Ariel - Volume 3 Number 5

Editors Richard J. Bonanno Robin A. Edwards Associate Editors Steven Ager Tom Williams Lay-out Editor Eugenia Miller Contributing Editors Paul Bialas Robert Breckenridge Lynne Porter David Jacoby Terry Burt Mark Pearlman Michael Leo Mike LeWitt Editors Emeritus Delvyn C. Case., Jr. Paul M. Fernhof

Multiscale benchmarking of drug delivery vectors

Cross-system comparisons of drug delivery vectors are essential to ensure optimal design. An in-vitro experimental protocol is presented that separates the role of the delivery vector from that of its cargo in determining the cell response, thus allowing quantitative comparison of different systems. The technique is validated through benchmarking of the dose–response of human fibroblast cells exposed to the cationic molecule, polyethylene imine (PEI); delivered as a free molecule and as a cargo on the surface of CdSe nanoparticles and Silica microparticles. The exposure metrics are converted to a delivered dose with the transport properties of the different scale systems characterized by a delivery time, τ. The benchmarking highlights an agglomeration of the free PEI molecules into micron sized clusters and identifies the metric determining cell death as the total number of PEI molecules presented to cells, determined by the delivery vector dose and the surface density of the cargo

Pressure measurements in a low-density nozzle plume for code verification

Measurements of Pitot pressure were made in the exit plane and plume of a low-density, nitrogen nozzle flow. Two numerical computer codes were used to analyze the flow, including one based on continuum theory using the explicit MacCormack method, and the other on kinetic theory using the method of direct-simulation Monte Carlo (DSMC). The continuum analysis was carried to the nozzle exit plane and the results were compared to the measurements. The DSMC analysis was extended into the plume of the nozzle flow and the results were compared with measurements at the exit plane and axial stations 12, 24 and 36 mm into the near-field plume. Two experimental apparatus were used that differed in design and gave slightly different profiles of pressure measurements. The DSMC method compared well with the measurements from each apparatus at all axial stations and provided a more accurate prediction of the flow than the continuum method, verifying the validity of DSMC for such calculations

Analysis of the Influence of Cell Heterogeneity on Nanoparticle Dose Response

Understanding the effect of variability in the interaction of individual cells with nanoparticles on the overall response of the cell population to a nanoagent is a fundamental challenge in bionanotechnology. Here, we show that the technique of time-resolved, high-throughput microscopy can be used in this endeavor. Mass measurement with single-cell resolution provides statistically robust assessments of cell heterogeneity, while the addition of a temporal element allows assessment of separate processes leading to deconvolution of the effects of particle supply and biological response. We provide a specific demonstration of the approach, in vitro, through time-resolved measurement of fibroblast cell (HFF-1) death caused by exposure to cationic nanoparticles. The results show that heterogeneity in cell area is the major source of variability with area-dependent nanoparticle capture rates determining the time of cell death and hence the form of the exposure–response characteristic. Moreover, due to the particulate nature of the nanoparticle suspension, there is a reduction in the particle concentration over the course of the experiment, eventually causing saturation in the level of measured biological outcome. A generalized mathematical description of the system is proposed, based on a simple model of particle depletion from a finite supply reservoir. This captures the essential aspects of the nanoparticle–cell interaction dynamics and accurately predicts the population exposure–response curves from individual cell heterogeneity distributions

Deep Interference Mitigation and Denoising of Real-World FMCW Radar Signals

Radar sensors are crucial for environment perception of driver assistance systems as well as autonomous cars. Key performance factors are a fine range resolution and the possibility to directly measure velocity. With a rising number of radar sensors and the so far unregulated automotive radar frequency band, mutual interference is inevitable and must be dealt with. Sensors must be capable of detecting, or even mitigating the harmful effects of interference, which include a decreased detection sensitivity. In this paper, we evaluate a Convolutional Neural Network (CNN)-based approach for interference mitigation on real-world radar measurements. We combine real measurements with simulated interference in order to create input-output data suitable for training the model. We analyze the performance to model complexity relation on simulated and measurement data, based on an extensive parameter search. Further, a finite sample size performance comparison shows the effectiveness of the model trained on either simulated or real data as well as for transfer learning. A comparative performance analysis with the state of the art emphasizes the potential of CNN-based models for interference mitigation and denoising of real-world measurements, also considering resource constraints of the hardware.Comment: 2020 IEEE International Radar Conference (RADAR

Indoor wireless communications and applications

Chapter 3 addresses challenges in radio link and system design in indoor scenarios. Given the fact that most human activities take place in indoor environments, the need for supporting ubiquitous indoor data connectivity and location/tracking service becomes even more important than in the previous decades. Specific technical challenges addressed in this section are(i), modelling complex indoor radio channels for effective antenna deployment, (ii), potential of millimeter-wave (mm-wave) radios for supporting higher data rates, and (iii), feasible indoor localisation and tracking techniques, which are summarised in three dedicated sections of this chapter

Unterschiede und Gemeinsamkeiten in der Bodenwasserdynamik unterschiedlicher Wald- und Ackerstandorte

Die standörtliche Bodenwasserdynamik wird wesentlich durch die Landnutzung, Vegetation, Bodeneigenschaften und Witterung bestimmt. Um in einer Region ein hydrologisches Modell erfolgreich anwenden zu können, ist es notwendig, den Bodenwasserhaushalt in seiner zeitlichen und räumlichen Ausprägung richtig abzubilden. Im Rahmen des vom BMBF geförderten Verbundprojektes „Nachhaltiges Landma-nagement im Norddeutschen Tiefland“ (NaLaMa-nT) wurden im Fläming boden-hydrologische Monitoringstandorte aufgebaut, die kleinräumige Heterogenitäten in der Bodenwasserdynamik kontinuierlich und zeitlich hoch aufgelöst erfassen. Ergebnisse der Saugspannungsmessungen mit Watermark-Sensoren auf sechs Acker- und Waldstandorten werden präsentiert. Gemeinsamkeiten und Unterschiede im Bodenwasserhaushalt der Monitoringstandorte werden aufgezeigt und analysiert