Robert Bosch (United Kingdom)

The great micromorphological diversity of pollen grains amongst the seed plants is not only a marvel of nature but also a significant tool for plant biologists, especially taxonomists and ecologists. However, with the staggering diversity comes the problem of setting up a consistent and useful terminology to cope with classifying such morphological features. As the authors of this book state, although such categorization is rather artificial it is essential for defining the range of morphological diversity and generating systematic order. The remit of this illustrated handbook of pollen terminology is to provide a collection of the most useful and important terms in palynology and illustrate them by light and electron microscope micrographs. Essentially, this handbook is an updated and beautifully illustrated version of the web-accessible ‘Glossary of pollen and spore terminology’ (Punt et al., 2007). The largest proportion of the handbook is devoted to an illustrated glossary of pollen-related terms, which is usefully split into several parts. These cover the terminology of pollen units, pollen class, shape and size, apertures, ornamentation, the pollen wall and a miscellany of other terms. This glossary section has been produced to high standards, with an excellent lay-out and organization. Every term is exceptionally illustrated, not by just one but by several micrographs, with light, SEM and TEM figures used where appropriate. Usefully, an alphabetical text version of the glossary is included at the back, making it even easier to track down and define palynological terms. Although the glossary alone is comprehensive, copiously illustrated and user-friendly enough to recommend this volume in its own right, the value of this work is enhanced by a series of short, general chapters that cover palynology and its history, an introduction to pollen morphology, a discussion of why categorization is required and an overview of pollen development. From a more practical perspective, the chapters that cover pollen features that can be misinterpreted, controversial or fuzzy terms and methods are particularly valuable. Whilst this volume will be an essential addition to reference libraries, there is no doubt that it will make a regularly consulted addition to the shelves of individuals involved in studying pollen, from those working in palaeobiology, ecology, entomology and plant systematics through to forensic scientists. Using this volume will simplify the procedure of describing pollen morphology from samples under study. Indeed, this volume would have great value in practical classes for students where pollen, pollen morphology and pollination biology is the subject of investigation. Although the authors clearly state that this handbook is not meant to be an exhaustive treatment of the subject, one or two additions would have further enhanced this attractive and practical book. In a few places, notably in the glossary of miscellaneous terms, the labelling in the illustrations of the feature being defined is inadequate, confusing or absent. For example, for tapetum in the glossary (p. 216) the TEM micrographs do not actually label the tapetal layers. The chapter on pollen development could be improved, with a diagram to explain the sporophytic lineage of cells in anther development leading to pollen formation via meiosis. The statement that ‘gametogenesis starts with formation of a central vacuole within the uninucleate microspore’ is both confusing and inaccurate. Strictly, gametogenesis is associated with the second pollen mitosis of the generative cell. Perhaps the most significant omission in this volume is a focused discussion concerning the use of pollen micromorphology in plant systematics. It would have been interesting and informative to discuss particular morphological and developmental features from a phylogenetic perspective. For instance, for each morphological feature an outline of the known pattern of distribution amongst seed plants would have been useful. There is also almost no mention of whether these strikingly different microscopic features are associated with biologically important phenomena, such as the mode of pollen dispersal, the type of stigmatic surface or manner of pollen germination. This kind of discussion would allow a much greater appreciation of which features of the pollen grain are of adaptive value and which have minimal selective value. Without so much as a limited comment of this kind, even if speculative in nature, the diversity of morphological features that are so well illustrated in this handbook become rather abstract and meaningless. Although there are a few shortcomings, this handbook is not only of practical use but also exceptionally well-crafted and a delight to the eye. In the age of online resources, it emphatically demonstrates that well-produced reference books can be superior to web-based material. I have no doubt that this will become an indispensable standard reference work for all scientists studying pollen.

Emphasis in this paper is on the fault ride-through and grid support capabilities of multi-pole permanent magnet synchronous generator (PMSG) wind turbines with a full-scale frequency converter. These wind turbines are announced to be very attractive, especially for large offshore wind farms. A control strategy is presented, which enhances the fault ride-through and voltage support capability of such wind turbines during grid faults. Its design has special focus on power converters' protection and voltage control aspects. The performance of the presented control strategy is assessed and discussed by means of simulations with the use of a transmission power system generic model developed and delivered by the Danish Transmission System Operator Energinet.dk. The simulation results show how a PMSG wind farm equipped with an additional voltage control can help a nearby active stall wind farm to ride through a grid fault, without implementation of any additional ride-through control strategy in the active stall wind farm.

After a century of fire suppression, dense forests in California have fueled high-severity fires. We surveyed mixed conifer forest with 995–1178 trees ha−1 (stems > 10 cm diameter at breast height), and nearby pine–oak woodland having 175–230 trees ha−1, 51 days after a severe burn, to contrast the spatial extent and properties of thermally altered soil at sites with different tree densities. Water-repellent soils were more extensive in forest than woodland. Deposits of white ash, composed largely of calicite, covered at most ~25% of the land surface, in places where large fuel items (e.g. logs, branches, exfoliated oak bark) had thoroughly combusted. At least 1690 kg ha−1 of CaCO3 in ash was deposited over the forest, and at least 700 kg ha−1 was added to the woodland. Combustion of logs and large branches also reddened the underlying yellow-brown soil as deep as 60 mm (average 8 mm), and over ~1–12% of the land surface. The reddened soils have magnetic susceptibilities that are three to seven times greater than surrounding unreddened soils within the burn, indicating thermal production of maghemite. Such fire-altered conditions persist over spatial and temporal scales that influence soil genesis in Mediterranean-type climate regions.

Efforts in design and optimization of catalyst layers for polymer electrolyte fuel cells hinge on mathematical models that link electrode composition and microstructure with effective physico-chemical properties. A pivotal property of these layers and the focus of this work is the proton conductivity, which is largely determined by the morphology of the ionomer. However, available relations between catalyst layer composition and proton conductivity are often adopted from general theories for random heterogeneous media and ignore specific features of the microstructure, e.g., agglomerates, film-like structures, or the hierarchical porous network. To establish a comprehensive understanding of the peculiar structure-property relations, we generated synthetic volumetric images of the catalyst layer microstructure. In a mesoscopic volume element, we modeled the electrolyte phase and calculated the proton conductivity using numerical tools. Varying the ionomer morphology in terms of ionomer film coverage and thickness revealed two limiting cases: the ionomer can either form a thin film with high coverage on the catalyst agglomerates; or the ionomer exists as voluminous chunks that connect across the inter-agglomerate space. Both cases were modeled analytically, adapting relations from percolation theory. Based on the simulated data, a novel relation is proposed, which links the catalyst layer microstructure to the proton conductivity over a wide range of morphologies. The presented analytical approach is a versatile tool for the interpretation of experimental trends and it provides valuable guidance for catalyst layer design. The proposed model was used to analyze the formation of the catalyst layer microstructure during the ink stage. A parameter study of the initial ionomer film thickness and the ionomer dispersion parameter revealed that the ionomer morphology should be tweaked towards well-defined films with high coverage of catalyst agglomerates. These implications match current efforts in the experimental literature and they may thus provide direction in electrode materials research for polymer electrolyte fuel cells.

<div class="htmlview paragraph">In the present work, the finite element method is used to analyze the friction-induced vibration of brake systems, which may lead to squeal. A new approach is proposed to model the friction interaction at the rotor/pad interface, leading to the dynamic equations which well represent the dynamic characteristics of brake systems. The complex eigenvalue analysis method is then employed to detect the unstable modes of the system.</div> <div class="htmlview paragraph">The analytical method presented can be applied to both disk brake and drum brake systems. Some application results are presented and discussed.</div>

The fatigue of mechanical strain induced by electric fields was investigated for antiferroelectric Pb 0.97 La 0.02 (Zr 0.77 Sn 0.14 Ti 0.09 )O 3 ceramics. The material shows a high resistance to fatigue owing to bipolar electric cycling up to 10 8 cycles. The strain hysteresis loop is still fairly symmetric, whereas the maximum field‐induced strain decreases by only 30% of its initial value. The fatigued samples show a damaged microstructure with dendritic macrocracks and microcrack clouds. The fatigue is attributed to a combination of electrochemical and mechanical mechanisms.

Abstract We report on the development of a microfluidic multiplexing technology for highly parallelized sample analysis via quantitative polymerase chain reaction (PCR) in an array of 96 nanoliter-scale microcavities made from silicon. This PCR array technology features fully automatable aliquoting microfluidics, a robust sample compartmentalization up to temperatures of 95 °C, and an application-specific prestorage of reagents within the 25 nl microcavities. The here presented hybrid silicon–polymer microfluidic chip allows both a rapid thermal cycling of the liquid compartments and a real-time fluorescence read-out for a tracking of the individual amplification reactions taking place inside the microcavities. We demonstrate that the technology provides very low reagent carryover of prestored reagents < 6 × 10 −2 and a cross talk rate < 1 × 10 −3 per PCR cycle, which facilitate a multi-targeted sample analysis via geometric multiplexing. Furthermore, we apply this PCR array technology to introduce a novel digital PCR-based DNA quantification method: by taking the assay-specific amplification characteristics like the limit of detection into account, the method allows for an absolute gene target quantification by means of a statistical analysis of the amplification results.

Micromechanical fatigue lifetime predictions, in particular for the high cycle fatigue regime, require an appropriate modelling of mean stress effects in order to account for lifetime reducing positive mean stresses. Focus of this micromechanical study is the comparison of three selected fatigue indicator parameters (FIPs), with respect to their applicability to different total strain ratios. In this work, investigations are performed on the modelling and prediction of the fatigue crack initiation life of the martensitic high-strength steel SAE 4150 for two different total strain ratios. First, multiple martensitic statistical volume elements (SVEs) are generated by multiscale Voronoi tessellations. Micromechanical fatigue simulations are then performed on these SVEs by means of a crystal plasticity model to obtain microstructure dependent fatigue responses. In order to account for the material specific fatigue damage zone, a non-local homogenisation scheme for the FIPs is introduced for lath martensitic microstructures. The numerical results of the different non-local FIPs are compared with experimental fatigue crack initiation results for two different total strain ratios. It is concluded that the multiaxial fatigue criteria proposed by Fatemi-Socie is superior for predicting fatigue crack initiation life to the energy dissipation criteria and the accumulated plastic slip criteria for the investigated total strain ratios.

Named Function Networking (NFN) is an extension for Information Centric Networking (ICN) to execute computation inside the Network. Thereby, NFN consists of two contributions: A workflow definition and a resolution strategy. The ICN communication model enables NFN to reuse already computed results by using the network's content store. To resolve a computation, NFN first tries to find a cached result and only if no result was found, the computation is executed - so-called FoX (Find or Execute) resolution strategy. Initially, NFN was optimized for cloud computing and data center computing next to the big data objects. However, new trends like IoT and edge computing describe other requirements to network computations (e.g. dynamic computations of automotive services at the edge). In this paper, we explore how the resolution strategy can be modified to fit to IoT scenarios without changing the workflow definition. Based on two exemplary IoT use cases (home automation and automotive IOT), new resolution strategies will be presented.

<div class="htmlview paragraph">In this paper, a newly developed model that can be applied for the prediction of ignition delay times and heat release in engines operating in Homogeneous Charge Compression Ignition (HCCI) mode is presented. The proprietary numerical model is based on multi-zone application of the First Law of Thermodynamics and is coupled with a newly developed reduced kinetic schemes describing the oxidation of primary reference fuels (n-Heptane and iso-Octane). This proprietary code takes into account the influence of inhomogeneities of residual gas, air-to-fuel ratio and temperature distribution on combustion processes in a simplified fashion.</div> <div class="htmlview paragraph">The proposed reaction schemes are validated by comparison with shock-tube measurements of ignition delay times at various pressures, fuel-to-air ratios and temperatures. Furthermore, the performance of reduced models are tested by comparing the results with predictions of detailed reaction mechanisms which are available in the literature.</div> <div class="htmlview paragraph">CHEMKIN solver has been coupled with MATLAB in order to solve the chemistry and to calculate the heat release during the compression stage.</div> <div class="htmlview paragraph">Simulations of combustion processes using different fuels at various operating points and engines (gasoline, diesel) show good agreement with experimental observations.</div>

Extrusion and injection molding processes of filled polymers are widely used in industry due to their high strength‐to‐weight ratios and for their ability to manufacture a variety of geometries while improving the overall mechanical and thermal properties. However, filler migration and filler–matrix separation during processing are phenomena that are not fully understood. To gain an improved understanding of these phenomena, polypropylene samples with different glass bead concentrations were manufactured using extrusion, injection molding and a customized screwless extruder that was built in‐house. Computed tomography was performed on the samples to observe particle position and distribution after material solidification. For all three processes, filler migration and filler–matrix separation was observed. In the extrusion and screwless extrusion processes, particles migrated towards the wall, contrary to current theories and believes. During the injection molding process, filler–matrix separation was manifested as bead‐free zones in the center region and the walls of the spiral mold at the entrance region of the spiral mold. These bead‐free zones were later filled at the far end of the spiral mold suggesting migration of particles along flow with almost no bead‐free zones at the end of the mold. Particle redistribution towards the wall and the center during flow could possibly have happened due to migration and fountain flow effects. POLYM. COMPOS., 40:2165–2177, 2019. © 2018 Society of Plastics Engineers

Abstract Different factors contribute to the weakness of weld lines (WLs) induced by injection molding such as unsuitable fiber orientation (FO), incomplete polymer matrix diffusion, voids and V‐notches. This study aims to characterize the contribution of each factor on the weakness of frontal WLs in a short glass fiber‐reinforced polybutylene‐terephthalate characterized by extensive X‐ray computed tomography and mechanical tensile testing assisted with digital image correlation. A reduction of 50% of the stress at break and almost 40% of the strain at break is observed despite the complete matrix healing at the WL interface and the absence of V‐notches. Frontal WLs induce a FO gradient starting 2 to 3 mm before the WL plane. The fibers in the WL region mainly orient in transverse‐to‐flow and thickness direction. This FO gradient localizes the deformations, which leads to failure at a strength near to the one of the unreinforced variant. Voids formation in frontal WLs seems to be driven by large gradients of FO and subsequent anisotropic shrinkage. In addition, this shrinkage behavior at the WL causes an increase of thickness. By applying higher packing pressures, the fibers orient more in flow direction at the core of the WL, leading to a higher tensile strength and a lower content of voids. Finally, we can conclude that the FO is the dominant factor controlling the mechanical performance in frontal WLs.

<div class="htmlview paragraph">In most cases of night time driving the low beam light function is used for the road illumination in front of the car. This conventional low beam function has a constant light pattern: no matter whether the driver is actually driving on a straight or curvy road, whether the road is wet or dry, always the same beam pattern is applied. Test experiences of the last years prove that a headlamp with an „adaptive light pattern” having different optimum light pattern adapted to different driving situations should give a better illumination than the conventional constant low beam pattern which can only be a compromise.</div> <div class="htmlview paragraph">In this paper an outline of the basic idea of the „adaptive light pattern” is given. Different driving situations and their corresponding optimum light pattern, basic technical concepts and the legal situation regarding homologation of such an advanced lighting system will be discussed.</div>

Abstract Focused ion beam (FIB) – scanning electron microscopy (SEM) serial sectioning tomography has become an important tool for three‐dimensional microstructure reconstruction of solid oxide fuel cells (SOFC) to obtain an understanding of fabrication‐related effects and SOFC performance. By sequential FIB milling and SEM imaging a stack of cross‐section images across all functional SOFC layers was generated covering a large volume of 3.5·10 4 μm 3 . One crucial step is image segmentation where regions with different image intensities are assigned to different material phases within the SOFC. To analyze all relevant SOFC materials, it was up to now mandatory to acquire several images by scanning the same region with different imaging parameters because sufficient material contrast could otherwise not be achieved. In this work we obtained high‐contast SEM images from a single scan to reconstract all functional SOFC layers consisting of a Ni/Y 2 O 3 ‐doped ZrO 2 (YDZ) cermet anode, YDZ electrolyte and (La,Sr)MnO 3 /YDZ cathode. This was possible by using different, simultaneous read‐out detectors installed in a state‐of‐the‐art scanning electron microscope. In addition, we used a deterministic approach for the optimization of imaging parameters by employing Monte Carlo simulations rather than trial‐and‐error tests. We also studied the effect of detection geometry, detecting angle range and detector type.

Mastering the complexity of safety assurance for modern, software-intensive systems is challenging in several domains, such as automotive, robotics, and avionics. Model-based safety analysis techniques show promising results to handle this challenge by automating the generation of required artifacts for an assurance case. In this work, we adapt prominent approaches and propose facilitation of SysML models with component fault trees (CFTs) to support the fault tree analysis (FTA). While most existing approaches based on CFTs are only targeting the system topology, e. g., UML Class Diagrams, we propose an integration of CFTs with SysML Internal Block Diagrams as well as SysML Activity Diagrams. We conclude with best practices and lessons learned that emerged from applying our approach to automotive use-cases.

The possibility of predicting Quality of Service, and particularly data rates, in mobile networks will enable new applications for future automated and connected mobility, such as teleoperated driving. Since network data is difficult to acquire and usually of low granularity, robust prediction approaches are required that need to be trained with data sets and measurements generated by end devices. In this paper, we present uplink and downlink data sets, measured in extensive drive tests, that are made available for the evaluation of machine learning methods. Based on this data, we compare the data rate prediction performance in uplink and downlink for neural network, random forest and gradient boosting approaches. Our results show a significantly higher achievable accuracy in uplink than in downlink, and that, even with reduced feature sets, gradient boosting is particularly suited for the prediction task. Moreover, we investigate the use of quantile estimation methods for predicting bounds on the achievable data rate. We show that conformalized approaches, both based on neural networks and random forests, can predict quantiles with very high accuracy.

Abstract Based on a previous study where key structural motifs of poly(acrylonitrile) (PAN) and sulfur/PAN (SPAN) were identified and their energies evaluated by using density functional theory, here plausible mechanisms for battery charging and discharging at a SPAN cathode were identified. Based on a simplified model for battery operation, we find that discharging the battery involves the formation of lithium polysulfide intermediates and the reductive adsorption of Li + ions onto S n PAN. In both discharging and charging, Li atoms preferentially coordinate with N atoms on the backbone, leading to strong Li‐S n PAN adsorption energies. Furthermore, we found that spatially separating a dissociated S n Li fragment from the backbone is difficult, providing a plausible explanation for the ability of a SPAN cathode to hinder polysulfides from diffusing to the cathode, leading to a reduction of the polysulfide shuttle mechanism.

In this work, a physics-based method of estimating the residual mass in a recompression homogeneous charge compression ignition engine is developed and analyzed for real-time implementation. The estimation routine is achieved through in-cylinder pressure and exhaust temperature measurements coupled with energy and mass conservation laws applied during the exhaust period. Experimental results on a multicylinder gasoline homogeneous charge compression ignition engine and dynamic analysis demonstrate the estimation routine’s ability to perform across a wide range of operating conditions as well as on a cycle-by-cycle basis for highly variable combustion phasing data.

Building dialogue interfaces for realworld scenarios often entails training semantic parsers starting from zero examples. How can we build datasets that better capture the variety of ways users might phrase their queries, and what queries are actually realistic? Wang et al. (2015) proposed a method to build semantic parsing datasets by generating canonical utterances using a grammar and having crowdworkers paraphrase them into natural wording. A limitation of this approach is that it induces bias towards using similar language as the canonical utterances. In this work, we present a methodology that elicits meaningful and lexically diverse queries from users for semantic parsing tasks. Starting from a seed lexicon and a generative grammar, we pair logical forms with mixed text-image representations and ask crowdworkers to paraphrase and confirm the plausibility of the queries that they generated. We use this method to build a semantic parsing dataset from scratch for a dialog agent in a smart-home simulation. We find evidence that this dataset, which we have named SMARTHOME, is demonstrably more lexically diverse and difficult to parse than existing domain-specific semantic parsing datasets.

Scanning micro-mirror actuators are silicon-based oscillatory micro-electro-mechanical systems (MEMS). They enable laser distance measurements for automotive LIDAR applications as well as projection modules for the consumer market. For MEMS applications, the geometric structure is typically designed to serve a number of functional requirements. Most importantly, the mode spectrum contains a single high-Q mode, the drive mode, which per design is expected to yield the only resonantly excited geometric motion during operation. Yet here, we report on the observation of a resonant three-mode excitation via a process known as spontaneous parametric down-conversion. We show that this phenomenon, most extensively studied in the field of nonlinear optics, originates from three-wave coupling induced by geometric nonlinearities. In combination with further Duffing-type nonlinearities, the micro mirror displays a variety of nonlinear dynamical behaviour ranging from stationary state bifurcations to dynamical instabilities observable via amplitude modulations. We are able to explain and emulate all experimental observations using a single fundamental model. In particular, our analysis allows us to understand the conditions for the onset of three-wave down-conversion which if not accounted for in the design of the MEMS structure, can have drastic impact on its functionality even leading to fracture.