Evaluating eGovernment in the Large - A Requirements Oriented Approach

An increasing level of cooperation between public administrations nowadays on national, regional and local level requires methods to develop interoperable eGovernment systems and leads to the necessity of an efficient evaluation and requirements engineering process. In this paper, we propose a framework to systematically gather and evaluate requirements for eGovernment in the large. The evaluation framework is designed to help requirements engineers to develop a suitable evaluation and requirements engineering process. The methodology is motivated and explained on the basis of a European research project

Prototyping and Evaluation of Infrastructure-assisted Transition of Control for Cooperative Automated Vehicles

Automated driving is now possible in diverse road and traffic conditions. However, there are still situations that automated vehicles cannot handle safely and efficiently. In this case, a Transition of Control (ToC) is necessary so that the driver takes control of the driving. Executing a ToC requires the driver to get full situation awareness of the driving environment. If the driver fails to get back the control in a limited time, a Minimum Risk Maneuver (MRM) is executed to bring the vehicle into a safe state (e.g., decelerating to full stop). The execution of ToCs requires some time and can cause traffic disruption and safety risks that increase if several vehicles execute ToCs/MRMs at similar times and in the same area. This study proposes to use novel C-ITS traffic management measures where the infrastructure exploits V2X communications to assist Connected and Automated Vehicles (CAVs) in the execution of ToCs. The infrastructure can suggest a spatial distribution of ToCs, and inform vehicles of the locations where they could execute a safe stop in case of MRM. This paper reports the first field operational tests that validate the feasibility and quantify the benefits of the proposed infrastructure-assisted ToC and MRM management. The paper also presents the CAV and roadside infrastructure prototypes implemented and used in the trials. The conducted field trials demonstrate that infrastructure-assisted traffic management solutions can reduce safety risks and traffic disruption

The Biochemical and Cellular Basis for Nutraceutical Strategies to Attenuate Neurodegeneration in Parkinson’s Disease

Future therapeutic intervention that could effectively decelerate the rate of degeneration within the substantia nigra pars compacta (SNc) could add years of mobility and reduce morbidity associated with Parkinson’s disease (PD). Neurodegenerative decline associated with PD is distinguished by extensive damage to SNc dopaminergic (DAergic) neurons and decay of the striatal tract. While genetic mutations or environmental toxins can precipitate pathology, progressive degenerative succession involves a gradual decline in DA neurotransmission/synaptic uptake, impaired oxidative glucose consumption, a rise in striatal lactate and chronic inflammation. Nutraceuticals play a fundamental role in energy metabolism and signaling transduction pathways that control neurotransmission and inflammation. However, the use of nutritional supplements to slow the progression of PD has met with considerable challenge and has thus far proven unsuccessful. This review re-examines precipitating factors and insults involved in PD and how nutraceuticals can affect each of these biological targets. Discussed are disease dynamics (Sections 1 and 2) and natural substances, vitamins and minerals that could impact disease processes (Section 3). Topics include nutritional influences on α-synuclein aggregation, ubiquitin proteasome function, mTOR signaling/lysosomal-autophagy, energy failure, faulty catecholamine trafficking, DA oxidation, synthesis of toxic DA-quinones, o-semiquinones, benzothiazolines, hyperhomocyseinemia, methylation, inflammation and irreversible oxidation of neuromelanin. In summary, it is clear that future research will be required to consider the multi-faceted nature of this disease and re-examine how and why the use of nutritional multi-vitamin-mineral and plant-based combinations could be used to slow the progression of PD, if possible

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

EU_MAVEN D3.3: Cooperative maneouvre and trajectory planning algorithms

This deliverable is the textual description of the cooperative manoeuvre and trajectory planning algorithm which have been designed and implemented by DLR and HMETC for MAVEN. An overview of different modules of vehicle automation is given. The trajectory planning and tactical and strategical modules and their roles on cooperation are explained. Furthermore, cooperation with infrastructure in the form of AGLOSA and lane change and cooperation with other automated vehicle in the form of platooning is described. Functionality of the algorithms is approved by simulation results, close field tests and urban tests in close relation to WP4, WP6 and WP7

EU_MAVEN D3.2: Cooperative environment perception algorithms

This document describes the project achievements in cooperative perception algorithm development and testing. An overview of the building blocks, vehicle setups and embeddings of the perception algorithms into the test vehicle architectures used within the experiments at DLR and HMETC is given. A review of the state-of-the-art outlines the different levels of sophistication that are known from literature for the association and data fusion steps of a cooperative environment perception algorithm and reflects recent developments in the field. Real time algorithms are explained that were used in the experiments and demonstrations at the HMETC test site with both HMETC and DLR vehicles involved. Fusion experiments demonstrate detection and perception of a pedestrian not in sight of the ego vehicle sensors via a collective perception (CPM) message and combining of position estimates received via a cooperative awareness message (CAM) with the sensor detections of a test vehicle. Based on the results of the state-of-the-art review, an advanced fusion algorithm is proposed and its performance in urban traffic scenarios as well as Monte Carlo simulation scenarios evaluated. Conclusions are drawn for cooperative perception algorithm development and testing. This deliverable serves (in combination with D3.3) as basis for the testing done in WP6 with its upcoming deliverable D6.4 and the evaluation done in WP7 with its upcoming deliverable D7.2. The developments, experiments and evaluations presented in this deliverable have been executed by the MAVEN project partners HMETC and DLR in tight cooperation