Magnetic Anomaly Detection Based on a Compound Tri-Stable Stochastic Resonance System.

In the case of strong background noise, a tri-stable stochastic resonance model has higher noise utilization than a bi-stable stochastic resonance (BSR) model for weak signal detection. However, the problem of severe system parameter coupling in a conventional tri-stable stochastic resonance model leads to difficulty in potential function regulation. In this paper, a new compound tri-stable stochastic resonance (CTSR) model is proposed to address this problem by combining a Gaussian Potential model and the mixed bi-stable model. The weak magnetic anomaly signal detection system consists of the CTSR system and judgment system based on statistical analysis. The system parameters are adjusted by using a quantum genetic algorithm (QGA) to optimize the output signal-to-noise ratio (SNR). The experimental results show that the CTSR system performs better than the traditional tri-stable stochastic resonance (TTSR) system and BSR system. When the input SNR is -8 dB, the detection probability of the CTSR system approaches 80%. Moreover, this detection system not only detects the magnetic anomaly signal but also retains information on the relative motion (heading) of the ferromagnetic target and the magnetic detection device.

Impacts of Drought and Rehydration Cycles on Isoprene Emissions in Populus nigra Seedlings.

The volatile organic compounds emitted by plants significantly impact the atmospheric environment. The impacts of drought stress on the biogenic volatile organic compound (BVOC) emissions of plants are still under debate. In this study, the effects of two drought-rehydration cycle groups with different durations on isoprene emissions from Populus nigra (black poplar) seedlings were studied. The P. nigra seedlings were placed in a chamber that controlled the soil water content, radiation, and temperature. The daily emissions of isoprene and physiological parameters were measured. The emission rates of isoprene (Fiso) reached the maximum on the third day (D3), increasing by 58.0% and 64.2% compared with the controlled groups, respectively, and then Fiso significantly decreased. Photosynthesis decreased by 34.2% and 21.6% in D3 in the first and second groups, respectively. After rehydration, Fiso and photosynthesis recovered fully in two groups. However, Fiso showed distinct inconsistencies in two groups, and the recovery rates of Fiso in the second drought group were slower than the recovery rates of Fiso in the first groups. The response of BVOC emissions during the drought-rehydration cycle was classified into three phases, including stimulated, inhibited, and restored after rehydration. The emission pattern of isoprene indicated that isoprene played an important role in the response of plants to drought stress. A drought-rehydration model was constructed, which indicated the regularity of BVOC emissions in the drought-rehydration cycle. BVOC emissions were extremely sensitive to drought, especially during droughts of short duration. Parameters in computational models related to BVOC emissions of plants under drought stress should be continuously improved.

Characterization and sources of trace elements in PM1 during autumn and winter in Qingdao, Northern China.

Atmospheric sub-micrometer particles (PM1, particles with an aerodynamic diameter ≤ 1.0 µm) monitoring in Qingdao, a coastal city in Northern China, was conducted for two consecutive years from November 1, 2018 to January 31, 2019 (hereafter referred to as OP2018-2019) and from October 28, 2019 to January 20, 2020 (hereafter referred to as OP2019-2020). The results showed that compared with OP2018-2019, the concentrations of V, Ni, As, Pb, and Cd in PM1 in OP2019-2020 decreased by 61.9%, 31.4%, 49.2%, 25.4%, and 27.1%, respectively. For the indicators of ship emission sources, a significant reduction in V (73.3%) and Ni (22.1%) concentrations were observed after the implementation of the updated Domestic Emission Control Area (DECA 2.0) policy for ships since January 1, 2019 proposed by the Ministry of Transportation. This result demonstrated that the implementation of the DECA 2.0 policy had a significant effect on reducing ship emissions. The Field Emission Scanning Electron Microscope analysis identified the impact of ship emission sources, while the inconsistent distribution of V and Ni revealed other potential sources of Ni. The V/Ni ratios during the pre-policy and post-policy periods decreased by 40.7%. Along with the further implementation of the domestic coastal ship pollution control zone policy, V/Ni ratio should be cautiously used as a parameter for ship emission sources. The positive matrix factorization method identified five source factors: coal combustion/biomass burning (47.8%), crustal sources (21.2%), vehicle exhaust/road dust (15.1%), industrial emissions (11.1%), and ship emissions (4.9%). The contribution rates of ship emission sources before and after the DECA 2.0 policy were analyzed and found to be 5.6% and 3.4%. The potential source contribution factor analysis of As showed that the potential emission source areas were significantly reduced in OP2019-2020, which might be related to the coal fired cleanup operations conducted in Beijing-Tianjin-Hebei and surrounding areas.