Solvation Layer of Antifreeze Proteins Analyzed with a Markov State Model

Three structurally very different antifreeze proteins (AFPs) are studied, addressing the question as to what extent the hypothesized preordering-binding mechanism is still relevant in the second solvation layer of the protein and beyond. Assuming a two-state model of water, the solvation layers are analyzed with the help of molecular dynamics simulations together with a Markov state model, which investigates the local tedrahedrality of the water hydrogen-bond network around a given water molecule. It has been shown previously that this analysis can discriminate the high-entropy, high-density state of the liquid (HDL) from its more structured low-density state (LDL). All investigated proteins, regardless of whether they are an AFP or not, have a tendency to increase the amount of HDL in their second solvation layer. The ice binding site (IBS) of the antifreeze proteins counteracts that trend, with either a hole in the HDL layer or a true excess of LDL. The results correlate to a certain extent with recent experiments, which have observed ice like vibrational (VSFG) spectra for the water atop the IBS of only a subset of antifreeze proteins. It is concluded that the preordering-binding mechanism indeed seems to play a role but is only part of the overall picture

Comparison of DVB-T Passive Radar Simulated and Measured Bistatic RCS Values for a Pilatus PC-12 Aircraft

Passive radar is a technology that has huge potential for airspace monitoring, taking advantage of existing transmissions. However, to predict whether particular targets can be measured in a particular scenario, it is necessary to be able to model the received signal. In this paper, we present the results of a campaign in which a Pilatus PC-12 single-engine aircraft was measured with a passive radar system relying on DVB-T transmission from a single transmitter. We then present our work to simulate the bistatic RCS of the aircraft along its flight track, using both the method of moments and the shooting and bouncing ray solvers, assess the uncertainty in the simulations, and compare against the measurements. We find that our simulated RCS values are useful in predicting whether or not detection occurs. However, we see poor agreement between simulated and measured RCS values where measurements are available, which we attribute primarily to the difficulties in extracting RCS measurements from the data and to unmodeled transmission and received path effects

Dependency of human target detection performance on clutter and quality of supporting image analysis algorithms in a video surveillance task

Background: In target detection, the success rates depend strongly on human observer performances. Two prior studies tested the contributions of target detection algorithms and prior training sessions. The aim of this Swiss-German cooperation study was to evaluate the dependency of human observer performance on the quality of supporting image analysis algorithms. Methods: The participants were presented 15 different video sequences. Their task was to detect all targets in the shortest possible time. Each video sequence showed a heavily cluttered simulated public area from a different viewing angle. In each video sequence, the number of avatars in the area was altered to 100, 150 and 200 subjects. The number of targets appearing was kept at 10%. The number of marked targets varied from 0, 5, 10, 20 up to 40 marked subjects while keeping the positive predictive value of the detection algorithm at 20%. During the task, workload level was assessed by applying an acoustic secondary task. Detection rates and detection times for the targets were analyzed using inferential statistics. Results: The study found Target Detection Time to increase and Target Detection Rates to decrease with increasing numbers of avatars. The same is true for the Secondary Task Reaction Time while there was no effect on Secondary Task Hit Rate. Furthermore, we found a trend for a u-shaped correlation between the numbers of markings and RTST indicating increased workload. Conclusion: The trial results may indicate useful criteria for the design of training and support of observers in observational tasks

Cloud detection and visibility estimation using thermal camera images during night time

Reduced visibility and adverse cloud cover is a major issue for aviation, road traffic, and military activities. Synoptic meteorological stations and LIDAR measurements are common tools to detect meteorological conditions. However, a low density of meteorological stations and LIDAR measurements may limit a detailed spatial analysis. While geostationary satellite data is a valuable source of information for analyzing the spatio-temporal variability of fog and clouds on a global scale, considerable effort is still required to improve the detection of atmospheric variables on a local scale, especially during the night. In this study we propose to use thermal camera images to (1) improve cloud detection and (2) to study visibility conditions during nighttime. For this purpose, we leverage FLIR A320 and FLIR A655sc Stationary Thermal Imagers installed in the city of Bern, Switzerland. We find that the proposed data provides detailed information about low clouds and the cloud base height that is usually not seen by satellites. However, clouds with a small optical depth such as thin cirrus clouds are difficult to detect as the noise level of the captured thermal images is high. The second part of this study focuses on the detection of structural features. Predefined targets such as roof windows, an antenna, or a small church tower are selected at distances of 140m to 1210m from the camera. We distinguish between active targets (heated targets or targets with insufficient thermal insulation) and passive structural features to analyze the sensor’s visibility range. We have found that a successful detection of some passive structural features highly depends on incident solar radiation. Therefore, the detection of such features is often hindered during the night. On the other hand, active targets can be detected without difficulty during the night due to major differences in temperature between the heated target and its surrounding non-heated objects. We retrieve response values by the cross-correlation of master edge signatures of the targets and the actual edge-detected thermal camera image. These response values are a precise indicator of the atmospheric conditions and allows us to detect restricted visibility conditions

Processing of MIRANDA35 FMCW-SAR data using a time-domain algorithm

Results from an airborne SAR campaign in July 2013 using the FMCW SAR system MIRANDA35 developed by FHR are presented. This system offers a high flexibility regarding the possible swath-widths, flight altitudes and operating band-widths. The platform is an optionally piloted aircraft operated by the Swiss Procurement and technology Center armasuisse. The navigational data is a combined product from INS / GPS and dGPS data. The data were focused and geocoded with a Time-Domain Algorithm dedicated to the processing of FMCW SAR systems. Examples of resulting high-resolution SAR images are shown. The focusing quality is assessed using corner reflectors

Near-Infrared High-Resolution Real-Time Omnidirectional Imaging Platform for Drone Detection

Recent technological advancements in hardware systems have made higher quality cameras. State of the art panoramic systems use them to produce videos with a resolution of 9000 x 2400 pixels at a rate of 30 frames per second (fps).(1) Many modern applications use object tracking to determine the speed and the path taken by each object moving through a scene. The detection requires detailed pixel analysis between two frames. In fields like surveillance systems or crowd analysis, this must be achieved in real time.(2) In this paper, we focus on the system-level design of multi-camera sensor acquiring near-infrared (NIR) spectrum and its ability to detect mini-UAVs in a representative rural Swiss environment. The presented results show the UAV detection from the trial that we conducted during a field trial in August 2015

Synthesis of real world drone signals based on lab recordings

There is a great interest in the generation of plausible drone signals in various applications, e.g. for auralization purposes or the compilation of training data for detection algorithms. Here, a methodology is presented which synthesises realistic immission signals based on laboratory recordings and subsequent signal processing. The transformation of a lab drone signal into a virtual field microphone signal has to consider a constant pitch shift to adjust for the manoeuvre specific rotational speed and the corresponding frequency dependent emission strength correction, a random pitch shift variation to account for turbulence induced rotational speed variations in the field, Doppler frequency shift and time and frequency dependent amplitude adjustments according to the different propagation effects. By evaluation of lab and field measurements, the relevant synthesizer parameters were determined. It was found that for the investigated set of drone types, the vertical radiation characteristics can be successfully described by a generic frequency dependent directivity pattern. The proposed method is applied to different drone models with a total weight between 800 g and 3.4 kg and is discussed with respect to its abilities and limitations comparing both, recordings taken in the lab and the field

Implementation of a fast time-domain processor for FMCW Synthetic Aperture Radar data

For the purpose of getting sensitive information relevant to civil or military security, high-resolution airborne Synthetic Aperture Radar (SAR) provides the possibility to organize missions at short notice regardless of the daylight and of the weather conditions. The use of compact millimeter-wave FMCW SAR systems allows reaching these goals more safely and at lower cost using unmanned lightweight platforms. As a counterpart these platforms are relatively unstable, making the data-processing more difficult. In order to reach optimum focusing quality also in unfavorable flight conditions or for highly non-linear tracks we developed a fast Time-Domain Processor that relies on parallelization using the GPU resources. A production areal processing rate as high as 6 km(2)/h using 20 cm ground pixel spacing on a single PC station was achieved. The processing quality and efficiency is demonstrated using real data from the MIRANDA35 Ka-band SAR system

Projektmanagement im "Unmarked Space" : Forschungsprojekte im Spannungsfeld von Industrie und Wissenschaft

Wer kennt das nicht aus Projekten, die zwischen Wissenschaft und Wirtschaft stattfinden: Es erscheint der Eindruck, als ob zwei verschiedene Welten/Kulturen zusammentreffen. Dies spiegelt sich nicht nur in der Zielformulierung und in der Herangehensweise wider, sondern auch wie Projektmanagement gelebt wird. In der spm Fachgruppe "Projektmanagement in der Forschung" hat man sich etwas eingehender mit dieser Thematik befasst, eigene Erfahrungen diskutiert sowie die Ergebnisse aus einer kleinen, nicht repräsentativen Umfrage analysiert. Sind die Unterschiede wirklich so gross, wie sie wahrgenommen werden? Im vorliegenden Artikel finden Sie Antworten und Handlungsempfehlungen dazu

Synthesis of real world drone signals based on lab recordings

There is a great interest in the generation of plausible drone signals in various applications, e.g. for auralization purposes or the compilation of training data for detection algorithms. Here, a methodology is presented which synthesises realistic immission signals based on laboratory recordings and subsequent signal processing. The transformation of a lab drone signal into a virtual field microphone signal has to consider a constant pitch shift to adjust for the manoeuvre specific rotational speed and the corresponding frequency dependent emission strength correction, a random pitch shift variation to account for turbulence induced rotational speed variations in the field, Doppler frequency shift and time and frequency dependent amplitude adjustments according to the different propagation effects. By evaluation of lab and field measurements, the relevant synthesizer parameters were determined. It was found that for the investigated set of drone types, the vertical radiation characteristics can be successfully described by a generic frequency dependent directivity pattern. The proposed method is applied to different drone models with a total weight between 800 g and 3.4 kg and is discussed with respect to its abilities and limitations comparing both, recordings taken in the lab and the field