SALOS-A UWB Single-Anchor Indoor Localization System Based on a Statistical Multipath Propagation Model.

Among other methods, UWB-based multi-anchor localization systems have been established for industrial indoor localization systems. However, multi-anchor systems have high costs and installation effort. By exploiting the multipath propagation of the UWB signal, the infrastructure and thus the costs of conventional systems can be reduced. Our UWB Single-Anchor Localization System (SALOS) successfully pursues this approach. The idea is to create a localization system with sophisticated signal modeling. Therefore, measured reference, like fingerprinting or training, is not required for position estimation. Although SALOS has already been implemented and tested successfully in an outdoor scenario with multipath propagation, it has not yet been evaluated in an indoor environment with challenging and hardly predictable multipath propagation. For this purpose, we have developed new algorithms for the existing hardware, mainly a three-dimensional statistical multipath propagation model for arbitrary spatial geometries. The signal propagation between the anchor and predefined candidate points for the tag position is modeled in path length and complex-valued receive amplitudes. For position estimation, these modeled signals are combined to multiple sets and compared to UWB measurements via a similarity metric. Finally, a majority decision of multiple position estimates is performed. For evaluation, we implement our localization system in a modular fashion and install the system in a building. For a fixed grid of 20 positions, the localization is evaluated in terms of position accuracy. The system results in correct position estimations for more than 73% of the measurements.

AAV vectors displaying bispecific DARPins enable dual-control targeted gene delivery.

Precise delivery of genes to therapy-relevant cells is crucial for in vivo gene therapy. Receptor-targeting as prime strategy for this purpose is limited to cell types defined by a single cell-surface marker. Many target cells are characterized by combinations of more than one marker, such as the HIV reservoir cells. Here, we explored the tropism of adeno-associated viral vectors (AAV2) displaying designed ankyrin repeat proteins (DARPins) mono- and bispecific for CD4 and CD32a. Cryo-electron tomography revealed an unaltered capsid structure in the presence of DARPins. Surprisingly, bispecific AAVs transduced CD4/CD32a double-positive cells at much higher efficiencies than single-positive cells, even if present in low amounts in cell mixtures or human blood. This preference was confirmed when vector particles were systemically administered into mice. Cell trafficking studies revealed an increased cell entry rate for bispecific over monospecific AAVs. When equipped with an HIV genome-targeting CRISPR/Cas cassette, the vectors prevented HIV replication in T cell cultures. The data provide proof-of-concept for high-precision gene delivery through tandem-binding regions on AAV. Reminiscent of biological products following Boolean logic AND gating, the data suggest a new option for receptor-targeted vectors to improve the specificity and safety of in vivo gene therapy.

MA-RTI: Design and Evaluation of a Real-World Multipath-Assisted Device-Free Localization System.

Device-free localization (DFL) systems exploit changes in the radio frequency channel by measuring, for example, the channel impulse response (CIR), to detect and localize obstacles within a target area. However, due to a lack of well-defined interfaces, missing modularization, as well as complex system configuration, it is difficult to deploy DFL systems outside of laboratory setups. This paper focused on the system view and the challenges that come with setting up a DFL system in an indoor environment. We propose MA-RTI, a modular DFL system that is easy to set up, and which utilizes a multipath-assisted (MA) radio-tomographic imaging (RTI) algorithm. To achieve a modular DFL system, we proposed and implemented an architectural model for DFL systems. For minimizing the configuration overhead, we applied a 3D spatial model, that helps in placing the sensors and calculating the required calibration parameters. Therefore, we configured the system solely with idle measurements and a 3D spatial model. We deployed such a DFL system and evaluated it in a real-world office environment with four sensor nodes. The radio technology was ultra-wideband (UWB) and the corresponding signal measurements were CIRs. The DFL system operated with CIRs that provided a sub-nanosecond time-domain resolution. After pre-processing, the update rate was approximately 46 Hz and it provided a localization accuracy of 1.0 m in 50% of all cases and 1.8 m in 80% of all cases. MA fingerprinting approaches lead to higher localization accuracy, but require a labor-intensive training phase.