Rainfall estimation using moving cars as rain gauges - Laboratory experiments

The spatial assessment of short time-step precipitation is a challenging task. Low density of observation networks, as well as the bias in radar rainfall estimation motivated the new idea of exploiting cars as moving rain gauges with windshield wipers or optical sensors as measurement devices. In a preliminary study, this idea has been tested with computer experiments (Haberlandt and Sester, 2010). The results have shown that a high number of possibly inaccurate measurement devices (moving cars) provide more reliable areal rainfall estimations than a lower number of precise measurement devices (stationary gauges). Instead of assuming a relationship between wiper frequency (W) and rainfall intensity (R) with an arbitrary error, the main objective of this study is to derive valid W-R relationships between sensor readings and rainfall intensity by laboratory experiments. Sensor readings involve the wiper speed, as well as optical sensors which can be placed on cars and are usually made for automating wiper activities. A rain simulator with the capability of producing a wide range of rainfall intensities is designed and constructed. The wiper speed and two optical sensors are used in the laboratory to measure rainfall intensities, and compare it with tipping bucket readings as reference. Furthermore, the effect of the car speed on the estimation of rainfall using a car speed simulator device is investigated. The results show that the sensor readings, which are observed from manual wiper speed adjustment according to the front visibility, can be considered as a strong indicator for rainfall intensity, while the automatic wiper adjustment show weaker performance. Also the sensor readings from optical sensors showed promising results toward measuring rainfall rate. It is observed that the car speed has a significant effect on the rainfall measurement. This effect is highly dependent on the rain type as well as the windshield angle. © 2013 Authjor(s).DFG/3504/5-

Areal rainfall estimation using moving cars - computer experiments including hydrological modeling

The need for high temporal and spatial resolution precipitation data for hydrological analyses has been discussed in several studies. Although rain gauges provide valuable information, a very dense rain gauge network is costly. As a result, several new ideas have been emerged to help estimating areal rainfall with higher temporal and spatial resolution. Rabiei et al. (2013) observed that moving cars, called RainCars (RCs), can potentially be a new source of data for measuring rainfall amounts. The optical sensors used in that study are designed for operating the windscreen wipers and showed promising results for rainfall measurement purposes. Their measurement accuracy has been quantified in laboratory experiments. Considering explicitly those errors, the main objective of this study is to investigate the benefit of using RCs for estimating areal rainfall. For that, computer experiments are carried out, where radar rainfall is considered as the reference and the other sources of data, i.e. RCs and rain gauges, are extracted from radar data. Comparing the quality of areal rainfall estimation by RCs with rain gauges and reference data helps to investigate the benefit of the RCs. The value of this additional source of data is not only assessed for areal rainfall estimation performance, but also for use in hydrological modeling. The results show that the RCs considering measurement errors derived from laboratory experiments provide useful additional information for areal rainfall estimation as well as for hydrological modeling. Even assuming higher uncertainties for RCs as obtained from the laboratory up to a certain level is observed practical.DFG/3504/5-

Feasibility of Prehospital Teleconsultation in Acute Stroke – A Pilot Study in Clinical Routine

BACKGROUND: Inter-hospital teleconsultation improves stroke care. To transfer this concept into the emergency medical service (EMS), the feasibility and effects of prehospital teleconsultation were investigated. METHODOLOGY/PRINCIPAL FINDINGS: Teleconsultation enabling audio communication, real-time video streaming, vital data and still picture transmission was conducted between an ambulance and a teleconsultation center. Pre-notification of the hospital was carried out with a 14-item stroke history checklist via e-mail-to-fax. Beside technical assessments possible influences on prehospital and initial in-hospital time intervals, prehospital diagnostic accuracy and the transfer of stroke specific data were investigated by comparing telemedically assisted prehospital care (telemedicine group) with local regular EMS care (control group). All prehospital stroke patients over a 5-month period were included during weekdays (7.30 a.m.-4.00 p.m.). In 3 of 18 missions partial dropouts of the system occurred; neurological co-evaluation via video transmission was conducted in 12 cases. The stroke checklist was transmitted in 14 cases (78%). Telemedicine group (n = 18) vs. control group (n = 47): Prehospital time intervals were comparable, but in both groups the door to brain imaging times were longer than recommended (median 59.5 vs. 57.5 min, p = 0.6447). The prehospital stroke diagnosis was confirmed in 61% vs. 67%, p = 0.8451. Medians of 14 (IQR 9) vs. 5 (IQR 2) stroke specific items were transferred in written form to the in-hospital setting, p<0.0001. In 3 of 10 vs. 5 of 27 patients with cerebral ischemia thrombolytics were administered, p = 0.655. CONCLUSIONS: Teleconsultation was feasible but technical performance and reliability have to be improved. The approach led to better stroke specific information; however, a superiority over regular EMS care was not found and in-hospital time intervals were unacceptably long in both groups. The feasibility of prehospital tele-stroke consultation has future potential to improve emergency care especially when no highly trained personnel are on-scene. TRIAL REGISTRATION: International Standard Randomised Controlled Trial Number Register (ISRCTN) ISRCTN83270177

Field Motion Estimation with a Geosensor Network

Physical environmental processes, such as the evolution of precipitation or the diffusion of chemical clouds in the atmosphere, can be approximated by numerical models based on the underlying physics, e.g., for the purpose of prediction. As the modeling process is often very complex and resource demanding, such models are sometimes replaced by those that use historic and current data for calibration. For atmospheric (e.g., precipitation) or oceanographic (e.g., sea surface temperature) fields, the data-driven methods often concern the horizontal displacement driven by transport processes (called advection). These methods rely on flow fields estimated from images of the phenomenon by computer vision techniques, such as optical flow (OF). In this work, an algorithm is proposed for estimating the motion of spatio-temporal fields with the nodes of a geosensor network (GSN) deployed in situ when images are not available. The approach adapts a well-known raster-based OF algorithm to the specifics of GSNs, especially to the spatial irregularity of data. In this paper, the previously introduced approach has been further developed by introducing an error model that derives probabilistic error measures based on spatial node configuration. Further, a more generic motion model is provided, as well as comprehensive simulations that illustrate the performance of the algorithm in different conditions (fields, motion behaviors, node densities and deployments) for the two error measures of motion direction and motion speed. Finally, the algorithm is applied to data sampled from weather radar images, and the algorithm performance is compared to that of a state-of-the-art OF algorithm applied to the weather radar images directly, as often done in nowcasting

Areal rainfall estimation using moving cars as rain gauges - laboratory and field experiment

Areal precipitation estimation for fine temporal and spatial resolution is still a challenging task. Beside the fact that newly developed instrumentations, e.g. weather radar, provide valuable information with high spatial and temporal resolutions, they are subject to different sources of errors. On the other hand, recording rain gauges provide accurate point rainfall depth, but are still often poor in density. Equipping a car with a GPS device as well as sensors measuring rainfall makes it possible to implement cars on the streets as the moving rain gauges. Initial results from a modeling study assuming arbitrary measurement errors have shown that implementing a reasonable large number of inaccurate measurement devices (raincars) provide more reliable areal precipitations compared to the available rain gauge network. The purpose of this study is to derive relationships between sensor readings and rain rate in a laboratory and quantify the errors. Sensor readings involve wiper frequency and optical sensors which are on the cars to automate wiper activities. Besides, the influence of car speed on the sensor readings is investigated implementing a car-speed simulator. It has been observed that the manual wiper activity adjustment, according to front visibility, shows a strong relationship between rainfall intensity and wiper speed. Two optical sensors calibrated in laboratory showed a relatively strong relationship with the rain intensity recorded by a tipping bucket. A positive relationship between the velocity and the amount of water has been observed meaning that the higher the speed of a car, the higher the amount of water hitting the car. Additionally, some preliminary results of the field experiments are discussed

A novel screening method for free non-standard amino acids in human plasma samples using AccQ·Tag reagents and LC-MS/MS

There are at least 500 naturally occurring amino acids, of which only 20 standard proteinogenic amino acids are used universally across all organisms in the synthesis of peptides and proteins. Non-standard amino acids can be incorporated into proteins or are intermediates and products of metabolic pathways. While the analysis of standard amino acids is well-defined, the analysis of non-standard amino acids can be challenging due to the wide range of physicochemical properties, and the lack of both reference standards and information in curated databases to aid compound identification. It has been shown that the use of an AccQ·Tag™ derivatization kit along with LC-MS/MS is an attractive option for the analysis of free standard amino acids in complex samples because it is fast, sensitive, reproducible, and selective. It has been demonstrated that the most abundant quantitative transition for MS/MS analysis of 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (AQC) derivatized amino acids corresponds to the fragmentation of the molecule at the 6-aminoquinoline carbonyl group producing a common m/z 171 fragment ion and occurs at similar mass spectrometry collision energy and cone voltages. In this study, the unique properties of AQC derivatized amino acids producing high intensity common fragment ions, along with chromatographic separation of amino acids under generic chromatography conditions, were used to develop a novel screening method for the detection of trace levels of non-standard amino acids in complex matrices. Structural elucidation was carried out by comparing the MS/MS fragment ion mass spectra generated with in silico predicted fragmentation spectra to enable a putative identification, which was confirmed using an appropriate analytical standard. This workflow was applied to screen human plasma samples for bioactive thiol-group modified cysteine amino acids and S-allylmercaptocysteine (SAMC), S-allylcysteine sulfoxide (SACS or alliin) and S-propenylcysteine (S1PC) are reported for the first time to be present in human plasma samples after the administration of garlic supplements