Integration of electrical neuroimaging with other functional imaging methods

Integrating evidence from different imaging modalities is important to overcome specific limitations of any given imaging method, such as insensitivity of the EEG to unsynchronized neural events, or the lack of fMRI sensitivity to events of low metabolic demand. Processes that are visible in one modality may be related in a nontrivial way to other processes visible in another modality and insight may only be obtained by integrating both methods through a common analysis. For example, brain activity at rest seems to be at least partly determined by an interaction of cortical rhythms (visible to EEG but not to fMRI) with sub-cortical activity (visible to fMRI, but usually not to EEG without averaging). A combination of EEG and fMRI data during rest may thus be more informative than the sum of two separate analyses in both modalities. Integration is also an important source of converging evidence about specific aspects and general principles of neural functions and their dysfunctions in certain pathologies. This is because not only electrical, but also energetic, biochemical, hemodynamic and metabolic processes characterize neural states and functions, and because brain structure provides crucial constraints upon neural functions. Focusing on multimodal integration of functional data should not distract from the privileged status of the electric field as the primary direct, noninvasive real-time measure of neural transmission. The preceding chapters illustrate how electrical neuroimaging has turned scalp EEG into an imaging modality which directly captures the full temporal dynamics of neural activity in the brain.

Enterprise Integration of Smart Objects using Semantic Service Descriptions

Integrating physical objects (smart objects) and enterprise IT systems is still a labor intensive, mainly manual task done by domain experts. On one hand, enterprise IT backend systems are based on service oriented architectures (SOA) and driven by business rule engines or business process execution engines. Smart objects on the other hand are often programmed at very low levels. In this paper we describe an approach that makes the integration of smart objects with such backends systems easier. We introduce semantic endpoint descriptions based on Linked USDL. Furthermore, we show how different communication patterns can be integrated into these endpoint descriptions. The strength of our endpoint descriptions is that they can be used to automatically create REST or SOAP endpoints for enterprise systems, even if which they are not able to talk to the smart objects directly. We evaluate our proposed solution with CoAP, UDP and 6LoWPAN, as we anticipate the industry converge towards these standards. Nonetheless, our approach also allows easy integration with backend systems, even if no standardized protocol is used.

Integration of merged delayed-enhanced magnetic resonance imaging and multidetector computed tomography for the guidance of ventricular tachycardia ablation: a pilot study

BACKGROUND Delayed enhancement (DE) MRI can assess the fibrotic substrate of scar-related VT. MDCT has the advantage of inframillimetric spatial resolution and better 3D reconstructions. We sought to evaluate the feasibility and usefulness of integrating merged MDCT/MRI data in 3D-mapping systems for structure-function assessment and multimodal guidance of VT mapping and ablation. METHODS Nine patients, including 3 ischemic cardiomyopathy (ICM), 3 nonischemic cardiomyopathy (NICM), 2 myocarditis, and 1 redo procedure for idiopathic VT, underwent MRI and MDCT before VT ablation. Merged MRI/MDCT data were integrated in 3D-mapping systems and registered to high-density endocardial and epicardial maps. Low-voltage areas (<1.5 mV) and local abnormal ventricular activities (LAVA) during sinus rhythm were correlated to DE at MRI, and wall-thinning (WT) at MDCT. RESULTS Endocardium and epicardium were mapped with 391 ± 388 and 1098 ± 734 points per map, respectively. Registration of MDCT allowed visualization of coronary arteries during epicardial mapping/ablation. In the idiopathic patient, integration of MRI data identified previously ablated regions. In ICM patients, both DE at MRI and WT at MDCT matched areas of low voltage (overlap 94 ± 6% and 79 ± 5%, respectively). In NICM patients, wall-thinning areas matched areas of low voltage (overlap 63 ± 21%). In patients with myocarditis, subepicardial DE matched areas of epicardial low voltage (overlap 92 ± 12%). A total number of 266 LAVA sites were found in 7/9 patients. All LAVA sites were associated to structural substrate at imaging (90% inside, 100% within 18 mm). CONCLUSION The integration of merged MDCT and DEMRI data is feasible and allows combining substrate assessment with high-spatial resolution to better define structure-function relationship in scar-related VT.

Legal Integration of Islam: A Transatlantic Comparison

The status of Islam in Western societies remains deeply contentious. Countering strident claims on both the right and left, Legal Integration of Islam offers an empirically informed analysis of how four liberal democracies—France, Germany, Canada, and the United States—have responded to the challenge of integrating Islam and Muslim populations. Demonstrating the centrality of the legal system to this process, Christian Joppke and John Torpey reject the widely held notion that Europe is incapable of accommodating Islam and argue that institutional barriers to Muslim integration are no greater on one side of the Atlantic than the other. While Muslims have achieved a substantial degree of equality working through the courts, political dynamics increasingly push back against these gains, particularly in Europe. From a classical liberal viewpoint, religion can either be driven out of public space, as in France, or included without sectarian preference, as in Germany. But both policies come at a price—religious liberty in France and full equality in Germany. Often seen as the flagship of multiculturalism, Canada has found itself responding to nativist and liberal pressures as Muslims become more assertive. And although there have been outbursts of anti-Islamic sentiment in the United States, the legal and political recognition of Islam is well established and largely uncontested. Legal Integration of Islam brings to light the successes and the shortcomings of integrating Islam through law without denying the challenges that this religion presents for liberal societies.

Integration of WSNs into enterprise systems based on semantic physical business entities

Internet of Things based systems are anticipated to gain widespread use in industrial applications. Standardization efforts, like 6L0WPAN and the Constrained Application Protocol (CoAP) have made the integration of wireless sensor nodes possible using Internet technology and web-like access to data (RESTful service access). While there are still some open issues, the interoperability problem in the lower layers can now be considered solved from an enterprise software vendors' point of view. One possible next step towards integration of real-world objects into enterprise systems and solving the corresponding interoperability problems at higher levels is to use semantic web technologies. We introduce an abstraction of real-world objects, called Semantic Physical Business Entities (SPBE), using Linked Data principles. We show that this abstraction nicely fits into enterprise systems, as SPBEs allow a business object centric view on real-world objects, instead of a pure device centric view. The interdependencies between how currently services in an enterprise system are used and how this can be done in a semantic real-world aware enterprise system are outlined, arguing for the need of semantic services and semantic knowledge repositories. We introduce a lightweight query language, which we use to perform a quantitative analysis of our approach to demonstrate its feasibility.

Stratigraphic analysis of lake level fluctuations in Lake Ohrid: an integration of high resolution hydro-acoustic data and sediment cores

Abstract. Ancient Lake Ohrid is a steep-sided, oligotrophic, karst lake that was tectonically formed most likely within the Pliocene and often referred to as a hotspot of endemic biodiversity. This study aims on tracing significant lake level fluctuations at Lake Ohrid using high-resolution acoustic data in combination with lithological, geochemical, and chronological information from two sediment cores recovered from sub-aquatic terrace levels at ca. 32 and 60m water depth. According to our data, significant lake level fluctuations with prominent lowstands of ca. 60 and 35m below the present water level occurred during Marine Isotope Stage (MIS) 6 and MIS 5, respectively. The effect of these lowstands on biodiversity in most coastal parts of the lake is negligible, due to only small changes in lake surface area, coastline, and habitat. In contrast, biodiversity in shallower areas was more severely affected due to disconnection of today sublacustrine springs from the main water body. Multichannel seismic data from deeper parts of the lake clearly image several clinoform structures stacked on top of each other. These stacked clinoforms indicate significantly lower lake levels prior to MIS 6 and a stepwise rise of water level with intermittent stillstands since its existence as water-filled body, which might have caused enhanced expansion of endemic species within Lake Ohrid.

Quantitative 3D strain analysis in analogue experiments: Integration of X-ray computed tomography and digital volume correlation techniques

The combination of scaled analogue experiments, material mechanics, X-ray computed tomography (XRCT) and Digital Volume Correlation techniques (DVC) is a powerful new tool not only to examine the 3 dimensional structure and kinematic evolution of complex deformation structures in scaled analogue experiments, but also to fully quantify their spatial strain distribution and complete strain history. Digital image correlation (DIC) is an important advance in quantitative physical modelling and helps to understand non-linear deformation processes. Optical non-intrusive (DIC) techniques enable the quantification of localised and distributed deformation in analogue experiments based either on images taken through transparent sidewalls (2D DIC) or on surface views (3D DIC). X-ray computed tomography (XRCT) analysis permits the non-destructive visualisation of the internal structure and kinematic evolution of scaled analogue experiments simulating tectonic evolution of complex geological structures. The combination of XRCT sectional image data of analogue experiments with 2D DIC only allows quantification of 2D displacement and strain components in section direction. This completely omits the potential of CT experiments for full 3D strain analysis of complex, non-cylindrical deformation structures. In this study, we apply digital volume correlation (DVC) techniques on XRCT scan data of “solid” analogue experiments to fully quantify the internal displacement and strain in 3 dimensions over time. Our first results indicate that the application of DVC techniques on XRCT volume data can successfully be used to quantify the 3D spatial and temporal strain patterns inside analogue experiments. We demonstrate the potential of combining DVC techniques and XRCT volume imaging for 3D strain analysis of a contractional experiment simulating the development of a non-cylindrical pop-up structure. Furthermore, we discuss various options for optimisation of granular materials, pattern generation, and data acquisition for increased resolution and accuracy of the strain results. Three-dimensional strain analysis of analogue models is of particular interest for geological and seismic interpretations of complex, non-cylindrical geological structures. The volume strain data enable the analysis of the large-scale and small-scale strain history of geological structures.

The Integration of Electricity from Renewable Energy Sources in the European Union Electricity Market – The case for “Smart Grids”

The power sector is to play a central role in a low carbon economy. In all the decarbonisation scenarios of the European Union renewable energy sources (RES) will be a crucial part of the solution. Current grids constitute however major bottlenecks for the future expansion of RES. Recognising the need for a modernisation of its grids, the European Union has called for the creation of a "smart supergrid" interconnecting European grids at the continental level and making them "intelligent" through the addition of information and communication technology (ICT). To implement its agenda the EU has taken a leading role in coordinating research efforts and creating a common legislative framework for the necessary modernisation of Europe’s grids. This paper intends to give both an overview and a critical appraisal of the measures taken so far by the European Union to "transform" the grids into the backbone of a decarbonised electricity system. It suggests that if competition is to play a significant role in the deployment of smart grids, the current regulatory paradigm will have to be fundamentally reassessed

The role of learning-related dopamine signals in addiction vulnerability

Dopaminergic signals play a mathematically precise role in reward-related learning, and variations in dopaminergic signaling have been implicated in vulnerability to addiction. Here, we provide a detailed overview of the relationship between theoretical, mathematical, and experimental accounts of phasic dopamine signaling, with implications for the role of learning-related dopamine signaling in addiction and related disorders. We describe the theoretical and behavioral characteristics of model-free learning based on errors in the prediction of reward, including step-by-step explanations of the underlying equations. We then use recent insights from an animal model that highlights individual variation in learning during a Pavlovian conditioning paradigm to describe overlapping aspects of incentive salience attribution and model-free learning. We argue that this provides a computationally coherent account of some features of addiction.