Choosing Suitable Indicators for the Assessment of Urban Air Mobility: A Case Study of Upper Bavaria, Germany

Technological advances are disrupting mobility patterns and transport technologies, both on the ground and in the air. The latter has been recently observed in the research community of urban air mobility (UAM). Research in this area has studied several areas of its implementation, such as vehicle concepts, infrastructure, transport modeling, or operational constraints. Few studies however have focused on evaluating this service as an alternative among existing transportation systems. This research presents an approach for the selection of indicators for a multi-criteria analysis for the assessment of UAM, in a case study of Upper Bavaria, Germany. A 5-stage approach is showcased including an expert assessment for the relevance and feasibility of indicators, based on two rating scales. A threshold for selection is presented, applied and validated for both scales. The results included a list of indicators for assessing the potentials of UAM integration to existing public transportation systems; the chosen indicators were then compared against existing ones for sustainable urban mobility. A high match between resulting indicators and previous ones further validate the results, and suggest that there is a need for an iterative approach in the assessment of disruptive transport technologies

Detection of Borrelia burgdorferi sensu-lato-Specific Antibodies in Sera of Canine and Equine Origin—A Comparative Study with Two Line Immunoassays

Lyme borreliosis is a vector-borne disease in humans and animals caused by bacteria from the Borrelia burgdorferi sensu lato complex (Bbsl). The possible transmission of Bbsl from companion animals to humans via ticks makes this disease important in terms of One Health approaches. Thus, early and accurate diagnosis and treatment are of utmost importance. Today’s standard for the detection of specific antibodies against Bbsl is a two-tiered test system based on an ELISA for screening combined with a line immunoassay (LIA) for confirmation. In this study, 200 canine and 200 equine serum samples with known antibody status were tested with two different LIAs (A and B). Results were compared regarding sensitivity, specificity, the diagnostic outcome for dogs and horses, as well as operability of the test. The results for canine serum samples corresponded to 94.0%, making both LIAs a good choice for LB diagnostic in dogs. For equine serum samples, the agreement of both tests was 65.5%, displaying the challenge equine samples still provide in LB diagnostic. Major concerns were the interpretation of the OspA antigen (AG) signal and the use of unspecific (i.e., p100/p83) or too sensitive signals on the LIA. The operability of both LIAs was equally user-friendly. Regarding the tests’ evaluation, the scanning process provided by LIA A was a major advantage considering the comparability of the tests

Bedarf für die Paketzustellung durch Drohnen – eine Alternative für die Versorgung schwer erreichbarer Gebiete?

The supply of the North Frisian Islands and Halligen is strongly characterized by their dependency on tides, weather, and seasons. This study examines whether supplying these difficult-to-reach areas with transport drones would have the potential to fill possible supply gaps to contribute to the alignment of living conditions with those of the mainland. Qualitative interviews with stakeholders in the region indicate that the seasonality of ferries leads to supply constraints, especially for time-critical goods. Although local residents have developed adaptation strategies such as stockpiling, there are always short-term unmet needs for specialty goods. A drone concept developed using existing regional supply routes shows that the use of drones has the potential to improve the supply situation by supplementing existing shipping. However, the majority of respondents are skeptical about the use of drones. The concerns expressed are mainly related to environmental protection, sustainability, tourist appeal, and the ability of drones to operate in adverse weather conditions. Thus, it can be seen that the acceptance of new technologies by the population is a core challenge for the successful solution of supply bottlenecks by transport drones and must receive central attention in addition to the investigation of the technical and economic feasibility of such concepts.Die Versorgung der nordfriesischen Inseln und Halligen ist stark durch ihre Tiden‑, Witterungs- und Saisonabhängigkeit geprägt. Die vorliegende Untersuchung prüft, ob eine Belieferung dieser schwierig zu erreichenden Gebiete mit Transportdrohnen das Potenzial hätte, mögliche Versorgungslücken zu schließen, um zur Angleichung der Lebensverhältnisse an die des Festlands beizutragen. Qualitative Interviews mit Stakeholdern der Region zeigen, dass die Saisonalität der Fähren zu Einschränkungen in der Versorgung, vor allem mit zeitkritischen Gütern, führt. Obwohl die Anwohner*innen Anpassungsstrategien wie Vorratshaltung entwickelt haben, gibt es immer wieder kurzfristig unerfüllten Bedarf an Spezialgütern. Ein anhand bestehender regionaler Versorgungsrouten erarbeitetes Drohnenkonzept zeigt, dass die Nutzung von Drohnen das Potenzial hat, durch Ergänzung des bestehenden Schiffsverkehrs die Versorgungssituation zu verbessern. Allerdings ist der Großteil der Befragten dem Einsatz von Drohnen gegenüber skeptisch. Die geäußerten Bedenken beziehen sich hauptsächlich auf Umweltschutz, Nachhaltigkeit, touristische Attraktivität und die Einsatzfähigkeit von Drohnen bei widrigem Wetter. Somit zeigt sich, dass die Akzeptanz neuer Technologien durch die Bevölkerung eine Kernherausforderung für die erfolgreiche Lösung von Versorgungsengpässen durch Transportdrohnen ist und neben der Untersuchung der technischen und ökonomischen Machbarkeit solcher Konzepte zentrale Beachtung finden muss

Detection of Leptospira DNA in urine and presence of specific antibodies in outdoor cats in Germany

Objectives Clinical manifestation of infection with Leptospira species in cats is rare. Nevertheless, cats can develop specific antibodies against the spirochetes after infection. In Canada, Taiwan and the USA it was recently demonstrated that naturally infected cats can also shed DNA from pathogenic Leptospira species in their urine, but the zoonotic potential of infected cats is still unclear. The objective of this study was to demonstrate if outdoor cats in Germany shed DNA from pathogenic Leptospira species in their urine. As a second aim, antibody prevalence was determined. Methods Two hundred and fifteen outdoor cats were prospectively recruited. Urine samples were tested by realtime PCR targeting the lipL32 gene of pathogenic Leptospira species. Antibody titres against eight serovars (Australis, Autumnalis, Bratislava, Canicola, Copenhageni, Grippotyphosa, Pomona, Saxkoebing) belonging to seven serogroups (Australis, Autumnalis, Canicola, Grippotyphosa, Icterohaemorrhagiae, Pomona, Sejroe) were determined by microscopic agglutination test. Results Urine samples from 7/215 cats (3.3%;95% confidence interval [CI] 0.9-5.7) were PCR-positive. Specific antibodies were detected in 35/195 cats (17.9%;95% CI: 12.5-23.3) with titres ranging from 1:100 to 1:6400. Australis, Bratislava and Grippotyphosa were the most common serovars. Conclusions and relevance Outdoor cats in Germany can shed DNA from pathogenic Leptospira species. Therefore, outdoor cats should be considered as a possible source of infection for dogs or humans. Further studies are needed to determine the role of Leptospira species as a cause of disease in cats

A Novel Rapid Sample Preparation Method for MALDI-TOF MS Permits Borrelia burgdorferi Sensu Lato Species and Isolate Differentiation

The genus Borrelia comprises vector-borne bacterial pathogens that can severely affect human and animal health. Members of the Borrelia burgdorferi sensu lato species complex can cause Lyme borreliosis, one of the most common vector-borne diseases in the Northern hemisphere. Besides, members of the relapsing fever group of spirochetes can cause tick-borne relapsing fever in humans and various febrile illnesses in animals in tropical, subtropical and temperate regions. Borrelia spp. organisms are fastidious to cultivate and to maintain in vitro, and therefore, difficult to work with in the laboratory. Currently, borrelia identification is mainly performed using PCR and DNA sequencing methods, which can be complicated/frustrating on complex DNA templates and may still be relatively expensive. Alternative techniques such as matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) are not well established for Borrelia spp., although this technique is currently one of the most used techniques for rapid identification of bacteria in microbiological diagnostic laboratories. This is mainly due to unsatisfactory results obtained by use of simple sample preparation techniques and medium-contamination obscuring the mass spectra. In addition, comprehensive libraries for Borrelia spp. MALDI-TOF MS have yet to be established. In this study, we developed a new filter-based chemical extraction technique that allows measurement of high quality Borrelia spp. spectra from less than 100,000 bacteria per spot in MALDI-TOF MS. We used 49 isolates of 13 different species to produce the largest mass-library for Borrelia spp. so far and to validate the protocol. The library was successfully established and identifies >96% of used isolates correctly to species level. Cluster analysis on the sum spectra was applied to all the different isolates, which resulted in tight cluster generation for most species. Comparative analysis of the generated cluster to a phylogeny based on concatenated multi-locus sequence typing genes provided a surprising homology. Our data demonstrate that the technique described here can be used for fast and reliable species and strain typing within the borrelia complex

Leptospira spp. strain identification by MALDI TOF MS is an equivalent tool to 16S rRNA gene sequencing and multi locus sequence typing (MLST)

Background: In this study mass spectrometry was used for evaluating extracted leptospiral protein samples and results were compared with molecular typing methods. For this, an extraction protocol for Leptospira spp. was independently established in two separate laboratories. Reference spectra were created with 28 leptospiral strains, including pathogenic, non-pathogenic and intermediate strains. This set of spectra was then evaluated on the basis of measurements with well-defined, cultured leptospiral strains and with 16 field isolates of veterinary or human origin. To verify discriminating peaks for the applied pathogenic strains, statistical analysis of the protein spectra was performed using the software tool ClinProTools. In addition, a dendrogram of the reference spectra was compared with phylogenetic trees of the 16S rRNA gene sequences and multi locus sequence typing (MLST) analysis. Results: Defined and reproducible protein spectra using MALDI-TOF MS were obtained for all leptospiral strains. Evaluation of the newly-built reference spectra database allowed reproducible identification at the species level for the defined leptospiral strains and the field isolates. Statistical analysis of three pathogenic genomospecies revealed peak differences at the species level and for certain serovars analyzed in this study. Specific peak patterns were reproducibly detected for the serovars Tarassovi, Saxkoebing, Pomona, Copenhageni, Australis, Icterohaemorrhagiae and Grippotyphosa. Analysis of the dendrograms of the MLST data, the 16S rRNA sequencing, and the MALDI-TOF MS reference spectra showed comparable clustering. Conclusions: MALDI-TOF MS analysis is a fast and reliable method for species identification, although Leptospira organisms need to be produced in a time-consuming culture process. All leptospiral strains were identified, at least at the species level, using our described extraction protocol. Statistical analysis of the three genomospecies L. borgpetersenii, L. interrogans and L. kirschneri revealed distinctive, reproducible differentiating peaks for seven leptospiral strains which represent seven serovars. Results obtained by MALDI-TOF MS were confirmed by MLST and 16S rRNA gene sequencing

Analysis of mass spectrometry data from the secretome of an explant model of articular cartilage exposed to pro-inflammatory and anti-inflammatory stimuli using machine learning

Background: Osteoarthritis (OA) is an inflammatory disease of synovial joints involving the loss and degeneration of articular cartilage. The gold standard for evaluating cartilage loss in OA is the measurement of joint space width on standard radiographs. However, in most cases the diagnosis is made well after the onset of the disease, when the symptoms are well established. Identification of early biomarkers of OA can facilitate earlier diagnosis, improve disease monitoring and predict responses to therapeutic interventions. Methods: This study describes the bioinformatic analysis of data generated from high throughput proteomics for identification of potential biomarkers of OA. The mass spectrometry data was generated using a canine explant model of articular cartilage treated with the pro-inflammatory cytokine interleukin 1 β (IL-1β). The bioinformatics analysis involved the application of machine learning and network analysis to the proteomic mass spectrometry data. A rule based machine learning technique, BioHEL, was used to create a model that classified the samples into their relevant treatment groups by identifying those proteins that separated samples into their respective groups. The proteins identified were considered to be potential biomarkers. Protein networks were also generated; from these networks, proteins pivotal to the classification were identified. Results: BioHEL correctly classified eighteen out of twenty-three samples, giving a classification accuracy of 78.3% for the dataset. The dataset included the four classes of control, IL-1β, carprofen, and IL-1β and carprofen together. This exceeded the other machine learners that were used for a comparison, on the same dataset, with the exception of another rule-based method, JRip, which performed equally well. The proteins that were most frequently used in rules generated by BioHEL were found to include a number of relevant proteins including matrix metalloproteinase 3, interleukin 8 and matrix gla protein. Conclusions: Using this protocol, combining an in vitro model of OA with bioinformatics analysis, a number of relevant extracellular matrix proteins were identified, thereby supporting the application of these bioinformatics tools for analysis of proteomic data from in vitro models of cartilage degradation

The long-run effects of urban air mobility: An urban spatial equilibrium assessment

This dissertation makes use of urban spatial computable general equilibrium (USCGE) models tailored towards the application to urban transport in general and urban air transport specifically. The thesis assesses the effects of urban air mobility (UAM) introduction and hopes to contribute to the young field of research by providing evidence on possible long-run effects of transport drones. In recent years there has been a strong increase in research output in the field of UAM. The studies on the topic are wide-spread discipline-wise, reaching from vehicle design over UTM, regulation and certification to acceptance and adoption. Not only research, but also business activities are strongly increasing. Yet, UAM still faces technical, infrastructural and societal hurdles on the way to introduction. One of the main hurdles is the support of authorities, policy makers and the public. To enable a supporting environment early on, it is important to provide tools and methods that enable an assessment of the long-run effects of transport drones. Making use of USCGE models, this thesis broadens the discussion on UAM impacts to include also welfare effects, environmental aspects, and differentiate between the impacts on different parts of society. Applying a USCGE model to an existent transportation issue, namely parking, gives confidence in the chosen method. Tailoring the model to UAM and incorporating both high- and low-skilled households enables us to derive several interesting findings. Using agglomeration effects and amenities the model allows to differentiate between cities where high-skilled locate close to the city-centre and cities where high-skilled rather move to the suburbs. Differentiating between both initial spatial structures shows that the impact that the city structure has on the impact of UAM introduction, is minor. UAM system characteristics, like, land demand, prices, marginal cost or travel speed, in contrast significantly impact direction and magnitude of welfare effects. We find that the welfare effects for households with different income levels strongly differ and hence want to emphasise the relevance of understanding the differential impacts of UAM on user and non-users. Expanding the assessment to also include electric ground mobility and explicitly considering the environmental effects of UAM introduction shows that differences in taxation between gasoline and electricity lead to welfare losses when a forced transition from gasoline cars to electric cars takes place, while CO2 emissions go down. The higher tax on gasoline compared to electricity, as it is currently in place in Germany, results in a better internalization of otherwise untackled congestion externalities and hence explains this somewhat unexpected effect. The model also provides evidence, that introducing UAM as a substitute for gasoline cars has the potential to reduce CO2 emissions, whereas serving as an alternative to electric cars UAM usage increases CO2 emissions due to higher energy demand. Drones can also be used for cargo transport. In order to understand these effects as well the USCGE model is adapted to model different retail channels (local shops, online shopping and delivery via drone and online shopping with delivery via truck) and the logistic structures behind them. The assessment shows that additional retail channel choice options increase welfare and that the rise of e-commerce could significantly impact location choices in cities. This research shows that especially the long-run impact of passenger and cargo drones on users as well as non-users need consideration when assessing promising applications. From an environmental perspective, it is essential to identify applications that either allow to save energy due to shorter routes (e.g. due to geographical barriers), or justify the additional energy use due to the value added by the service (e.g. emergency applications or generating parity in living conditions)

Identification of Relevant Aspects for Personal Air Transport System Integration in Urban Mobility Modelling

This research evaluates relevant prerequisites for Personal Air Transport System (PATS) introduction into the urban transport modelling environment. Integrating Personal Air Vehicles (PAV) into existing transport systems poses various questions, which have to be thoroughly assessed. Therefore, different possible concepts of operations are being discussed, including not only ownership structure but also aspects like the adaptability of schedules (on-demand vs. scheduled services). Furthermore different demand drivers, such as job, housing, and retail location, user behaviour and mode choice are being presented with a digression on possible impacts on the city structure. In addition to that, potential cities for PAV introduction and the required properties are examined. Finally, different state-of-the-art approaches for transport modelling are constituted in order to lay the foundation for further research