Fraunhofer-Gesellschaft

OBJECTIVE: To address the problem of volume conduction and active reference electrodes in the assessment of functional connectivity, we propose a novel measure to quantify phase synchronization, the phase lag index (PLI), and compare its performance to the well-known phase coherence (PC), and to the imaginary component of coherency (IC). METHODS: The PLI is a measure of the asymmetry of the distribution of phase differences between two signals. The performance of PLI, PC, and IC was examined in (i) a model of 64 globally coupled oscillators, (ii) an EEG with an absence seizure, (iii) an EEG data set of 15 Alzheimer patients and 13 control subjects, and (iv) two MEG data sets. RESULTS: PLI and PC were more sensitive than IC to increasing levels of true synchronization in the model. PC and IC were influenced stronger than PLI by spurious correlations because of common sources. All measures detected changes in synchronization during the absence seizure. In contrast to PC, PLI and IC were barely changed by the choice of different montages. PLI and IC were superior to PC in detecting changes in beta band connectivity in AD patients. Finally, PLI and IC revealed a different spatial pattern of functional connectivity in MEG data than PC. CONCLUSION: The PLI performed at least as well as the PC in detecting true changes in synchronization in model and real data but, at the same token and like-wise the IC, it was much less affected by the influence of common sources and active reference electrodes.

With the introduction of the Internet of Things (IoT) and cyber-physical system (CPS) concepts in industrial application scenarios, industrial automation is undergoing a tremendous change. This is made possible in part by recent advances in technology that allow interconnection on a wider and more fine-grained scale. The purpose of this article is to review technological trends and the impact they may have on industrial communication. We will review the impact of IoT and CPSs on industrial automation from an industry 4.0 perspective, give a survey of the current state of work on Ethernet time-sensitive networking (TSN), and shed light on the role of fifth-generation (5G) telecom networks in automation. Moreover, we will point out the need for harmonization beyond networking.

The anisotropic etching behavior of single‐crystal silicon and the behavior of SiO 2 and Si 3 N 4 in an ethylenediaminebased solution as well as in aqueous KOH , NaOH , and LiOH were studied. The crystal planes bounding the etch front and their etch rates were determined as a function of temperature, crystal orientation, and etchant composition. A correlation was found between the etch rates and their activation energies, with slowly etching crystal surfaces exhibiting higher activation energies and vice versa. For highly concentrated KOH solutions, a decrease of the etch rate with the fourth power of the water concentration was observed. Based on these results, an electrochemical model is proposed, describing the anisotropic etching behavior of silicon in all alkaline solutions. In an oxidation step, four hydroxide ions react with one surface silicon atom, leading to the injection of four electrons into the conduction band. These electrons stay localized near the crystal surface due to the presence of a space charge layer. The reaction is accompanied by the breaking of the backbonds, which requires the thermal excitation of the respective surface state electrons into the conduction band. This step is considered to be rate limiting. In a reduction step, the injected electrons react with water molecules to form new hydroxide ions and hydrogen. It is assumed that these hydroxide ions generated at the silicon surface are consumed in the oxidation reaction rather than those from the bulk electrolyte, since the latter are kept away from the crystal by the repellent force of the negative surface charge. According to this model, monosilicic acid Si ( OH ) 4 is formed as the primary dissolution product in all anisotropic silicon etchants. The anisotropic behavior is due to small differences of the energy levels of the backbond surface states as a function of the crystal orientation.

The W3C Semantic Sensor Network Incubator group (the SSN-XG) produced an OWL 2 ontology to describe sensors and observations — the SSN ontology, available at http://purl.oclc.org/NET/ssnx/ssn. The SSN ontology can describe sensors in terms of capabilities, measurement processes, observations and deployments. This article describes the SSN ontology. It further gives an example and describes the use of the ontology in recent research projects.

This paper presents details of a system that allows for an evolutionary introduction of depth perception into the existing 2D digital TV framework. The work is part of the European Information Society Technologies (IST) project "Advanced Three-Dimensional Television System Technologies" (ATTEST), an activity, where industries, research centers and universities have joined forces to design a backwards-compatible, flexible and modular broadcast 3D-TV system. At the very heart of the described new concept is the generation and distribution of a novel data representation format, which consists of monoscopic color video and associated per-pixel depth information. From these data, one or more "virtual" views of a real-world scene can be synthesized in real-time at the receiver side (i.e. a 3D-TV set-top box) by means of so-called depth-image-based rendering (DIBR) techniques. This publication will provide: (1) a detailed description of the fundamentals of this new approach on 3D-TV; (2) a comparison with the classical approach of "stereoscopic" video; (3) a short introduction to DIBR techniques in general; (4) the development of a specific DIBR algorithm that can be used for the efficient generation of high-quality "virtual" stereoscopic views; (5) a number of implementation details that are specific to the current state of the development; (6) research on the backwards-compatible compression and transmission of 3D imagery using state-of-the-art MPEG (Moving Pictures Expert Group) tools.

We investigated whether functional brain networks are abnormally organized in Alzheimer's disease (AD). To this end, graph theoretical analysis was applied to matrices of functional connectivity of beta band-filtered electroencephalography (EEG) channels, in 15 Alzheimer patients and 13 control subjects. Correlations between all pairwise combinations of EEG channels were determined with the synchronization likelihood. The resulting synchronization matrices were converted to graphs by applying a threshold, and cluster coefficients and path lengths were computed as a function of threshold or as a function of degree K. For a wide range of thresholds, the characteristic path length L was significantly longer in the Alzheimer patients, whereas the cluster coefficient C showed no significant changes. This pattern was still present when L and C were computed as a function of K. A longer path length with a relatively preserved cluster coefficient suggests a loss of complexity and a less optimal organization. The present study provides further support for the presence of "small-world" features in functional brain networks and demonstrates that AD is characterized by a loss of small-world network characteristics. Graph theoretical analysis may be a useful approach to study the complexity of patterns of interrelations between EEG channels.

The BCI competition IV stands in the tradition of prior BCI competitions that aim to provide high quality neuroscientific data for open access to the scientific community. As experienced already in prior competitions not only scientists from the narrow field of BCI compete, but scholars with a broad variety of backgrounds and nationalities. They include high specialists as well as students. The goals of all BCI competitions have always been to challenge with respect to novel paradigms and complex data. We report on the following challenges: (1) asynchronous data, (2) synthetic, (3) multi-class continuous data, (4) session-to-session transfer, (5) directionally modulated MEG, (6) finger movements recorded by ECoG. As after past competitions, our hope is that winning entries may enhance the analysis methods of future BCIs.

A new gas‐phase chemical mechanism for the modeling of regional atmospheric chemistry, the “Regional Atmospheric Chemistry Mechanism” (RACM) is presented. The mechanism is intended to be valid for remote to polluted conditions and from the Earth's surface through the upper troposphere. The RACM mechanism is based upon the earlier Regional Acid Deposition Model, version 2 (RADM2) mechanism [ Stockwell et al. , 1990] and the more detailed Euro‐RADM mechanism [ Stockwell and Kley , 1994]. The RACM mechanism includes rate constants and product yields from the most recent laboratory measurements, and it has been tested against environmental chamber data. A new condensed reaction mechanism is included for biogenic compounds: isoprene, α‐pinene, and d‐limonene. The branching ratios for alkane decay were reevaluated, and in the revised mechanism the aldehyde to ketone ratios were significantly reduced. The relatively large amounts of nitrates resulting from the reactions of unbranched alkenes with NO 3 are now included, and the production of HO from the ozonolysis of alkenes has a much greater yield. The aromatic chemistry has been revised through the use of new laboratory data. The yield of cresol production from aromatics was reduced, while the reactions of HO, NO 3 , and O 3 with unsaturated dicarbonyl species and unsaturated peroxynitrate are now included in the RACM mechanism. The peroxyacetyl nitrate chemistry and the organic peroxy radical‐peroxy radical reactions were revised, and organic peroxy radical +NO 3 reactions were added.

The present Communication compares the thermosensitivity in dilute aqueous solutions of well-defined copolymers composed of 95% of 2-(2-methoxyethoxy)ethyl methacrylate (MEO2MA) and 5% of oligo(ethylene glycol) methacrylate (OEGMA, Mn = 475 g.mol-1) and poly(N-isopropylacrylamide) (PNIPAM) samples having similar degrees of polymerization and chain-ends. The thermoresponsive behavior of P(MEO2MA-co-OEGMA) was found to be overall comparable, and in some cases, superior to PNIPAM. Hence, P(MEO2MA-co-OEGMA) copolymers can be considered as ideal structures, which combine both the properties of poly(ethylene glycol) and PNIPAM in a single macromolecule.

Electrical impedance tomography (EIT) has undergone 30 years of development. Functional chest examinations with this technology are considered clinically relevant, especially for monitoring regional lung ventilation in mechanically ventilated patients and for regional pulmonary function testing in patients with chronic lung diseases. As EIT becomes an established medical technology, it requires consensus examination, nomenclature, data analysis and interpretation schemes. Such consensus is needed to compare, understand and reproduce study findings from and among different research groups, to enable large clinical trials and, ultimately, routine clinical use. Recommendations of how EIT findings can be applied to generate diagnoses and impact clinical decision-making and therapy planning are required. This consensus paper was prepared by an international working group, collaborating on the clinical promotion of EIT called TRanslational EIT developmeNt stuDy group. It addresses the stated needs by providing (1) a new classification of core processes involved in chest EIT examinations and data analysis, (2) focus on clinical applications with structured reviews and outlooks (separately for adult and neonatal/paediatric patients), (3) a structured framework to categorise and understand the relationships among analysis approaches and their clinical roles, (4) consensus, unified terminology with clinical user-friendly definitions and explanations, (5) a review of all major work in thoracic EIT and (6) recommendations for future development (193 pages of online supplements systematically linked with the chief sections of the main document). We expect this information to be useful for clinicians and researchers working with EIT, as well as for industry producers of this technology.

A brain-computer interface (BCI) is a system that allows its users to control external devices with brain activity. Although the proof-of-concept was given decades ago, the reliable translation of user intent into device control commands is still a major challenge. Success requires the effective interaction of two adaptive controllers: the user's brain, which produces brain activity that encodes intent, and the BCI system, which translates that activity into device control commands. In order to facilitate this interaction, many laboratories are exploring a variety of signal analysis techniques to improve the adaptation of the BCI system to the user. In the literature, many machine learning and pattern classification algorithms have been reported to give impressive results when applied to BCI data in offline analyses. However, it is more difficult to evaluate their relative value for actual online use. BCI data competitions have been organized to provide objective formal evaluations of alternative methods. Prompted by the great interest in the first two BCI Competitions, we organized the third BCI Competition to address several of the most difficult and important analysis problems in BCI research. The paper describes the data sets that were provided to the competitors and gives an overview of the results.

A mapping between one frame from an image sequence and the preceding or following frame can be represented as a displacement vector field. In most situations, the mere gray value variations do not provide sufficient information in order to estimate such a displacement vector field. Supplementary constraints are necessary, for example the postulate that a displacement vector field varies smoothly as a function of the image position. Taken as a general requirement, this creates difficulties at gray value transitions which correspond to occluding contours. Nagel therefore introduced the ``oriented smoothness'' requirement which restricts variations of the displacement vector field only in directions with small or no variation of gray values. This contribution reports results of an investigation about how such an ``oriented smoothness'' constraint may be formulated and evaluated.

Art. e1000173, 10 S.

Data recorded in electroencephalogram (EEG)-based brain-computer interface experiments is generally very noisy, non-stationary, and contaminated with artifacts that can deteriorate discrimination/classification methods. In this paper, we extend the common spatial pattern (CSP) algorithm with the aim to alleviate these adverse effects. In particular, we suggest an extension of CSP to the state space, which utilizes the method of time delay embedding. As we will show, this allows for individually tuned frequency filters at each electrode position and, thus, yields an improved and more robust machine learning procedure. The advantages of the proposed method over the original CSP method are verified in terms of an improved information transfer rate (bits per trial) on a set of EEG-recordings from experiments of imagined limb movements.

Noninvasive electroencephalogram (EEG) recordings provide for easy and safe access to human neocortical processes which can be exploited for a brain-computer interface (BCI). At present, however, the use of BCIs is severely limited by low bit-transfer rates. We systematically analyze and develop two recent concepts, both capable of enhancing the information gain from multichannel scalp EEG recordings: 1) the combination of classifiers, each specifically tailored for different physiological phenomena, e.g., slow cortical potential shifts, such as the pre-movement Bereitschaftspotential or differences in spatio-spectral distributions of brain activity (i.e., focal event-related desynchronizations) and 2) behavioral paradigms inducing the subjects to generate one out of several brain states (multiclass approach) which all bare a distinctive spatio-temporal signature well discriminable in the standard scalp EEG. We derive information-theoretic predictions and demonstrate their relevance in experimental data. We will show that a suitably arranged interaction between these concepts can significantly boost BCI performances.

We propose a new measure (phase-slope index) to estimate the direction of information flux in multivariate time series. This measure (a) is insensitive to mixtures of independent sources, (b) gives meaningful results even if the phase spectrum is not linear, and (c) properly weights contributions from different frequencies. These properties are shown in extended simulations and contrasted to Granger causality which yields highly significant false detections for mixtures of independent sources. An application to electroencephalography data (eyes-closed condition) reveals a clear front-to-back information flow.

As part of the work of the Economic Commission for Europe of the United Nations Task Force on Emission Inventories, a new set of guidelines has been developed for assessing the emissions of sulphur, nitrogen oxides, NH3, CH4, and nonmethane volatile organic compounds (NMVOC) from biogenic and other natural sources in Europe. This paper gives the background to these guidelines, describes the sources, and gives our recommended methodologies for estimating emissions. We have assembled land use and other statistics from European or national compilations and present emission estimates for the various natural/biogenic source categories based on these. Total emissions from nature derived here amount to ∼1.1 Tg S yr−1, 6–8 Tg CH4yr−1, 70 Gg NH3(as N) yr−1, and 13 Tg NMVOC yr−1. Estimates of biogenic NOxemissions cover a wide range, from 140 to 1500 Gg NOx(as N) yr−1. In terms of relative contribution to total European emissions for different pollutants, then NMVOC from forests and vegetation are clearly the most important emissions source. Biogenic NOxemissions (although heavily influenced by nitrogen inputs from anthropogenic activities) are very important if the higher estimates are reliable. CH4from wetlands and sulphur from volcanoes are also significant emissions in the European budgets. On a global scale, European biogenic emissions are not significant, a consequence of the climate and size (7% of global land area) of Europe and of the destruction of natural ecosystems since prehistoric times. However, for assessing local budgets and for photochemical oxidant modeling, natural/biogenic emissions can play an important role. The most important contributor in this regard is undoubtedly forest VOC emissions, although this paper also indicates that NMVOC emissions from nonforested areas also need to be further evaluated. This paper was originally conceived as a contribution to the collection of papers arising as a result of the Workshop on Biogenic Hydrocarbons in the Atmospheric Boundary Layer, August 24–27, 1997. (Several papers arising from this workshop have been published inJournal of Geophysical Research, 103(D19) 1998.)

Noninvasive Brain Computer Interfaces (BCI) have been promoted to be used for neuroprosthetics. However, reports on applications with electroencephalography (EEG) show a demand for a better accuracy and stability. Here we investigate whether near-infrared spectroscopy (NIRS) can be used to enhance the EEG approach. In our study both methods were applied simultaneously in a real-time Sensory Motor Rhythm (SMR)-based BCI paradigm, involving executed movements as well as motor imagery. We tested how the classification of NIRS data can complement ongoing real-time EEG classification. Our results show that simultaneous measurements of NIRS and EEG can significantly improve the classification accuracy of motor imagery in over 90% of considered subjects and increases performance by 5% on average (p<0:01). However, the long time delay of the hemodynamic response may hinder an overall increase of bit-rates. Furthermore we find that EEG and NIRS complement each other in terms of information content and are thus a viable multimodal imaging technique, suitable for BCI.

Abstract Plastic in the global oceans fulfills two of the three conditions for pollution to pose a planetary boundary threat because it is causing planetary-scale exposure that is not readily reversible. Plastic is a planetary boundary threat if it is having a currently unrecognized disruptive effect on a vital Earth system process. Discovering possible unknown effects is likely to be aided by achieving a fuller understanding of the environmental fate of plastic. Weathering of plastic generates microplastic, releases chemical additives, and likely also produces nanoplastic and chemical fragments cleaved from the polymer backbone. However, weathering of plastic in the marine environment is not well understood in terms of time scales for fragmentation and degradation, the evolution of particle morphology and properties, and hazards of the chemical mixture liberated by weathering. Biofilms that form and grow on plastic affect weathering, vertical transport, toxicity, and uptake of plastic by marine organisms and have been underinvestigated. Laboratory studies, field monitoring, and models of the impact of weathering on plastic debris are needed to reduce uncertainty in hazard and risk assessments for known and suspected adverse effects. However, scientists and decision makers must also recognize that plastic in the oceans may have unanticipated effects about which we are currently ignorant. Possible impacts that are currently unknown can be confronted by vigilant monitoring of plastic in the oceans and discovery-oriented research related to the possible effects of weathering plastic.

We interpret several well-known algorithms for dimensionality reduction of manifolds as kernel methods. Isomap, graph Laplacian eigenmap, and locally linear embedding (LLE) all utilize local neighborhood information to construct a global embedding of the manifold. We show how all three algorithms can be described as kernel PCA on specially constructed Gram matrices, and illustrate the similarities and differences between the algorithms with representative examples.