Extracellular vesicles (EVs) function as important conveyers of information between cells and thus can be exploited as drug delivery systems or disease biomarkers. Transmission electron microscopy (TEM) remains the gold standard method for visualisation of EVs, however the analysis of individual EVs in TEM images is time-consuming if performed manually. Therefore, we present here a software tool for computer-assisted evaluation of EVs in TEM images. TEM ExosomeAnalyzer detects EVs based on their shape and edge contrast criteria and subsequently analyses their size and roundness. The software tool is compatible with common negative staining protocols and isolation methods used in the field of EV research; even with challenging TEM images (EVs both lighter and darker than the background, images containing artefacts or precipitated stain, etc.). If the fully-automatic analysis fails to produce correct results, users can promptly adjust the detected seeds of EVs as well as their boundaries manually. The performance of our tool was evaluated for three different modes with variable levels of human interaction, using two datasets with various heterogeneity. The semi-automatic mode analyses EVs with high success rate in the homogenous dataset (F1 score 0.9094, Jaccard coefficient 0.8218) as well as in the highly heterogeneous dataset containing EVs isolated from cell culture medium and patient samples (F1 score 0.7619, Jaccard coefficient 0.7553). Moreover, the extracted size distribution profiles of EVs isolated from malignant ascites of ovarian cancer patients overlap with those derived by cryo-EM and are comparable to NTA- and TRPS-derived data. In summary, TEM ExosomeAnalyzer is an easy-to-use software tool for evaluation of many types of vesicular microparticles and is available at http://cbia.fi.muni.cz/exosome-analyzer free of charge for non-commercial and research purposes. The web page contains also detailed description how to use the software tool including a video tutorial.

Fig. 1: Novel representation of electrostatic interaction energy (in the middle) helps navigating the simulation by spatially resolving contributions to the integral measure traditionally represented by a timeseries (blue line in the bottom). It captures different modes of the simulation better than the timeseries and helps localizing changes in the configuration of the simulation by providing spatial context. The multiscale behaviour of the data is explored by seamlessly navigating the spatiotemporal scale-space. The selected timestep shows the ligand escaping from the tunnel, before it is sucked back in by the protein.Abstract-Understanding large amounts of spatiotemporal data from particle-based simulations, such as molecular dynamics, often relies on the computation and analysis of aggregate measures. These, however, by virtue of aggregation, hide structural information about the space/time localization of the studied phenomena. This leads to degenerate cases where the measures fail to capture distinct behaviour. In order to drill into these aggregate values, we propose a multi-scale visual exploration technique. Our novel representation, based on partial domain aggregation, enables the construction of a continuous scale-space for discrete datasets and the simultaneous exploration of scales in both space and time. We link these two scale-spaces in a scale-space space-time cube and model linked views as orthogonal slices through this cube, thus enabling the rapid identification of spatio-temporal patterns at multiple scales. To demonstrate the effectiveness of our approach, we showcase an advanced exploration of a protein-ligand simulation.

Abstract. While convection is a key process in the development of the atmospheric boundary layer, conventional meteorological measurement approaches fall short in capturing the evolution of the complex dynamics of convection. To obtain deeper observational insight into convection, we assess the potential of a novel dual-lidar approach. We present the capability of two pre-processing procedures, an advanced clustering filter instead of a simple threshold filter, as well as a temporal interpolation, to increase data availability and reduce errors in the individual lidar observations that would amplify in the dual-lidar retrieval. To evaluate the optimal balance between spatial and temporal resolution to sufficiently resolve convective properties, we test a set of scan configurations. We tested the dual-lidar setup at two Norwegian airfields in a different geographic setting. We present a retrieval of the convective flow field in a vertical plane above the airfield for each of these setups. Both pre-processing procedures show an improving effect on the data availability and quality and are applied to the observations used in the dual-lidar retrieval. All tested angular resolutions captured the relevant spatial features of the convective flow field and balance between resolutions can be shifted towards a higher temporal resolution. Based on the evaluated cases, we show that the dual-lidar approach sufficiently resolves and provides valuable insight into the dynamic properties of atmospheric convection.

Langmuir probes with RF compensation are used for measurements of electron concentration, electron temperature and the DC value of plasma potential in RF discharges. In order to obtain all the RF components of plasma potential, simple probes without RF compensation are used. However, it has been believed that these uncompensated probes can not be used for determination of the DC value of plasma potential and of electron concentration and temperature, since their VA characteristics is distorted by the RF current. Consequently, the evaluation of data measured with uncompensated probes was not possible without additional measurement with a RF compensated Langmuir probe. This contribution analyzes the possibility to use uncompensated probes not only for measurement of RF components of plasma potential, but also for measurement of the DC component of plasma potential, electron concentration and electron temperature.

Fig. 1: The convection analysis is enabled by two main views. In the left view we provide a tool for analysing the parameter-space of the model, as well as for comparing the model results to data from observations. We allow adjustment of the model parameters on the far left; the greyed-out parameter is under automatic control by the anchor point. A gallery of segmented thermals is at the bottom. On the right, a 3D view showing tracks of paragliding flights presents an instance of a thermal in its environment.