Energieeffizientes Fahren 2014 (EFA2014) - 2. Projektphase Erhöhung der Reichweite von Elektrofahrzeugen: Abschlussbericht

In AP 1.4 wurde ein Verfahren zur Schaltzeitprognose verkehrsabhängiger Lichtsignalanlagen entwickelt, welches auf eine Vielzahl weiterer Lichtsignalanlagen anwendbar ist. Weiterhin wurden (AP.1.4.5) im Bereich der spurgenauen Ortung, die auf Basis von GPS ermittelten Positionen durch Fusion mit anderen Sensordaten, wie der axialen Beschleunigungen und den Drehraten um die Fahrzeughochachse sowie der Einbeziehung einer digitalen Karte (Digital Enhanced Map), diese hinsichtlich einer Spurdetektion weiterhin verbessert. Im Bereich der Datenübertragung (LSA-Fzg.) konnte die erste Teilstrecke von der Verkehrsmanagementzentrale zum Serviceprovider im Labor untersucht werden. In AP 2.1 wurde eine auf der optimalen Steuerung basierte Methode zum Energiemanagement von seriellen Hybriden entwickelt. Die optimale Ansteuerung von Motor-Start-Stopp, Gangwahl und Momentenaufteilung wird modellprädiktiv unter Beachtung des Kraftstoffverbrauchs und der Schademissionen berechnet. Nach Anpassung auf praktische Randbedingungen, lässt sich diese Methode in zukünftigen Hybridfahrzeugen als optimales Energiemanagement nutzen. Die in AP 3.1 entwickelte Softwareumgebung zur gekoppelten Fahrzeug und Verkehrssimulation wurde an Beispielszenarien getestet. Für ein Modell der Versuchsstrecke wurde umfangreiche Analysen des Ampelassistenzfunktion in komplexen Verkehrsszenarien durchgeführt. Für eine Variation verschiedener Parameter, wie Wirkreichweite, Verkehrsstärke, usw. konnten Aussagen über das Potential getroffen werden. In Zusammenarbeit mit AP 3.3 wurde ein Ampelassistenzsystem und die Ansteuerung des Active-Force-Feedback Pedals im Demonstrator implementiert. In AP 3.3 wurde ein Konzept zur Darstellung von LSA-Daten im Fahrzeug erarbeitet. Dieses wurde in einem Versuchsträger umgesetzt. Dazu wurde der Versuchsträger hardwareseitig ertüchtigt, und für die Untersuchung verschiedener Varianten der Darstellung eingesetzt.:I. Versionsübersicht 4 II. Kurze Darstellung 5 1. Aufgabenstellung 5 2. Voraussetzungen 6 3. Planung und Ablauf des Vorhabens 7 4. Wissenschaftlicher und technischer Stand 8 5. Bekannte Konstruktionen, Verfahren und Schutzrechte 9 6. verwendete Fachliteratur und Informations- und Dokumentationsdienste 9 7. Zusammenarbeit mit anderen Stellen 10 III. Eingehende Darstellung 11 1. Arbeitsinhalte und erzielte Ergebnisse 11 AP 1.4: Datenmanagement 11 AP 2.1: Range-Extender-Betriebsstrategien 40 AP 3.1: Fahrstrategie 63 AP 3.3: Mensch-Maschine-Interface 73 2. Nutzen der Ergebnisse 81 3. Fortschritt bei anderen Stellen 82 4. Veröffentlichungen und studentische Arbeiten 83 Vorträge 83 Publikationen 83 Studentische Arbeiten 84 IV. Literaturverzeichnis 8

Biochemical markers of ongoing joint damage in rheumatoid arthritis - current and future applications, limitations and opportunities

Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease associated with potentially debilitating joint inflammation, as well as altered skeletal bone metabolism and co-morbid conditions. Early diagnosis and aggressive treatment to control disease activity offers the highest likelihood of preserving function and preventing disability. Joint inflammation is characterized by synovitis, osteitis, and/or peri-articular osteopenia, often accompanied by development of subchondral bone erosions, as well as progressive joint space narrowing. Biochemical markers of joint cartilage and bone degradation may enable timely detection and assessment of ongoing joint damage, and their use in facilitating treatment strategies is under investigation. Early detection of joint damage may be assisted by the characterization of biochemical markers that identify patients whose joint damage is progressing rapidly and who are thus most in need of aggressive treatment, and that, alone or in combination, identify those individuals who are likely to respond best to a potential treatment, both in terms of limiting joint damage and relieving symptoms. The aims of this review are to describe currently available biochemical markers of joint metabolism in relation to the pathobiology of joint damage and systemic bone loss in RA; to assess the limitations of, and need for additional, novel biochemical markers in RA and other rheumatic diseases, and the strategies used for assay development; and to examine the feasibility of advancement of personalized health care using biochemical markers to select therapeutic agents to which a patient is most likely to respond

An Optical Sensor Network for Vegetation Phenology Monitoring and Satellite Data Calibration

We present a network of sites across Fennoscandia for optical sampling of vegetation properties relevant for phenology monitoring and satellite data calibration. The network currently consists of five sites, distributed along an N-S gradient through Sweden and Finland. Two sites are located in coniferous forests, one in a deciduous forest, and two on peatland. The instrumentation consists of dual-beam sensors measuring incoming and reflected red, green, NIR, and PAR fluxes at 10-min intervals, year-round. The sensors are mounted on separate masts or in flux towers in order to capture radiation reflected from within the flux footprint of current eddy covariance measurements. Our computations and model simulations demonstrate the validity of using off-nadir sampling, and we show the results from the first year of measurement. NDVI is computed and compared to that of the MODIS instrument on-board Aqua and Terra satellite platforms. PAR fluxes are partitioned into reflected and absorbed components for the ground and canopy. The measurements demonstrate that the instrumentation provides detailed information about the vegetation phenology and variations in reflectance due to snow cover variations and vegetation development. Valuable information about PAR absorption of ground and canopy is obtained that may be linked to vegetation productivity

ESR1 and EGF genetic variation in relation to breast cancer risk and survival

The main purposes of this thesis were to analyse common genetic variation in candidate genes and candidate pathways in relation to breast cancer risk, prognosticators and survival, to develop statistical methods for genetic association analysis for evaluating the joint importance of genes, and to investigate the potential impact of adding genetic information to clinical risk factors for projecting individualised risk of developing breast cancer over specific time periods. In Paper I we studied genetic variation in the estrogen receptor α and epidermal growth factor genes in relation to breast cancer risk and survival. We located a region in the estrogen receptor α gene which showed a moderate signal for association with breast cancer risk but were unable to link common variation in the epidermal growth factor gene with breast cancer aetiology or prognosis. In Paper II we investigated whether suspected breast cancer risk SNPs within genes involved in androgen-to-estrogen conversion are associated with breast cancer prognosticators grade, lymph node status and tumour size. The strongest association was observed for a marker within the CYP19A1 gene with histological grade. We also found evidence that a second marker from the same gene is associated with histological grade and tumour size. In Paper III we developed a novel test of association which incorporates multivariate measures of categorical and continuous heterogeneity. In this work we described both a single-SNP and a global multi-SNP test and used simulated data to demonstrate the power of the tests when genetic effects differ across disease subtypes. In Paper IV we assessed the extent to which recently associated genetic risk variants improve breast cancer risk-assessment models. We investigated empirically the performance of eighteen breast cancer risk SNPs together with mammographic density and clinical risk factors in predicting absolute risk of breast cancer. We also examined the usefulness of various prediction models considered at a population level for a variety of individualised breast cancer screening approaches. The goal of a genetic association study is to establish statistical associations between genetic variants and disease states. Each variant linked to a disease can lead the way to a better understanding of the underlying biological mechanisms that govern the development of a disease. Increased knowledge of molecular variation provides the opportunity to stratify populations according to genetic makeup, which in turn has the potential to lead to improved disease prevention programs and improved patient care

Comparative genomics of Escherichia coli isolated from patients with inflammatory bowel disease

<p>Abstract</p> <p>Background</p> <p>Inflammatory bowel disease (IBD) is used to describe a state of idiopathic, chronic inflammation of the gastrointestinal tract. The two main phenotypes of IBD are Crohn's disease (CD) and ulcerative colitis (UC). The major cause of IBD-associated mortality is colorectal cancer. Although both host-genetic and exogenous factors have been found to be involved, the aetiology of IBD is still not well understood. In this study we characterized thirteen <it>Escherichia coli </it>strains from patients with IBD by comparative genomic hybridization employing a microarray based on 31 sequenced <it>E. coli </it>genomes from a wide range of commensal and pathogenic isolates.</p> <p>Results</p> <p>The IBD isolates, obtained from patients with UC and CD, displayed remarkably heterogeneous genomic profiles with little or no evidence of group-specific determinants. No IBD-specific genes were evident when compared with the prototypic CD isolate, LF82, suggesting that the IBD-inducing effect of the strains is multifactorial. Several of the IBD isolates carried a number of extraintestinal pathogenic <it>E. coli </it>(ExPEC)-related virulence determinants such as the <it>pap</it>, <it>sfa</it>, <it>cdt </it>and <it>hly </it>genes. The isolates were also found to carry genes of ExPEC-associated genomic islands.</p> <p>Conclusions</p> <p>Combined, these data suggest that <it>E. coli </it>isolates obtained from UC and CD patients represents a heterogeneous population of strains, with genomic profiles that are indistinguishable to those of ExPEC isolates. Our findings indicate that IBD-induction from <it>E. coli </it>strains is multifactorial and that a range of gene products may be involved in triggering the disease.</p