Robert Bosch (Germany)

Gaia is a cornerstone mission in the science programme of the EuropeanSpace Agency (ESA). The spacecraft construction was approved in 2006, following a study in which the original interferometric concept was changed to a direct-imaging approach. Both the spacecraft and the payload were built by European industry. The involvement of the scientific community focusses on data processing for which the international Gaia Data Processing and Analysis Consortium (DPAC) was selected in 2007. Gaia was launched on 19 December 2013 and arrived at its operating point, the second Lagrange point of the Sun-Earth-Moon system, a few weeks later. The commissioning of the spacecraft and payload was completed on 19 July 2014. The nominal five-year mission started with four weeks of special, ecliptic-pole scanning and subsequently transferred into full-sky scanning mode. We recall the scientific goals of Gaia and give a description of the as-built spacecraft that is currently (mid-2016) being operated to achieve these goals. We pay special attention to the payload module, the performance of which is closely related to the scientific performance of the mission. We provide a summary of the commissioning activities and findings, followed by a description of the routine operational mode. We summarise scientific performance estimates on the basis of in-orbit operations. Several intermediate Gaia data releases are planned and the data can be retrieved from the Gaia Archive, which is available through the Gaia home page.

The International League Against Epilepsy (ILAE) Commission on Classification and Terminology has revised concepts, terminology, and approaches for classifying seizures and forms of epilepsy. Generalized and focal are redefined for seizures as occurring in and rapidly engaging bilaterally distributed networks (generalized) and within networks limited to one hemisphere and either discretely localized or more widely distributed (focal). Classification of generalized seizures is simplified. No natural classification for focal seizures exists; focal seizures should be described according to their manifestations (e.g., dyscognitive, focal motor). The concepts of generalized and focal do not apply to electroclinical syndromes. Genetic, structural-metabolic, and unknown represent modified concepts to replace idiopathic, symptomatic, and cryptogenic. Not all epilepsies are recognized as electroclinical syndromes. Organization of forms of epilepsy is first by specificity: electroclinical syndromes, nonsyndromic epilepsies with structural-metabolic causes, and epilepsies of unknown cause. Further organization within these divisions can be accomplished in a flexible manner depending on purpose. Natural classes (e.g., specific underlying cause, age at onset, associated seizure type), or pragmatic groupings (e.g., epileptic encephalopathies, self-limited electroclinical syndromes) may serve as the basis for organizing knowledge about recognized forms of epilepsy and facilitate identification of new forms.

<i>Herschel<i/> was launched on 14 May 2009, and is now an operational ESA space observatory offering unprecedented observational capabilities in the far-infrared and submillimetre spectral range 55–671 <i>μ<i/>m. <i>Herschel<i/> carries a 3.5 m diameter passively cooled Cassegrain telescope, which is the largest of its kind and utilises a novel silicon carbide technology. The science payload comprises three instruments: two direct detection cameras/medium resolution spectrometers, PACS and SPIRE, and a very high-resolution heterodyne spectrometer, HIFI, whose focal plane units are housed inside a superfluid helium cryostat. <i>Herschel<i/> is an observatory facility operated in partnership among ESA, the instrument consortia, and NASA. The mission lifetime is determined by the cryostat hold time. Nominally approximately 20 000 h will be available for astronomy, 32% is guaranteed time and the remainder is open to the worldwide general astronomical community through a standard competitive proposal procedure.

Context. At about 1000 days after the launch of Gaia we present the first Gaia data release, Gaia DR1, consisting of astrometry and photometry for over 1 billion sources brighter than magnitude 20.7.&#13;\n&#13;\nAims. A summary of Gaia DR1 is presented along with illustrations of the scientific quality of the data, followed by a discussion of the limitations due to the preliminary nature of this release.&#13;\n&#13;\nMethods. The raw data collected by Gaia during the first 14 months of the mission have been processed by the Gaia Data Processing and Analysis Consortium (DPAC) and turned into an astrometric and photometric catalogue.&#13;\n&#13;\nResults. Gaia DR1 consists of three components: a primary astrometric data set which contains the positions, parallaxes, and mean proper motions for about 2 million of the brightest stars in common with the Hipparcos and Tycho-2 catalogues – a realisation of the Tycho-Gaia Astrometric Solution (TGAS) – and a secondary astrometric data set containing the positions for an additional 1.1 billion sources. The second component is the photometric data set, consisting of mean G-band magnitudes for all sources. The G-band light curves and the characteristics of ~3000 Cepheid and RR Lyrae stars, observed at high cadence around the south ecliptic pole, form the third component. For the primary astrometric data set the typical uncertainty is about 0.3 mas for the positions and parallaxes, and about 1 mas yr-1 for the proper motions. A systematic component of ~0.3 mas should be added to the parallax uncertainties. For the subset of ~94 000 Hipparcos stars in the primary data set, the proper motions are much more precise at about 0.06 mas yr-1. For the secondary astrometric data set, the typical uncertainty of the positions is ~10 mas. The median uncertainties on the mean G-band magnitudes range from the mmag level to ~0.03 mag over the magnitude range 5 to 20.7.&#13;\n&#13;\nConclusions. Gaia DR1 is an important milestone ahead of the next Gaia data release, which will feature five-parameter astrometry for all sources. Extensive validation shows that Gaia DR1 represents a major advance in the mapping of the heavens and the availability of basic stellar data that underpin observational astrophysics. Nevertheless, the very preliminary nature of this first Gaia data release does lead to a number of important limitations to the data quality which should be carefully considered before drawing conclusions from the data.

Herschel was launched on 14 May 2009, and is now an operational ESA space observatory offering unprecedented observational capabilities in the far-infrared and submillimetre spectral range 55-671 μm. Herschel carries a 3.5 metre diameter passively cooled Cassegrain telescope, which is the largest of its kind and utilises a novel silicon carbide technology. The science payload comprises three instruments: two direct detection cameras/medium resolution spectrometers, PACS and SPIRE, and a very high-resolution heterodyne spectrometer, HIFI, whose focal plane units are housed inside a superfluid helium cryostat. Herschel is an observatory facility operated in partnership among ESA, the instrument consortia, and NASA. The mission lifetime is determined by the cryostat hold time. Nominally approximately 20,000 hours will be available for astronomy, 32% is guaranteed time and the remainder is open to the worldwide general astronomical community through a standard competitive proposal procedure.

BACKGROUND: The addition of rituximab to combination chemotherapy with cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP), or R-CHOP, has significantly improved the survival of patients with diffuse large-B-cell lymphoma. Whether gene-expression signatures correlate with survival after treatment of diffuse large-B-cell lymphoma is unclear. METHODS: We profiled gene expression in pretreatment biopsy specimens from 181 patients with diffuse large-B-cell lymphoma who received CHOP and 233 patients with this disease who received R-CHOP. A multivariate gene-expression-based survival-predictor model derived from a training group was tested in a validation group. RESULTS: A multivariate model created from three gene-expression signatures--termed "germinal-center B-cell," "stromal-1," and "stromal-2"--predicted survival both in patients who received CHOP and patients who received R-CHOP. The prognostically favorable stromal-1 signature reflected extracellular-matrix deposition and histiocytic infiltration. By contrast, the prognostically unfavorable stromal-2 signature reflected tumor blood-vessel density. CONCLUSIONS: Survival after treatment of diffuse large-B-cell lymphoma is influenced by differences in immune cells, fibrosis, and angiogenesis in the tumor microenvironment.

ADVERTISEMENT RETURN TO ISSUEPREVReviewNEXTPyrene-Based Materials for Organic ElectronicsTeresa M. Figueira-Duarte† and Klaus Müllen*‡View Author Information† BASF SE, Carl-Bosch-Strasse 38, 67056 Ludwigshafen, Germany‡ Max Planck Institute for Polymer Research, Ackermannweg 10, P.O. Box 3148, Mainz, GermanyE-mail: [email protected]Cite this: Chem. Rev. 2011, 111, 11, 7260–7314Publication Date (Web):July 11, 2011Publication History Received14 December 2010Published online11 July 2011Published inissue 9 November 2011https://pubs.acs.org/doi/10.1021/cr100428ahttps://doi.org/10.1021/cr100428areview-articleACS PublicationsCopyright © 2011 American Chemical SocietyRequest reuse permissionsArticle Views31534Altmetric-Citations1332LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose SUBJECTS:Aromatic compounds,Dendrons,Diodes,Fluorescence,Hydrocarbons Get e-Alerts

The European Space Agency's Planck satellite, dedicated to studying the early Universe and its subsequent evolution, was launched 14 May 2009 and has been scanning the microwave and submillimetre sky continuously since 12 August 2009. In March 2013, ESA and the Planck Collaboration released the initial cosmology products based on the first 15.5 months of Planck data, along with a set of scientific and technical papers and a web-based explanatory supplement. This paper gives an overview of the mission and its performance, the processing, analysis, and characteristics of the data, the scientific results, and the science data products and papers in the release. The science products include maps of the cosmic microwave background (CMB) and diffuse extragalactic foregrounds, a catalogue of compact Galactic and extragalactic sources, and a list of sources detected through the Sunyaev-Zeldovich effect. The likelihood code used to assess cosmological models against the Planck data and a lensing likelihood are described. Scientific results include robust support for the standard six-parameter ΛCDM model of cosmology and improved measurements of its parameters, including a highly significant deviation from scale invariance of the primordial power spectrum. The Planck values for these parameters and others derived from them are significantly different from those previously determined. Several large-scale anomalies in the temperature distribution of the CMB, first detected by WMAP, are confirmed with higher confidence. Planck sets new limits on the number and mass of neutrinos, and has measured gravitational lensing of CMB anisotropies at greater than 25σ. Planck finds no evidence for non-Gaussianity in the CMB. Planck's results agree well with results from the measurements of baryon acoustic oscillations. Planck finds a lower Hubble constant than found in some more local measures. Some tension is also present between the amplitude of matter fluctuations (σ8) derived from CMB data and that derived from Sunyaev-Zeldovich data. The Planck and WMAP power spectra are offset from each other by an average level of about 2% around the first acoustic peak. Analysis of Planck polarization data is not yet mature, therefore polarization results are not released, although the robust detection of E-mode polarization around CMB hot and cold spots is shown graphically. © 2014 ESO.

This review summarizes the corrosion inhibition of steel materials in acidic media. Numerous corrosion inhibitors for steels in acidic solutions are presented. The emphasis is on HCl solutions, lower-grade steels, and elevated temperatures. This review is also devoted to corrosion inhibitor formulation design – mixtures of corrosion inhibitors with (mainly) surfactants, solvents, and intensifiers to improve the effectiveness of individual compounds at elevated temperatures. The information presented in this review is useful for diverse industrial fields, primarily for the well acidizing procedure, and secondly for other applications where corrosion inhibitors for steel materials are needed.

In order to achieve autonomous operation of a vehicle in urban situations with unpredictable traffic, several realtime systems must interoperate, including environment perception, localization, planning, and control. In addition, a robust vehicle platform with appropriate sensors, computational hardware, networking, and software infrastructure is essential. We previously published an overview of Junior, Stanford's entry in the 2007 DARPA Urban Challenge. This race was a closed-course competition which, while historic and inciting much progress in the field, was not fully representative of the situations that exist in the real world. In this paper, we present a summary of our recent research towards the goal of enabling safe and robust autonomous operation in more realistic situations. First, a trio of unsupervised algorithms automatically calibrates our 64-beam rotating LIDAR with accuracy superior to tedious hand measurements. We then generate high-resolution maps of the environment which are subsequently used for online localization with centimeter accuracy. Improved perception and recognition algorithms now enable Junior to track and classify obstacles as cyclists, pedestrians, and vehicles; traffic lights are detected as well. A new planning system uses this incoming data to generate thousands of candidate trajectories per second, choosing the optimal path dynamically. The improved controller continuously selects throttle, brake, and steering actuations that maximize comfort and minimize trajectory error. All of these algorithms work in sun or rain and during the day or night. With these systems operating together, Junior has successfully logged hundreds of miles of autonomous operation in a variety of real-life conditions.

Recent advancements in perception for autonomous driving are driven by deep learning. In order to achieve robust and accurate scene understanding, autonomous vehicles are usually equipped with different sensors (e.g. cameras, LiDARs, Radars), and multiple sensing modalities can be fused to exploit their complementary properties. In this context, many methods have been proposed for deep multi-modal perception problems. However, there is no general guideline for network architecture design, and questions of “what to fuse”, “when to fuse”, and “how to fuse” remain open. This review paper attempts to systematically summarize methodologies and discuss challenges for deep multi-modal object detection and semantic segmentation in autonomous driving. To this end, we first provide an overview of on-board sensors on test vehicles, open datasets, and background information for object detection and semantic segmentation in autonomous driving research. We then summarize the fusion methodologies and discuss challenges and open questions. In the appendix, we provide tables that summarize topics and methods. We also provide an interactive online platform to navigate each reference: https://boschresearch.github.io/multimodalperception/.

The market for driver assistance systems based on millimeter-wave radar sensor technology is gaining momentum. In the near future, the full range of newly introduced car models will be equipped with radar based systems which leads to high volume production with low cost potential. This paper provides background and an overview of the state of the art of millimeter-wave technology for automotive radar applications, including two actual silicon based fully integrated radar chips. Several advanced packaging concepts and antenna systems are presented and discussed in detail. Finally measurement results of the fully integrated radar front ends are shown.

Affect recognition aims to detect a person's affective state based on observables, with the goal to e.g. improve human-computer interaction. Long-term stress is known to have severe implications on wellbeing, which call for continuous and automated stress monitoring systems. However, the affective computing community lacks commonly used standard datasets for wearable stress detection which a) provide multimodal high-quality data, and b) include multiple affective states. Therefore, we introduce WESAD, a new publicly available dataset for wearable stress and affect detection. This multimodal dataset features physiological and motion data, recorded from both a wrist- and a chest-worn device, of 15 subjects during a lab study. The following sensor modalities are included: blood volume pulse, electrocardiogram, electrodermal activity, electromyogram, respiration, body temperature, and three-axis acceleration. Moreover, the dataset bridges the gap between previous lab studies on stress and emotions, by containing three different affective states (neutral, stress, amusement). In addition, self-reports of the subjects, which were obtained using several established questionnaires, are contained in the dataset. Furthermore, a benchmark is created on the dataset, using well-known features and standard machine learning methods. Considering the three-class classification problem ( baseline vs. stress vs. amusement ), we achieved classification accuracies of up to 80%,. In the binary case ( stress vs. non-stress ), accuracies of up to 93%, were reached. Finally, we provide a detailed analysis and comparison of the two device locations ( chest vs. wrist ) as well as the different sensor modalities.

neural networks (SNNs) can potentially offer an efficient way of doing inference because the neurons in the networks are sparsely activated and computations are event-driven. Previous work showed that simple continuous-valued deep Convolutional Neural Networks (CNNs) can be converted into accurate spiking equivalents. These networks did not include certain common operations such as max-pooling, softmax, batch-normalization and Inception-modules. This paper presents spiking equivalents of these operations therefore allowing conversion of nearly arbitrary CNN architectures. We show conversion of popular CNN architectures, including VGG-16 and Inception-v3, into SNNs that produce the best results reported to date on MNIST, CIFAR-10 and the challenging ImageNet dataset. SNNs can trade off classification error rate against the number of available operations whereas deep continuous-valued neural networks require a fixed number of operations to achieve their classification error rate. From the examples of LeNet for MNIST and BinaryNet for CIFAR-10, we show that with an increase in error rate of a few percentage points, the SNNs can achieve more than 2x reductions in operations compared to the original CNNs. This highlights the potential of SNNs in particular when deployed on power-efficient neuromorphic spiking neuron chips, for use in embedded applications.

Lithium/air batteries, based on their high theoretical specific energy, are an extremely attractive technology for electrical energy storage that could make long-range electric vehicles widely affordable. However, the impact of this technology has so far fallen short of its potential due to several daunting challenges. In nonaqueous Li/air cells, reversible chemistry with a high current efficiency over several cycles has not yet been established, and the deposition of an electrically resistive discharge product appears to limit the capacity. Aqueous cells require water-stable lithium-protection membranes that tend to be thick, heavy, and highly resistive. Both types of cell suffer from poor oxygen redox kinetics at the positive electrode and deleterious volume and morphology changes at the negative electrode. Closed Li/air systems that include oxygen storage are much larger and heavier than open systems, but so far oxygen- and OH−-selective membranes are not effective in preventing contamination of cells. In this review we discuss the most critical challenges to developing robust, high-energy Li/air batteries and suggest future research directions to understand and overcome these challenges. We predict that Li/air batteries will primarily remain a research topic for the next several years. However, if the fundamental challenges can be met, the Li/air battery has the potential to significantly surpass the energy storage capability of today's Li-ion batteries.

BACKGROUND: Myocarditis can occasionally lead to sudden death and may progress to dilated cardiomyopathy in up to 10% of patients. Because the initial onset is difficult to recognize clinically and the diagnostic tools available are unsatisfactory, new strategies to diagnose myocarditis are needed. METHODS AND RESULTS: Cardiovascular MR imaging (CMR) was performed in 32 patients who were diagnosed with myocarditis by clinical criteria. To determine whether CMR visualizes areas of active myocarditis, endomyocardial biopsy was taken from the region of contrast enhancement and submitted to histopathologic analysis. Follow-up was performed 3 month later. Contrast enhancement was present in 28 patients (88%) and was usually seen with one or several foci in the myocardium. Foci were most frequently located in the lateral free wall. In the 21 patients in whom biopsy was obtained from the region of contrast enhancement, histopathologic analysis revealed active myocarditis in 19 patients (parvovirus B19, n=12; human herpes virus type 6 [HHV 6], n=5). Conversely, in the remaining 11 patients, in whom biopsy could not be taken from the region of contrast enhancement, active myocarditis was found in one case only (HHV6). At follow-up, the area of contrast enhancement decreased from 9+/-11% to 3+/-4% of left ventricular mass as the left ventricular ejection fraction improved from 47+/-19% to 60+/-10%. CONCLUSIONS: Contrast enhancement is a frequent finding in the clinical setting of suspected myocarditis and is associated with active inflammation defined by histopathology. Myocarditis occurs predominantly in the lateral free wall. Contrast CMR is a valuable tool for the evaluation and monitoring of inflammatory heart disease.

Background— Enteroviruses and adenoviruses have been considered the most common causes of viral myocarditis, but parvovirus B19 (PVB19) and human herpesvirus 6 (HHV6) are increasingly found in endomyocardial biopsy samples. Methods and Results— Consequently, our aim was to evaluate the prevalence and clinical presentation of cardiac PVB19 and/or HHV6 infection in a cohort of myocarditis patients and to follow its clinical course. In addition, we sought to demonstrate patterns of myocardial damage and to determine predictors for chronic heart failure. Our study design consisted of a cardiovascular magnetic resonance protocol as well as endomyocardial biopsies in the myocardial region affected as indicated by cardiovascular magnetic resonance. One hundred twenty-eight patients were enrolled by clinical criteria. In the group of myocarditis patients (n=87), PVB19 (n=49), HHV6 (n=16), and combined PVB19/HHV6 infections (n=15) were detected most frequently. The remaining patients were diagnosed with healing myocarditis (n=15) or did not have myocarditis (n=26). Patients with PVB19 presented in a manner similar to that of myocardial infarction; most had typical subepicardial late gadolinium enhancement in the lateral wall and recovered within months. Conversely, patients with HHV6 and especially with HHV6/PVB19 myocarditis presented with new onset of heart failure, had septal late gadolinium enhancement, and frequently progressed toward chronic heart failure. Conclusions— Our data indicate that PVB19 and HHV6 are the most important causes for viral myocarditis in Germany and that the clinical presentation is related to the type of virus. Furthermore, clinical presentation, type of virus, and pattern of myocardial damage are related to the clinical course.

This contribution provides a review of fundamental goals, development and future perspectives of driver assistance systems. Mobility is a fundamental desire of mankind. Virtually any society strives for safe and efficient mobility at low ecological and economic costs. Nevertheless, its technical implementation significantly differs among societies, depending on their culture and their degree of industrialization. A potential evolutionary roadmap for driver assistance systems is discussed. Emerging from systems based on proprioceptive sensors, such as ABS or ESC, we review the progress incented by the use of exteroceptive sensors such as radar, video, or lidar. While the ultimate goal of automated and cooperative traffic still remains a vision of the future, intermediate steps towards that aim can be realized through systems that mitigate or avoid collisions in selected driving situations. Research extends the state-of-the-art in automated driving in urban traffic and in cooperative driving, the latter addressing communication and collaboration between different vehicles, as well as cooperative vehicle operation by its driver and its machine intelligence. These steps are considered important for the interim period, until reliable unsupervised automated driving for all conceivable traffic situations becomes available. The prospective evolution of driver assistance systems will be stimulated by several technological, societal and market trends. The paper closes with a view on current research fields.

The detailed crop specific descriptions of the phenological growth stages of grapevine are supplementary to the general BBCH-scale. It will be instrumental in standardising the national and international experimentation in viticulture. The phenological development of the grapevine is divided into growth phases (principal growth stages 0–9) and each growth phase is subdivided into growth steps (secondary growth stages 0–9). A two-digit code is attached to each growth stage. The description and coding of the phenological growth stages covers the period between dormancy and leaf fall.

Spiking neural networks (SNNs) are inspired by information processing in biology, where sparse and asynchronous binary signals are communicated and processed in a massively parallel fashion. SNNs on neuromorphic hardware exhibit favorable properties such as low power consumption, fast inference, and event-driven information processing. This makes them interesting candidates for the efficient implementation of deep neural networks, the method of choice for many machine learning tasks. In this review, we address the opportunities that deep spiking networks offer and investigate in detail the challenges associated with training SNNs in a way that makes them competitive with conventional deep learning, but simultaneously allows for efficient mapping to hardware. A wide range of training methods for SNNs is presented, ranging from the conversion of conventional deep networks into SNNs, constrained training before conversion, spiking variants of backpropagation, and biologically motivated variants of STDP. The goal of our review is to define a categorization of SNN training methods, and summarize their advantages and drawbacks. We further discuss relationships between SNNs and binary networks, which are becoming popular for efficient digital hardware implementation. Neuromorphic hardware platforms have great potential to enable deep spiking networks in real-world applications. We compare the suitability of various neuromorphic systems that have been developed over the past years, and investigate potential use cases. Neuromorphic approaches and conventional machine learning should not be considered simply two solutions to the same classes of problems, instead it is possible to identify and exploit their task-specific advantages. Deep SNNs offer great opportunities to work with new types of event-based sensors, exploit temporal codes and local on-chip learning, and we have so far just scratched the surface of realizing these advantages in practical applications.