Single-photon avalanche diodes dynamic range and linear response enhancement by conditional probability correction.

Detectors based on single-photon avalanche diodes (SPADs) operating in free-running mode surfer from distorted detection signals due to the impact of afterpulse, dead time, and the non-linear detection efficiency response. This study presents a correction method based on conditional probability. In the experiments with high temporal resolution and huge dynamic range conditions, this method's residual sum of squares is near 68 times smaller than the uncorrected received data of SPAD and near 50 times smaller than deconvolution method. This method is applied to polarization lidar and CO2 lidar, and the performance shows significant improvement. This method effectively mitigates the impact of SPAD afterpulse, dead time, and detection efficiency non-linear response, making it suitable for all SPADs. Especially, our method is primarily employed for atmospheric detection.

Denoising coherent Doppler lidar data based on a U-Net convolutional neural network.

The coherent Doppler wind lidar (CDWL) has long been thought to be the most suitable technique for wind remote sensing in the atmospheric boundary layer (ABL) due to its compact size, robust performance, and low-cost properties. However, as the coherent lidar exploits the Mie scattering from aerosol particles, the signal intensity received by the lidar is highly affected by the concentration of aerosols. Unlike air molecules, the concentration of aerosol varies greatly with time and weather, and decreases dramatically with altitude. As a result, the performance of the coherent lidar fluctuates greatly with time, and the detection range is mostly confined within the planetary boundary layer. The original data collected by the lidar are first transformed into a spectrogram and then processed into radial wind velocities utilizing algorithms such as a spectral centroid. When the signal-to-noise ratio (SNR) is low, these classic algorithms fail to retrieve the wind speed stably. In this work, a radial wind velocity retrieving algorithm based on a trained convolutional neural network (CNN) U-Net is proposed for denoising and an accurate estimate of the Doppler shift in a low-SNR regime. The advantage of the CNN is first discussed qualitatively and then proved by means of a numerical simulation. Simulated spectrum data are used for U-Net training and testing, which show that the U-Net is not only more accurate than the spectral centroid but also achieves a further detection range. Finally, joint observation data from the lidar and radiosonde show excellent agreement, demonstrating that the U-Net-based retrieving algorithm has superior performance over the traditional spectral centroid method both in accuracy and detection range.

Mitigation of amplified spontaneous emission noise for an all-fiber coaxial aerosol lidar with different single-photon detectors.

For a coaxial single-photon lidar system, amplified spontaneous emission (ASE) noise from the fiber amplifier is inevitable. The ASE backscattering from specular reflection annihilates the far-field weak signal, resulting in low signal-to-noise ratio, short measurement distance, and even misidentification. We propose a method for calibrating and mitigating ASE noise in all-fiber coaxial aerosol lidar and demonstrate the method for a lidar system with different single-photon detectors (SPDs). The accuracy of the coaxial aerosol lidar is comparable to that of the biaxial one. We conducted an experiment using three different detectors, namely, InGaAs/InP SPD, up-conversion SPD, and superconducting nanowire SPD in the same coaxial lidar system. Compared with the biaxial system, the three different detectors we used have achieved more than 90% ASE noise suppression, the measured visibility percent errors of InGaAs/InP SPD data, up-conversion SPD data, and superconducting nanowire SPD data all within 20%, and the percent error within 10% are 99.47%, 100%, and 95.12%, respectively. Moreover, time-sharing optical switching allowed to obtain background noise with high accuracy.

Meter-scale and sub-second-resolution coherent Doppler wind LIDAR and hyperfine wind observation.

Hyperfine wind structure detection is important for aerodynamic and aviation safety. Pulse coherent Doppler wind LIDAR (PCDWL) is a widespread wind remote sensing method with tunable spatial and temporal resolutions. However, meter scale and sub-second resolution are still challenging for PCDWL. This is because of the constraints among short laser pulse duration, spectral broadening, detection accuracy, and real-time processing. In this Letter, to further improve the spatial and temporal resolution of PCDWL, we optimize the optical design of a nanosecond fiber laser and telescope and adopt a new, to the best of our knowledge, algorithm called the even-order derivative peak sharpening technique. During the experiment, all-fiber PCDWL with spatial and temporal resolutions of 3 m and 0.1 s, respectively, is demonstrated. Two-day continuous observation of the wakes of the Chinese high-speed train shows detailed hyperfine wind structures. This is similar to a computational fluid dynamics simulation.

Metastable helium Faraday filter for helium lidar to measure the density of the thermosphere.

We demonstrate a metastable helium Faraday optical filter operating on the 23S1 - 23P1 and 23S1 - 23P2 transition at 1083 nm by using a 3 cm long helium cell. The influence of the magnetic field and gas pressure of the helium cell on the filter characteristics is experimental studied. When the magnetic field is 230 Gs and the gas pressure of helium cell is about 110 Pa, the peak transmission corresponding to the two energy level transitions is about 32% and 57%, respectively. The equivalent noise bandwidth (ENBW) under this working condition is about 1.9 GHz. The metastable helium Faraday filter can be used to improve the optical inefficiency of a helium resonance fluorescence lidar to achieve the metastable helium density detection at 200-1000 km thermosphere.

Fine gust front structure observed by coherent Doppler lidar at Lanzhou Airport (103°49$

Coherent Doppler lidar (CDL) has long been used to automatically identify gust front-induced wind shear signatures from the velocity data, but rare attention has been given to the fine structure of wind gust fronts. In this work, a compact and robust CDL with high efficiency and accuracy is equipped at Lanzhou Airport (103°49$^{\prime}$'E, 36°03$^{\prime}$'N) to conduct interpretation of wind gust front structures by using high-resolution CDL data. Outflows of gust fronts could be detected reliably from radial velocities, spectral widths, as well as radial shears. For the case study presented here, photographs of the velocity and spectrum width capacitates gust front characteristics such as height, advance speed, and radial shear, as well as vertical structure to be displayed in minute detail. Besides, the quasi-continuous vertical wind reveals the potential turbulent mixing and vertical transport process during the gust front event, which makes CDL a very attractive and essential technique for future development of gust front automatic detection systems.

Genetic polymorphisms of exon 1 of MBL2 contribute to tuberculosis risk especially in Asian populations: an updated meta-analysis of 26 studies.

BACKGROUND: Evidence suggests that genetic variations of exon 1 of mannose-binding lectin 2 (MBL2) may contribute to tuberculosis (TB) risk. Many studies have investigated the association between MBL2 exon 1 polymorphisms (rs1800450, rs1800451, and rs5030737) and TB risk, but yielded inconclusive results. METHOD: We conducted this meta-analysis of 26 eligible case-control studies that included 7952 cases and 9328 controls to identify the strength of association. Odds ratio (OR) and 95% CI were used to evaluate the strength of association. Statistical analyses were performed by using STATA 12.1. RESULTS: We found a statistically significant correlation between MBL2 exon 1 polymorphisms and increased TB risk among three models: allele model (O vs A: OR =1.18, 95% CI: 1.01-1.38, Pheterogeneity<0.0001, I2=85.8%), homozygote comparison (OO vs AA: OR =1.49, 95%CI: 1.02-2.18, Pheterogeneity<0.0001, I2=79.1%), dominant model (AO/OO vs AA: OR =1.20, 95% CI: 1.01-1.43, Pheterogeneity<0.0001, I2=83.5%), especially in studies based on Asian populations among five models: allele model (O vs A: OR =1.29, 95% CI: 1.11-1.51, Pheterogeneity<0.0001, I2=66.0%), homozygote comparison (OO vs AA: OR =1.67, 95% CI: 1.09-2.55, Pheterogeneity=0.008, I2=54.2%), heterozygote comparison (AO vs AA: OR =1.26, 95% CI: 1.05-1.50, Pheterogeneity=0.001, I2=62.9%), dominant model (AO/OO vs. AA: OR =1.31, 95% CI: 1.10-1.56, Pheterogeneity=0.001, I2=64.2%), and recessive model (OO vs AO/AA: OR =1.50, 95% CI: 1.01-2.22, Pheterogeneity=0.023, I2=48.0%). Meta-regression results revealed that source of controls (p=0.009), but not ethnicity (p=0.687), genotyping method (p=0.231), and sample size (p=0.451) contributed to the source of heterogeneity. CONCLUSION: This meta-analysis suggests that MBL2 exon 1 polymorphisms may contribute to TB risk, especially in Asian populations.

Gravity waves observation of wind field in stratosphere based on a Rayleigh Doppler lidar.

Simultaneous wind and temperature measurements in stratosphere with high time-spatial resolution for gravity waves study are scarce. In this paper we perform wind field gravity waves cases in the stratosphere observed by a mobile Rayleigh Doppler lidar. This lidar system with both wind and temperature measurements were implemented for atmosphere gravity waves research in the altitude region 15-60 km. Observations were carried out for two periods of time: 3 months started from November 4, 2014 in Xinzhou, China (38.425°N,112.729°E) and 2 months started from October 7, 2015 in Jiuquan, China (39.741°N, 98.495°E) . The mesoscale fluctuations of the horizontal wind velocity and the two dimensional spectra analysis of these fluctuations show the presence of dominant oscillatory modes with wavelength of 4-14 km and period of around 10 hours in several cases. The simultaneous temperature observations make it possible to identify gravity wave cases from the relationships between different variables: temperature and horizontal wind. The observed cases demonstrate the Rayleigh Doppler Lidar's capacity to study gravity waves.