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We propose a novel approach for semantic segmentation of building facades. Our system consists of three distinct layers, representing different levels of abstraction in facade images: segments, objects and architectural elements. In the first layer, the facade is segmented into regions, each of which is assigned a probability distribution over semantic classes. We evaluate different state-of-the-art segmentation and classification strategies to obtain the initial probabilistic semantic labeling. In the second layer, we investigate the performance of different object detectors and show the benefit of using such detectors to improve our initial labeling. The generic approaches of the first two layers are then specialized for the task of facade labeling in the third layer. There, we incorporate additional meta-knowledge in the form of weak architectural principles , which enforces architectural plausibility and consistency on the final reconstruction. Rigorous tests performed on two existing datasets of building facades demonstrate that we outperform the current state of the art, even when using outputs from lower layers of the pipeline. Finally, we demonstrate how the output of the highest layer can be used to create a procedural building reconstruction.

Necrosis is a form of cell death that occurs only under pathological conditions such as ischemic diseases and traumatic brain injury （TBI）. Non-invasive imaging of the affected tissue is a key component of novel therapeutic interventions and measurement of treatment responses in patients. Here, we report a bimodal approach for the detection and monitoring of TBI. PEGylated poly（lactic-coglycolic acid） （PLGA） nanoparticles （NPs）, encapsulating both near infrared （NIR） fluorophores and perfluorocarbons （PFCs）, were targeted to necrotic ceils. We used cyanine dyes such as IRDye 800CW, for which we have previously demonstrated specific targeting to intracellular proteins of cells that have lost membrane integrity. Here, we show specific in vivo detection of necrosis by optical imaging and fluorine magnetic resonance imaging （^19F MRI） using newly designed PLGA NP（NIR700 ＋ PFC）-PEG-800CW. Quantitative ex vivo optical imaging and ^19F MR spectroscopy of NIR-PFC content in injured brain regions and in major organs were well correlated. Both modalities allowed the in vivo identification of necrotic brain lesions in a mouse model of TBI, with optical imaging being more sensitive than ^19F MRI. Our results confirm increased blood pool residence time of PLGA NPs coated with a PEG layer and the successful targeting of TBI-damaged tissue. A single PLGA NP containing NIR-PFC enables both rapid qualitative optical monitoring of the TBI state and quantitative 3D information from deeper tissues on the extent of the lesion by MRI. These necrosis-targeting PLGA NPs can potentially be used for clinical diagnosis of brain injuries.

Tracking in urban street scenes plays a central role in autonomous systems such as self-driving cars. Most of the current vision-based tracking methods perform tracking in the image domain. Other approaches, eg based on LIDAR and radar, track purely in 3D. While some vision-based tracking methods invoke 3D information in parts of their pipeline, and some 3D-based methods utilize image-based information in components of their approach, we propose to use image- and world-space information jointly throughout our method. We present our tracking pipeline as a 3D extension of image-based tracking. From enhancing the detections with 3D measurements to the reported positions of every tracked object, we use world-space 3D information at every stage of processing. We accomplish this by our novel coupled 2D-3D Kalman filter, combined with a conceptually clean and extendable hypothesize-and-select framework. Our approach matches the current state-of-the-art on the official KITTI benchmark, which performs evaluation in the 2D image domain only. Further experiments show significant improvements in 3D localization precision by enabling our coupled 2D-3D tracking.

Semantic image segmentation is an essential component of modern autonomous driving systems, as an accurate understanding of the surrounding scene is crucial to navigation and action planning. Current state-of-the-art approaches in semantic image segmentation rely on pre-trained networks that were initially developed for classifying images as a whole. While these networks exhibit outstanding recognition performance (i.e., what is visible?), they lack localization accuracy (i.e., where precisely is something located?). Therefore, additional processing steps have to be performed in order to obtain pixel-accurate segmentation masks at the full image resolution. To alleviate this problem we propose a novel ResNet-like architecture that exhibits strong localization and recognition performance. We combine multi-scale context with pixel-level accuracy by using two processing streams within our network: One stream carries information at the full image resolution, enabling precise adherence to segment boundaries. The other stream undergoes a sequence of pooling operations to obtain robust features for recognition. The two streams are coupled at the full image resolution using residuals. Without additional processing steps and without pre-training, our approach achieves an intersection-over-union score of 71.8% on the Cityscapes dataset.

CA19-9 values are regularly measured in patients with pancreatic cancer. Certainly, its potential as a biomarker has been compromised by false negative results in CA19-9 negative patients and false positive results in benign pancreatico-biliary diseases. For detection of PDAC recurrence, however, CA19-9 might play an important role. The aim of this study is to analyze the accuracy of CA19-9 for detecting recurrence of pancreatic cancer. All included patients were treated either at the University Medical Center Goettingen, or at the Department of Interdisciplinary Oncology and Pneumonology, DRK-Kliniken Nordhessen, Kassel. We analyzed data of 93 patients with pancreatic cancer in the training set and 41 in the validation set, both retrospectively. Pre- and postoperative CA19-9 values and results of imaging techniques were compared. We performed ROC-analysis. The association between longitudinally measured CA19-9 values and relapse was studied with a joint model between a random effects model for the longitudinal CA19-9 measurements and a Cox proportional hazards models for the survival data. In the test set (n = 93 patients) the median follow-up time was 644 days (22 months). Overall, 71 patients (76.3%) developed recurrence during follow-up. Patients with CA19-9 values of <10kU/l were considered as CA19-9 negative patients (n = 11) and excluded from further analysis. Among the rest, approximately 60% of the patients showed significantly elevated CA19-9 prior to detection of recurrence by imaging techniques. Recurrence was shown by 2.45 times elevated CA19-9 values with 90% positive predictive value. In the validation set, 2.45 times elevated CA19-9 values showed recurrence with 90% sensitivity and 83,33% specificity, with an area under the curve of 95%. Based on measured CA19-9 values during follow-up care, the joint model estimates in recurrence-free patients the probability of recurrence-free survival. CA19-9 elevation is an early and reliable sign for PDAC recurrence. On the strength of a very high accuracy in CA19-9 positive patients, it should be considered to use CA19-9 for therapy decision even without a correlate of imaging technics. Using the joint model, follow-up care of PDAC patients after curative therapy can be stratified.

Brucellosis, a worldwide common bacterial zoonotic disease, has become quite rare in Northern and Western Europe. However, since 2014 a significant increase of imported infections caused by Brucella (B.) melitensis has been noticed in Germany. Patients predominantly originated from Middle East including Turkey and Syria. These circumstances afforded an opportunity to gain insights into the population structure of Brucella strains. Brucella-isolates from 57 patients were recovered between January 2014 and June 2016 with culture confirmed brucellosis by the National Consultant Laboratory for Brucella. Their whole genome sequences were generated using the Illumina MiSeq platform. A whole genome-based SNP typing assay was developed in order to resolve geographically attributed genetic clusters. Results were compared to MLVA typing results, the current gold-standard of Brucella typing. In addition, sequences were examined for possible genetic variation within target regions of molecular diagnostic assays. Phylogenetic analyses revealed spatial clustering and distinguished strains from different patients in either case, whereas multiple isolates from a single patient or technical replicates showed identical SNP and MLVA profiles. By including WGS data from the NCBI database, five major genotypes were identified. Notably, strains originating from Turkey showed a high diversity and grouped into seven subclusters of genotype II. MLVA analysis congruently clustered all isolates and predominantly matched the East Mediterranean genetic clade. This study confirms whole-genome based SNP-analysis as a powerful tool for accurate typing of B. melitensis. Furthermore it allows special allocation and therefore provides useful information on the geographic origin for trace-back analysis. However, the lack of reliable metadata in public databases often prevents a resolution below geographic regions or country levels and corresponding precise trace-back analysis. Once this obstacle is resolved, WGS-derived bacterial typing adds an important method to complement epidemiological surveys during outbreak investigations. This is the first report of a detailed genetic investigation of an extensive collection of B. melitensis strains isolated from human cases in Germany.

Cells maintain the balance between homeostasis and inflammation by adapting and integrating the activity of intracellular signaling cascades, including the JAK-STAT pathway. Our understanding of how a tailored switch from homeostasis to a strong receptor-dependent response is coordinated remains limited. Here, we use an integrated transcriptomic and proteomic approach to analyze transcription-factor binding, gene expression and in vivo proximity-dependent labelling of proteins in living cells under homeostatic and interferon (IFN)-induced conditions. We show that interferons (IFN) switch murine macrophages from resting-state to induced gene expression by alternating subunits of transcription factor ISGF3. Whereas preformed STAT2-IRF9 complexes control basal expression of IFN-induced genes (ISG), both type I IFN and IFN-γ cause promoter binding of a complete ISGF3 complex containing STAT1, STAT2 and IRF9. In contrast to the dogmatic view of ISGF3 formation in the cytoplasm, our results suggest a model wherein the assembly of the ISGF3 complex occurs on DNA. A rapid cellular response to interferons (IFNs) is critical for establishing antimicrobial immunity, but how cells switch from from homeostasis to IFN signaling is not fully understood. Here, the authors provide evidence that IFNs induce gene expression by alternating subunits of transcription factor ISGF3.

Understanding the transfer of spin angular momentum is essential in modern magnetism research. A model case is the generation of magnons in magnetic insulators by heating an adjacent metal film. Here, we reveal the initial steps of this spin Seebeck effect with <27 fs time resolution using terahertz spectroscopy on bilayers of ferrimagnetic yttrium iron garnet and platinum. Upon exciting the metal with an infrared laser pulse, a spin Seebeck current j s arises on the same ~100 fs time scale on which the metal electrons thermalize. This observation highlights that efficient spin transfer critically relies on carrier multiplication and is driven by conduction electrons scattering off the metal–insulator interface. Analytical modeling shows that the electrons’ dynamics are almost instantaneously imprinted onto j s because their spins have a correlation time of only ~4 fs and deflect the ferrimagnetic moments without inertia. Applications in material characterization, interface probing, spin-noise spectroscopy and terahertz spin pumping emerge. Probing spin pumping in the terahertz regime allows one to reveal its initial elementary steps. Here, the authors show that the formation of the spin Seebeck current in YIG/Pt critically relies on hot thermalized metal electrons because they impinge on the metal-insulator interface with maximum noise.

In December, 2019, the newly identified severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, China, causing COVID-19, a respiratory disease presenting with fever, cough, and often pneumonia. WHO has set the strategic objective to interrupt spread of SARS-CoV-2 worldwide. An outbreak in Bavaria, Germany, starting at the end of January, 2020, provided the opportunity to study transmission events, incubation period, and secondary attack rates. A case was defined as a person with SARS-CoV-2 infection confirmed by RT-PCR. Case interviews were done to describe timing of onset and nature of symptoms and to identify and classify contacts as high risk (had cumulative face-to-face contact with a confirmed case for ≥15 min, direct contact with secretions or body fluids of a patient with confirmed COVID-19, or, in the case of health-care workers, had worked within 2 m of a patient with confirmed COVID-19 without personal protective equipment) or low risk (all other contacts). High-risk contacts were ordered to stay at home in quarantine for 14 days and were actively followed up and monitored for symptoms, and low-risk contacts were tested upon self-reporting of symptoms. We defined fever and cough as specific symptoms, and defined a prodromal phase as the presence of non-specific symptoms for at least 1 day before the onset of specific symptoms. Whole genome sequencing was used to confirm epidemiological links and clarify transmission events where contact histories were ambiguous; integration with epidemiological data enabled precise reconstruction of exposure events and incubation periods. Secondary attack rates were calculated as the number of cases divided by the number of contacts, using Fisher's exact test for the 95% CIs. Patient 0 was a Chinese resident who visited Germany for professional reasons. 16 subsequent cases, often with mild and non-specific symptoms, emerged in four transmission generations. Signature mutations in the viral genome occurred upon foundation of generation 2, as well as in one case pertaining to generation 4. The median incubation period was 4·0 days (IQR 2·3–4·3) and the median serial interval was 4·0 days (3·0–5·0). Transmission events were likely to have occurred presymptomatically for one case (possibly five more), at the day of symptom onset for four cases (possibly five more), and the remainder after the day of symptom onset or unknown. One or two cases resulted from contact with a case during the prodromal phase. Secondary attack rates were 75·0% (95% CI 19·0–99·0; three of four people) among members of a household cluster in common isolation, 10·0% (1·2–32·0; two of 20) among household contacts only together until isolation of the patient, and 5·1% (2·6–8·9; 11 of 217) among non-household, high-risk contacts. Although patients in our study presented with predominately mild, non-specific symptoms, infectiousness before or on the day of symptom onset was substantial. Additionally, the incubation period was often very short and false-negative tests occurred. These results suggest that although the outbreak was controlled, successful long-term and global containment of COVID-19 could be difficult to achieve. All authors are employed and all expenses covered by governmental, federal state, or other publicly funded institutions.

The realization of quantum spin Hall effect in HgTe quantum wells is considered a milestone in the discovery of topological insulators. Quantum spin Hall states are predicted to allow current flow at the edges of an insulating bulk, as demonstrated in various experiments. A key prediction yet to be experimentally verified is the breakdown of the edge conduction under broken time-reversal symmetry. Here we first establish a systematic framework for the magnetic field dependence of electrostatically gated quantum spin Hall devices. We then study edge conduction of an inverted quantum well device under broken time-reversal symmetry using microwave impedance microscopy, and compare our findings to a non-inverted device. At zero magnetic field, only the inverted device shows clear edge conduction in its local conductivity profile, consistent with theory. Surprisingly, the edge conduction persists up to 9 T with little change. This indicates physics beyond simple quantum spin Hall model, including material-specific properties and possibly many-body effects. Quantum spin Hall edge states are protected by time-reversal symmetry and are expected to disappear in a strong magnetic field. Here, the authors use microwave impedance microscopy and find, surprisingly, edge conduction in mercury telluride quantum wells that survives up to 9 T with little change.