Hotspot Detection of Coastal Regions

The increasing sea level and number of extreme weather events due to the climate change, affects and imperils the coastal regions and with it the people and logistics located in these regions. In order to detect threatening trends, we develop an AI based hotspot detection software applying unsupervised methods

ARTIFACT DETECTION IN SAR IMAGES WITH AUTOENCODER METHODS

Automated evaluation of Earth Observation data gains in importance due to their increasing number. Autoencder (AE) have been successfully applied to change detection on optical images. Here, we compare three different convolutional AE methods for change detection on time series of radar data

Scientific Software Engineering: Mining Repositories to gain insights into BACARDI

For Space Situational Awareness, the German Aerospace Center (DLR) develops the software system "Backbone Catalogue of Relational Debris Information" (BACARDI), which allows for keeping track of resident space objects. BACARDI's key features are automated processing services which produce orbit information and products like collision warnings. We present how we applied new methods of software analytics to the BACARDI project. BACARDI is an example of a complex software system with large development effort carried out by a team of various specialists. Our goal is to design and implement an efficient software development process, balancing the explorative character of a research project and operational requirements (i.e. tailored from official standards in the aerospace domain). Therefore, we established a software development process for the project where we focus on software quality. We applied methods to structure, communicate, and utilize the diverse skills, knowledge, and experience in the team concisely and precisely. After one year of practical utilization, we analyzed the process based on the repository data. By analyzing these data, we assess and prove the effects of the introduced process on the development of a software, which is used in the aerospace domain

Regional opening strategies with commuter testing and containment of new SARS-CoV-2 variants

Background Despite the accelerating vaccination process, a large majority of the population is still susceptible to SARS-CoV-2. In addition, we face the spread of novel variants. Until we overcome the pandemic, reasonable mitigation and opening strategies are crucial to balance public health and economic interests. Methods We model the spread of SARS-CoV-2 over the German counties by a graph-SIR-type model with particular focus on commuter testing. We account for political interventions by varying contact reduction values in private and public locations such as homes, schools, workplaces, and other. We consider different levels of lockdown strictness, commuter testing strategies, or the delay of intervention implementation. We conduct numerical simulations to assess the effectiveness of the different intervention strategies after one month. The virus dynamics in the counties are initialized randomly with incidences between 75-150 weekly new cases per 100,000 inhabitants (red zones) or below 10 (green zones) and consider 25 different initial scenarios of randomly distributed red zones (between 2 and 20 % of all counties). To account for uncertainty, we consider an ensemble set of 500 Monte Carlo runs for each scenario. Results We find that the strength of the lockdown in regions with out of control virus dynamics is most important to avoid the spread into neighboring regions. With very strict lockdowns in red zones, commuter testing rates of twice a week can substantially contribute to the safety of adjacent regions. In contrast, less strict lockdowns with the same commuter testing rate quickly and substantially lead to overall higher infection dynamics. A further key contributor is the potential delay of the intervention implementation. In order to keep the spread of the virus under control, strict regional lockdowns with minimum delay and commuter testing of at least twice a week are advisable

Regional opening strategies with commuter testing and containment of new SARS-CoV-2 variants in Germany

Background Despite the vaccination process in Germany, a large share of the population is still susceptible to SARS-CoV-2. In addition, we face the spread of novel variants. Until we overcome the pandemic, reasonable mitigation and opening strategies are crucial to balance public health and economic interests. Methods We model the spread of SARS-CoV-2 over the German counties by a graph-SIR-type, metapopulation model with particular focus on commuter testing. We account for political interventions by varying contact reduction values in private and public locations such as homes, schools, workplaces, and other. We consider different levels of lockdown strictness, commuter testing strategies, or the delay of intervention implementation. We conduct numerical simulations to assess the effectiveness of the different intervention strategies after one month. The virus dynamics in the regions (German counties) are initialized randomly with incidences between 75 and 150 weekly new cases per 100,000 inhabitants (red zones) or below (green zones) and consider 25 different initial scenarios of randomly distributed red zones (between 2 and 20% of all counties). To account for uncertainty, we consider an ensemble set of 500 Monte Carlo runs for each scenario. Results We find that the strength of the lockdown in regions with out of control virus dynamics is most important to avoid the spread into neighboring regions. With very strict lockdowns in red zones, commuter testing rates of twice a week can substantially contribute to the safety of adjacent regions. In contrast, the negative effect of less strict interventions can be overcome by high commuter testing rates. A further key contributor is the potential delay of the intervention implementation. In order to keep the spread of the virus under control, strict regional lockdowns with minimum delay and commuter testing of at least twice a week are advisable. If less strict interventions are in favor, substantially increased testing rates are needed to avoid overall higher infection dynamics. Conclusions Our results indicate that local containment of outbreaks and maintenance of low overall incidence is possible even in densely populated and highly connected regions such as Germany or Western Europe. While we demonstrate this on data from Germany, similar patterns of mobility likely exist in many countries and our results are, hence, generalizable to a certain extent

Five Years of SMARTnet: Data, Processing, and Improvements

SMARTnet, operated by the Astronomical Institute of the University of Bern (AIUB) and the German Aerospace Center (DLR), went online and open to the public in 2017 with two telescope stations located in Zimmerwald, Switzerland, and Sutherland, South Africa. Over its five-year operational timespan, new partners have joined while one partner left, leaving telescope stations distributed today in Australia, South Africa, and Europe. All stations combined, 9 telescopes are actively providing data to the network. New contributors are currently in the applicant phase and will, together with further stations planned by DLR, enhance the network’s capabilities. The retrieved data is used for research, collision warnings, catalogue maintenance or for deriving data products, which can be sold to third parties. For the aforementioned points, the Backbone Catalogue of Relational Debris Information (BACARDI) was developed at DLR. BACARDI processes input data received from SMARTnet to data products such as ephemerides and orbit information for telescope observation planning, and attempts to detect new objects where an association of observations to already known objects is unsuccessful. To better operate the telescope stations, a dedicated software, called SMARTies, is under development in a joint project by AIUB and DLR. With this software, the telescope stations operations can be optimized to increase the daily data acquisition. It is planned to release SMARTies as Open Source software. To avoid deteriorating accuracy of the orbital information, ephemerides forecasted by BACARDI are combined with the planning tool “Optimal Catalog Maintenance and Survey Tasking” (OMST), which will help keeping all resident space objects in the data base. Furthermore, OMST will allow to search for new objects in the vicinity of the telescopes’ field of view in so-called “dead-times”. A short introduction to SMARTnet and its requirements is given, followed by some products retrieved from SMARTnet data. Also, the complete end-to-end chain from observations to processing, forecast, and its feed-back loop to observations is presented. Lastly, selected campaigns of some of the telescopes are presented. As part of non-regular observations, supporting observations can be acquired in case of special events (e.g. DART)

Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.NovartisEli Lilly and CompanyAstraZenecaAbbViePfizer UKCelgeneEisaiGenentechMerck Sharp and DohmeRocheCancer Research UKGovernment of CanadaArray BioPharmaGenome CanadaNational Institutes of HealthEuropean CommissionMinistère de l'Économie, de l’Innovation et des Exportations du QuébecSeventh Framework ProgrammeCanadian Institutes of Health Researc

Genome-wide association study of germline variants and breast cancer-specific mortality

BACKGROUND: We examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry. METHODS: Meta-analyses included summary estimates based on Cox models of twelve datasets using ~10

Flow-induced adhesion of shear-activated polymers to a substrate

Adhesion of polymers and proteins to substrates plays a crucial role in many technological applications and biological processes. A prominent example is the von Willebrand factor (VWF) protein, which is essential in blood clotting as it mediates adhesion of blood platelets to the site of injury at high shear rates. VWF is activated by flow and is able to bind efficiently to damaged vessel walls even under extreme flow-stress conditions; however, its adhesion is reversible when the flow strength is significantly reduced or the flow is ceased. Motivated by the properties and behavior of VWF in flow, we investigate adhesion of shear-activated polymers to a planar wall in flow and whether the adhesion is reversible under flow stasis. The main ingredients of the polymer model are cohesive inter-monomer interactions, a catch bond with the adhesive surface, and the shear activation/deactivation of polymer adhesion correlated with its stretching in flow. The cohesive interactions within the polymer maintain a globular conformation under low shear stresses and allow polymer stretching if a critical shear rate is exceeded, which is directly associated with its activation for adhesion. Our results show that polymer adhesion at high shear rates is significantly stabilized by catch bonds, while at the same time they also permit polymer dissociation from a surface at low or no flow stresses. In addition, the activation/deactivation mechanism for adhesion plays a crucial role in the reversibility of its adhesion. These observations help us better understand the adhesive behavior of VWF in flow and interpret its adhesion malfunctioning in VWF-related diseases