Design of Detection-Jamming Shared Waveform Based on Virtual Force Field Algorithm

Due to the technical barriers between radars and jammers and the poor performance of the traditional detection-jamming shared signal in integrated radar-electronic warfare systems, a new detection-jamming shared signal waveform based on the virtual force field algorithm (VFFA) is proposed in this paper. First, a multi-objective and multi-dimensional characteristic parameter optimization model, based on a virtual force field, is established, and then the design principle of the shared signal is presented in detail. The simulation results show that the detection-jamming shared signal based on the VFFA presents the deceptive jamming of multiple false targets in non-collaborative radar. Further, there is better detection performance with the advantages of multiple pulse repetition frequency (PRF) and pulse accumulation number, which are highly sensitive to the multi-jagged PRF signals emitted by the non-collaborative radar. According to the VFFA described in this paper, the optimum detection-jamming shared signal waveform can be output in real time for specific free space targets, to improve the efficiency of integrated radar and electronic warfare systems.

AI-Blue-Carba: A Rapid and Improved Carbapenemase Producer Detection Assay Using Blue-Carba With Deep Learning

A rapid and accurate detection of carbapenemase-producing Gram-negative bacteria (CPGNB) has an immediate demand in the clinic. Here, we developed and validated a method for rapid detection of CPGNB using Blue-Carba combined with deep learning (designated as AI-Blue-Carba). The optimum bacterial suspension concentration and detection wavelength were determined using a Multimode Plate Reader and integrated with deep learning modeling. We examined 160 carbapenemase-producing and non-carbapenemase-producing bacteria using the Blue-Carba test and a series of time and optical density values were obtained to build and validate the machine models. Subsequently, a simplified model was re-evaluated by descending the dataset from 13 time points to 2 time points. The best suitable bacterial concentration was determined to be 1.5 optical density (OD) and the optimum detection wavelength for AI-Blue-Carba was set as 615 nm. Among the 2 models (LRM and LSTM), the LSTM model generated the higher ROC-AUC value. Moreover, the simplified LSTM model trained by short time points (0–15 min) did not impair the accuracy of LSTM model. Compared with the traditional Blue-Carba, the AI-Blue-Carba method has a sensitivity of 95.3% and a specificity of 95.7% at 15 min, which is a rapid and accurate method to detect CPGNB.

Alcohol Determination by HPLC with Postcolumn Derivatization Based on the Thiosulfate-catalyzed Reaction of Alcohols and Cerium(IV) and Fluorescence Detection of Cerium(III)

Background: Determination of a reducing substance based on the reaction between Ce(IV) and a reducing substance and fluorescence detection of Ce(III) generated has been reported as a selective and sensitive method. However, this method could not be applied to the determination of alcohol due to the low reaction rate of alcohol and Ce(IV). Objective: We found that thiosulfate catalytically enhanced reaction of alcohols (such as, methanol, ethanol, and propanol) and Ce(IV). Utilizing this effect, we developed a new method for the determination of alcohols. Results: In the presence of thiosulfate, an increase in fluorescence intensity was detected by injecting alcohol at concentrations of several millimolar, whereas it was not observed even at the concentration of 10% v/v (2 M for ethanol) in the absence of thiosulfate. The optimum detection conditions were determined to be 4.0 mM Ce(IV) sulfate and 0.50 mM thiosulfate, and the detection limit (S/N = 3) of ethanol under these conditions was 1 mM. In the calibration curves, changes in the slope were observed when the alcohol concentrations were approximately 10–25 mM. Using a thiosulfate solution containing ethanol as the reaction solution, a calibration curve without any change in slope was obtained, although the concentration of ethanol at the detection limit increased. The alcohols in the liquor and fuel were successfully analyzed using the proposed detection method as a postcolumn reaction. Conclusion: This new alcohol detection method using a versatile fluorescence detector can be applied to the postcolumn reaction of HPLC omitting need of time-consuming pretreatment processes.

Short-duration infrasound signals observed at the array PVCI

<p>We present the most interesting cases from observations of short-duration infrasound signals at the array PVCI (50.53°N 14.57°E).  The array is equipped with three sensors and it has an aperture of 200 m. The optimum detection range of the array is 0.02-4 Hz.</p><p>On 24 August 2016 at 01:36:32 UTC, a strong earthquake occurred in Central Italy; the epicentre was located at 42.75°N and 13.22°E. The azimuth from PVCI to the epicentre was 187° and the distance was 871 km. At 02:23-02:40 UTC, signals from the azimuths around 195° were recorded at the array. The time interval corresponds to the expected stratospheric signal arrival.</p><p>On 3 March 2016 at 21:51-21:53 UTC, PVCI registered signal from the azimuth of 199°. The signal elevation was 30-35°. We assume that the signal source was the bolide EN060316 that entered the atmosphere above Upper Austria and Bavaria. </p><p>Two large accidental explosions occurred in the region recently; both of them were recorded by PVCI and other member stations of the CEEIN network. On 26-27 September 2017, an ammunition depot exploded in Kalynivka, Central Ukraine. Signals from the azimuths of 85-90° were recorded on 26 September 2017 at 21:02-21:05 UTC and at 23:16-23:21 UTC. On 1 September 2018 around 03:15 UTC, an explosion occurred in the refinery near Ingolstadt, Germany. A high amplitude signal arrived at PVCI at 03:30:48 UTC from the azimuth of 243°.</p>