascade Annulation Approach to Bridged Polycyclic Heterocycles Involving an Unexpected Rearrangement.

A diastereoselective cascade annulation between allenoates and in-situ generated isoquinoline N-oxides generating sp3-rich bridged polycyclic heterocycles is disclosed. The reaction proceeds through an unprecedented non-rearomatized rearrangement and allows access to a broad range of bridged heterocycles in 38-93% yields with excellent functional group tolerance and high diastereoselectivity. Density functional theory calculations provided key insights into the possible reaction pathway and the stereoselectivity of this procedure.

A General C-N Cross-Coupling to Synthesize Heteroaryl Amines Using a Palladacyclic N-Heterocyclic Carbene Precatalyst.

A new palladacyclic N-heterocyclic carbene precatalyst was designed by the combination of 1,3-bis(2,6-diisopropylphenyl)acenaphthoimidazol-2-ylidene (AnIPr) with an achiral 2-naphthyl-4,4-dimethyloxazoline palladacyclic fragment. Applying this precatalyst enabled a general protocol for Pd-catalyzed C-N cross-coupling reactions of challenging five- or six-membered ring heteroaryl chlorides and various heterocyclic amines. The desired aminated products, including commercial pharmaceuticals or key intermediates such as piribedil, cyprodinil, V600EBRAF inhibitor, tripelennamine, 517-ß-hydroxysteroid dehydrogenase inhibitor, brexpiprazole, and sonidegib, were achieved in good to excellent yields (>61 examples, ≤99% yields).

Development and Validation of a Deep Learning Based Automated Minirhizotron Image Analysis Pipeline.

Root systems of crops play a significant role in agroecosystems. The root system is essential for water and nutrient uptake, plant stability, symbiosis with microbes, and a good soil structure. Minirhizotrons have shown to be effective to noninvasively investigate the root system. Root traits, like root length, can therefore be obtained throughout the crop growing season. Analyzing datasets from minirhizotrons using common manual annotation methods, with conventional software tools, is time-consuming and labor-intensive. Therefore, an objective method for high-throughput image analysis that provides data for field root phenotyping is necessary. In this study, we developed a pipeline combining state-of-the-art software tools, using deep neural networks and automated feature extraction. This pipeline consists of two major components and was applied to large root image datasets from minirhizotrons. First, a segmentation by a neural network model, trained with a small image sample, is performed. Training and segmentation are done using "RootPainter." Then, an automated feature extraction from the segments is carried out by "RhizoVision Explorer." To validate the results of our automated analysis pipeline, a comparison of root length between manually annotated and automatically processed data was realized with more than 36,500 images. Mainly the results show a high correlation (r = 0.9) between manually and automatically determined root lengths. With respect to the processing time, our new pipeline outperforms manual annotation by 98.1-99.6%. Our pipeline, combining state-of-the-art software tools, significantly reduces the processing time for minirhizotron images. Thus, image analysis is no longer the bottle-neck in high-throughput phenotyping approaches.

Cobalt-Catalyzed Hydroboration of Terminal and Internal Alkynes.

A novel methodology to access synthetically versatile vinylboronic esters through a ligand-controlled cobalt-catalyzed hydroboration of terminal and internal alkynes is reported. The approach relies on the in situ reduction of Co(II) by H-BPin in the presence of bisphosphine ligands generating catalytically active Co(I) hydride complexes. This procedure avoids the use of stoichiometric amounts of base, and no boron-containing byproducts are generated which is translated into high functional group tolerance and atom economy.

Catalyst Deactivation During Rhodium Complex-Catalyzed Propargylic C-H Activation.

Detailed mechanistic investigations on our previously reported synthesis of branched allylic esters by the rhodium complex-catalyzed propargylic C-H activation have been carried out. Based on initial mechanistic studies, we present herein more detailed investigations of the reaction mechanism. For this, various analytical (NMR, X-ray crystal structure analysis, Raman) and kinetic methods were used to characterize the formation of intermediates under the reaction conditions. The knowledge obtained by this was used to further optimize the previous conditions and generate a more active catalytic system.

Asymmetric hydroalkylation of alkynes and allenes with imidazolidinone derivatives: α-alkenylation of α-amino acids.

This work reports a new method for the synthesis of quaternary α-alkenyl substituted amino acids by the enantio- and diastereoselective addition of imidazolidinone derivatives to alkynes and allenes. Further hydrolysis of the imidazolidinone products under acidic conditions afforded biologically relevant amino acid derivatives. This method is geometry-selective (E-isomer), enantio- and diastereoselective, and products were obtained in good to excellent yields. The utility of this new methodology is proved by its operational simplicity and the successful accomplishment of gram-scale reactions. Experimental and computational studies suggest the key role of Li in terms of selectivity and support the proposed reaction mechanism.

Real-Time Ultra-Low Power ECG Anomaly Detection Using an Event-Driven Neuromorphic Processor.

Accurate detection of pathological conditions in human subjects can be achieved through off-line analysis of recorded biological signals such as electrocardiograms (ECGs). However, human diagnosis is time-consuming and expensive, as it requires the time of medical professionals. This is especially inefficient when indicative patterns in the biological signals are infrequent. Moreover, patients with suspected pathologies are often monitored for extended periods, requiring the storage and examination of large amounts of non-pathological data, and entailing a difficult visual search task for diagnosing professionals. In this work we propose a compact and sub-mW low power neural processing system that can be used to perform on-line and real-time preliminary diagnosis of pathological conditions, to raise warnings for the existence of possible pathological conditions, or to trigger an off-line data recording system for further analysis by a medical professional. We apply the system to real-time classification of ECG data for distinguishing between healthy heartbeats and pathological rhythms. Multi-channel analog ECG traces are encoded as asynchronous streams of binary events and processed using a spiking recurrent neural network operated in a reservoir computing paradigm. An event-driven neuron output layer is then trained to recognize one of several pathologies. Finally, the filtered activity of this output layer is used to generate a binary trigger signal indicating the presence or absence of a pathological pattern. We validate the approach proposed using a Dynamic Neuromorphic Asynchronous Processor (DYNAP) chip, implemented using a standard 180 nm CMOS VLSI process, and present experimental results measured from the chip.