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Figure-ground maps play a key role in many disciplines where urban planning or analysis is involved. In this context, the automatic generation of such maps with respect to certain requirements and constraints is an important task. This paper presents a first step towards a deep automatic generation of figure-ground maps where the built density of the generated scenes is controlled and taken into account. This is preformed building upon a Geographic Data Translation model which has been applied to generate less available geospatial features, e.g. building footprints, from more widely available geospatial data, e.g. street network data, using conditional Generative Adversarial Networks. A novel processing approach is introduced to incorporate the population density and the built density accordingly. Furthermore, the impact of both the level of detail of the street network, i.e. its sparsity or density, and the spatial resolution of the training data on the generated figure-ground maps has been investigated. The generated maps and the qualitative results reveal an obvious impact of these parameters on the layout of built and unbuilt areas. Our approach paves the way for the expansion of existing districts by figure-ground maps of future neighbourhoods considering factors such as density and further parameters which will be subject of future work.

Abstract A comparison between storm‐time TIMED/GUVI FUV spectra in thermospheric composition disturbed (O/N2 depleted and NO enhanced) and undisturbed regions reveals the following features: (1) A clear decrease in N2 LBHS (140–150 nm) band intensities compared to that between 150 and 160 nm; (2) A significant spectral decrease around O 164.1 nm; (3) Two enhanced peaks between 170 and 185 nm. The feature (2) is clearly due to atomic oxygen density decrease in the low thermosphere. The feature (3) is caused by storm‐time production and transport of nitric oxide. An AURIC simulation reproduced feature (1) confirming that storm‐time enhancement in O2 density (∼120–170 km) and the wavelength dependent O2 absorption cross section are the source of observed feature (1). On the other hand, the feature (1) was not observed in the regions without O/N2 depletion. This further supports that O2 density enhancement is responsible for feature (1).

Abstract Background Despite recent developments in THA, a more objective method is needed to assist orthopedic surgeons in identifying the insertion endpoint of the broaching procedure. Therefore, this systematic review evaluated the in-vivo efficacy of various acoustic and vibration analyses in detecting proper implant seating, identifying intraoperative complications, and quantifying the accuracy of predictive modeling using acoustics. Methods Four electronic databases were searched on July 23rd, 2023, to retrieve articles evaluating the use of acoustic analysis during THA. The search identified 835 unique articles, which were subsequently screened by two independent reviewers as per our inclusion and exclusion criteria. In total, 12 studies evaluating 580 THAs were found to satisfy our criteria and were included in this review. Results Methodologically, analyses have suggested stopping broaching when consecutive blows emit similar acoustic profiles (maximum peak frequency ± 0.5 kHz), which indicates proper implant seating in terms of stability and mitigates subsidence. Also, abrupt large deviations from the typical progression of acoustic signals while broaching are indicative of an intraoperative fracture. Since height, weight, femoral morphological parameters, and implant type have been shown to alter acoustic emissions while hammering, incorporating these factors into models to predict subsidence or intraoperative fracture yielded virtually 100% accuracy in identifying these adverse events. Conclusion These findings support that acoustic analyses during THA show promise as an accurate, objective, and non-invasive method to predict and detect proper implant fixation as well as to identify intraoperative fractures. Trial registration PROSPERO registration of the study protocol: CRD42023447889, 23 July 2023.