80 research outputs found
Improvement of source localization by dynamical systems based modelling
Summary: Recently, we have proposed a new concept for analyzing EEG/MEG data (Uhl et al. 1998), which leads to a dynamical systems based modeling (DSBM) of neurophysiological data. We report the application of this approach to four different classes of simulated noisy data sets, to investigate the impact of DSBM-filtering on source localization. An improvement is demonstrated of up to above 50 % of the distance between simulated and estimated dipole positions compared to principal component filtered and unfiltered data. On a noise level on which two underlying dipoles cannot be resolved from the unfiltered data, DSBM allows for an extraction of the two sources
Using an OCL Impact Analysis Algorithm for View-Based Textual Modelling
The Object Constraint Language (OCL) has become a vital part of many frameworks, tools and languages within model-driven engineering. One such application of OCL is the use for describing rules in concrete syntax definitions. Within the textual modeling framework FURCAS, OCL is extensively used for the definition of lookup and attribution rules. Based on these rules the model which is described by such a textual representation is created and updated accordingly. Changes on models over which such an expression is specified require the expression to be re-evaluated to keep the constructed model up-to-date. However, the effort for re-evaluating OCL expressions over a set of model elements grows with the number of elements, the complexity of the expressions, and the number of model changes. Thus, having large models and/or complex expressions places considerable performance costs on OCL evaluation. Techniques to reduce this effort have been presented in previous work but do not cover the full range of OCL expressions, in particular calls to operations defined in OCL, including recursive operations. In this paper, we present an approach that is applicable to the full range of OCL expressions. We validated our approach based on a large set of models and complex expressions to evaluate the performance impact of our newly introduced techniques
Development of concepts for a climate-neutral chemical-pharmaceutical industry in 2045
Global primary energy consumption has increased tenfold over the course of the 20th Century, the availability of non-renewable energy is becoming scarce, and the burning of fossil fuels is leading to global warming. Climate change has now become tangible. The will to act against fossil fuels has become apparent in the western world, and in Germany in particular. This poses a particular challenge for the chemical and pharmaceutical industry, since, in the future, not only will the energy input, but also the feedstock, have to come from non-fossil sources. They must be replaced by carbon capture and utilization, and the exploitation of a circular economy. Concepts for a climate-neutral chemical–pharmaceutical industry have been developed and evaluated. Due to a high predicted consumption of renewable energies and an insufficient expansion of these, Germany will remain an energy importer in the future. The largest consumer in a climate-neutral chemical–pharmaceutical industry will be electrolysis for hydrogen (up to 81%, 553 TWh/a). This can be circumvented by importing green ammonia and cracking. This will require investments of EUR 155 bn. An additional benefit will be increased independence from fossil resource imports, as green ammonia can be produced in a multitude of nations with strong potential for renewable energies and a diversified set of exporting nations
Establishment of a research focus on resilient sustainable climate neutral agricultural production: resilient farming initiative
Efficient and sustainable agricultural production is a pivotal factor in meeting the nutritional needs of an expanding global population. However, it is imperative to optimize national, regional and local effectiveness to support government initiatives towards climate neutrality and resilience, while simultaneously ensuring economic viability for farmers. A significant reduction in the cost of goods must be accompanied by a decrease in their global warming potential contribution to maintain competitiveness in the world market. As such, it is necessary to adopt practices that enhance productivity while minimizing environmental impacts. This paper discusses potential solutions for the sustainable enlargement of botanical product portfolios towards essential oil products and natural extracts for value-added products, such as natural pharmaceuticals, cosmetics, agrochemicals and materials by direct waste valorization. Contributions from the fields of automation and digitalization provide the basic technology for the realization of the approaches presented. Agricultural photovoltaics can contribute to the goal of the reduction of the cost of goods and global warming potential, such as the already established utilization of biogas. The potential of the research initiative described is demonstrated by basic data on key characteristic numbers and costs from the literature. The economic potential for climate neutrality and the reduction of global warming potential contribution is seen in magnitudes of factors 5–10. A research initiative is recommended and exemplified for the industrialization of such integrated processing
Navigating Across Non-Navigable Ecore References via OCL
The Eclipse Modeling Framework (EMF) and its meta-meta model Ecore support uni-directional and bi-directional references. It is quite common that references are defined uni-directionally only because of saving storage space or separating meta models, which is problematic when implementing Object Constraint Language (OCL) constraints that require navigation against the direction of uni-directional references. This is essential for certain approaches, e.g., incremental evaluation of OCL constraints on models shown by Altenhofen et al. that is used in SAP's Modeling Infrastructure (MOIN). In this paper, we present an approach that overcomes the aforementioned issue by providing navigation across non-navigable Ecore references via OCL. We further discuss different alternative solutions and briefly describe the realization that was outcome of a project in cooperation with the SAP AG
Distinct chemokine receptor expression profiles in de novo DLBCL, transformed follicular lymphoma, Richter’s trans-formed DLBCL and germinal center B-cells
Implementation of effect biomarkers in human biomonitoring studies: A systematic approach synergizing toxicological and epidemiological knowledge
ReviewHuman biomonitoring (HBM) studies have highlighted widespread daily exposure to environmental chemicals. Some of these are suspected to contribute to adverse health outcomes such as reproductive, neurological, and metabolic disorders, among other developmental and chronic impairments. One of the objectives of the H2020 European Human Biomonitoring Initiative (HBM4EU) was the development of informative effect biomarkers for application in a more systematic and harmonized way in large-scale European HBM studies. The inclusion of effect biomarkers would complement exposure data with mechanistically-based information on early and late adverse effects. For this purpose, a stepwise strategy was developed to identify and implement a panel of validated effect biomarkers in European HBM studies.
This work offers an overview of the complete procedure followed, from comprehensive literature search strategies, selection of criteria for effect biomarkers and their classification and prioritization, based on toxicological data and adverse outcomes, to pilot studies for their analytical, physiological, and epidemiological validation. We present the example of one study that demonstrated the mediating role of the effect biomarker status of brain-derived neurotrophic factor BDNF in the longitudinal association between infant bisphenol A (BPA) exposure and behavioral function in adolescence.
A panel of effect biomarkers has been implemented in the HBM4EU Aligned Studies as main outcomes, including traditional oxidative stress, reproductive, and thyroid hormone biomarkers. Novel biomarkers of effect, such as DNA methylation status of BDNF and kisspeptin (KISS) genes were also evaluated as molecular markers of neurological and reproductive health, respectively. A panel of effect biomarkers has also been applied in HBM4EU occupational studies, such as micronucleus analysis in lymphocytes and reticulocytes, whole blood comet assay, and malondialdehyde, 8-oxo-2′-deoxyguanosine and untargeted metabolomic profile in urine, to investigate, for example, biological changes in response to hexavalent chromium Cr(VI) exposure.
The use of effect biomarkers in HBM4EU has demonstrated their ability to detect early biological effects of chemical exposure and to identify subgroups that are at higher risk. The roadmap developed in HBM4EU confirms the utility of effect biomarkers, and support one of the main objectives of HBM research, which is to link exposure biomarkers to mechanistically validated effect and susceptibility biomarkers in order to better understand the public health implications of human exposure to environmental chemicals.Supported by the European Union's Horizon 2020 research and innovation program projects HBM4EU [grant number 733032]info:eu-repo/semantics/publishedVersio
A systematic approach synergizing toxicological and epidemiological knowledge
Funding Information: This work was supported by the European Union's Horizon 2020 research and innovation program projects HBM4EU [grant number 733032 ]. Authors acknowledge the editorial assistance of Richard Davies. Publisher Copyright: © 2023 The Author(s)Human biomonitoring (HBM) studies have highlighted widespread daily exposure to environmental chemicals. Some of these are suspected to contribute to adverse health outcomes such as reproductive, neurological, and metabolic disorders, among other developmental and chronic impairments. One of the objectives of the H2020 European Human Biomonitoring Initiative (HBM4EU) was the development of informative effect biomarkers for application in a more systematic and harmonized way in large-scale European HBM studies. The inclusion of effect biomarkers would complement exposure data with mechanistically-based information on early and late adverse effects. For this purpose, a stepwise strategy was developed to identify and implement a panel of validated effect biomarkers in European HBM studies. This work offers an overview of the complete procedure followed, from comprehensive literature search strategies, selection of criteria for effect biomarkers and their classification and prioritization, based on toxicological data and adverse outcomes, to pilot studies for their analytical, physiological, and epidemiological validation. We present the example of one study that demonstrated the mediating role of the effect biomarker status of brain-derived neurotrophic factor BDNF in the longitudinal association between infant bisphenol A (BPA) exposure and behavioral function in adolescence. A panel of effect biomarkers has been implemented in the HBM4EU Aligned Studies as main outcomes, including traditional oxidative stress, reproductive, and thyroid hormone biomarkers. Novel biomarkers of effect, such as DNA methylation status of BDNF and kisspeptin (KISS) genes were also evaluated as molecular markers of neurological and reproductive health, respectively. A panel of effect biomarkers has also been applied in HBM4EU occupational studies, such as micronucleus analysis in lymphocytes and reticulocytes, whole blood comet assay, and malondialdehyde, 8-oxo-2′-deoxyguanosine and untargeted metabolomic profile in urine, to investigate, for example, biological changes in response to hexavalent chromium Cr(VI) exposure. The use of effect biomarkers in HBM4EU has demonstrated their ability to detect early biological effects of chemical exposure and to identify subgroups that are at higher risk. The roadmap developed in HBM4EU confirms the utility of effect biomarkers, and support one of the main objectives of HBM research, which is to link exposure biomarkers to mechanistically validated effect and susceptibility biomarkers in order to better understand the public health implications of human exposure to environmental chemicals.publishersversionpublishe
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