Tunable single frequency Hz-magnitude narrow linewidth Brillouin fiber laser based on parity-time symmetry.

An Hz-magnitude ultra-narrow linewidth single-frequency Brillouin fiber laser (BFL) is proposed and experimentally demonstrated. The single frequency of the laser is selected by parity-time (PT) symmetry, which consists of a stimulated Brillouin scatter (SBS) gain path excited by a 24 km single-mode fiber (SMF) and an approximately equal length loss path tuned with a variable optical attenuator (VOA). These paths are coupled through a fiber Bragg grating (FBG) into a wavelength space. Accomplishing single-frequency oscillation involves the precise adjustment of polarization control (PC) and VOA to attain the PT broken phase. In the experiment, the linewidth of the proposed BFL is 9.58 Hz. The optical signal-to-noise ratio (OSNR) reached 78.89 dB, with wavelength and power fluctuations of less than 1pm and 0.02 dB within one hour. Furthermore, the wavelength can be tuned from 1549.9321 nm to 1550.2575 nm, with a linewidth fluctuation of 1.81 Hz. The relative intensity noise (RIN) is below -74 dB/Hz. The proposed ultra-narrow single-frequency BFL offers advantages such as cost-effectiveness, ease of control, high stability and excellent output characteristics, making it highly promising for the applications in the coherent detection.

Dual wavelength laser Doppler anemometer for simultaneous velocity and particulate size distribution measurements in submarine environments.

An in-situ laser Doppler current probe (LDCP) for the simultaneous measurements of the micro-scale subsurface current speed and the characterizations of micron particles is dedicated in this paper. The LDCP performs as an extension sensor for the state-of-the-art laser Doppler anemometry (LDA). The all-fiber LDCP utilized a compact dual wavelength (491 nm and 532 nm) diode pumped solid state laser as the light source to achieve the simultaneous measurements of the two components of the current speed. Besides its ability for the measurements of the current speed, the LDCP is also capable of obtaining the equivalent spherical size distribution of the suspended particles within small size range. The micro-scale measurement volume formed by two intersecting coherent laser beams makes it possible to accurately estimate the size distribution of the micron suspended particles with high temporal and spatial resolution. With its deployment during the field campaign at Yellow Sea, the LDCP has been experimentally demonstrated as an effective instrument to capture the micro-scale subsurface ocean current speed. The algorithm for retrieving the size distribution of the small suspended particles (2∼7.5µm) has been developed and validated. The combined LDCP system could be applied to the continuous long-term observations of plankton community structure, ocean water optical parameter over a wide range, and useful to elucidate the processes and interactions of the carbon cycles in the upper ocean.

Validation of the polarized Monte Carlo model of shipborne oceanic lidar returns.

The polarized Monte Carlo (PMC) model has been applied to study the backscattering measurement of oceanic lidar. This study proposes a PMC model for shipborne oceanic lidar simulation. This model is validated by the Rayleigh scattering experiment, lidar equation, and in-situ lidar LOOP (Lidar for Ocean Optics Profiler) returns [Opt. Express30, 8927 (2022)10.1364/OE.449554]. The relative errors of the simulated Rayleigh scattering results are less than 0.07%. The maximum mean relative error (MRE) of the simulated single scattering scalar signals and lidar equation results is 30.94%. The maximum MRE of simulated total scattering signals and LOOP returns in parallel and cross channels are 33.29% and 22.37%, respectively, and the maximal MRE of the depolarization ratio is 24.13%. The underwater light field of the laser beam is also simulated to illustrate the process of beam energy spreading. These results prove the validity of the model. Further analyses show that the measured signals of shipborne lidar LOOP are primarily from the particle single scatterings. This model is significant for analyzing the signal contributions from multiple scattering and single scattering.

Scattering direction sampling methods for polarized Monte Carlo simulation of oceanic lidar.

Monte Carlo techniques have been widely applied in polarized light simulation. Based on different preconditions, there are two main types of sampling strategies for scattering direction: one is the scalar sampling method; the others are polarized sampling approaches, including the one- and two-point rejection methods. The polarized simulation of oceanic lidar involves a variety of mediums, and an efficient scattering sampling method is the basis for the coupling simulation of the atmosphere and ocean. To determine the optimal scattering sampling method for oceanic lidar simulation, we developed a polarized Monte Carlo model and simulated Mie scattering, Rayleigh scattering, and Petzold average-particle scattering experiments. This simulation model has been validated by comparison with Ramella-Roman's program [Opt. Express13, 4420 (2005)OPEXFF1094-408710.1364/OPEX.13.004420], with differences in reflectance and transmittance Stokes less than 1% in Mie scattering. The simulation results show these scattering sampling methods differ in runtime, scattering angle distributions, and reflectance and transmittance Stokes. Considering the current simulation accuracy of oceanic lidar, the differences in reflectance and transmittance Stokes are acceptable; thus, the runtime becomes the main evaluation factor. The one-point rejection method and scalar sampling method are preferable for the oceanic lidar polarized simulation. Under complex atmosphere-ocean coupling systems, scalar sampling methods may be a better choice since the calculation process of the sampling is independent of the incident Stokes vector.

Research on Simultaneous Measurement of Magnetic Field and Temperature Based on Petaloid Photonic Crystal Fiber Sensor.

In this paper, we propose and design a magnetic field and temperature sensor using a novel petaloid photonic crystal fiber filled with magnetic fluid. The PCF achieves a high birefringence of more than 1.43 × 10-2 at the wavelength of 1550 nm via the design of material parameters, air hole shape and the distribution of the photonic crystal fiber. Further, in order to significantly improve the sensitivity of the sensor, the magnetic-fluid-sensitive material is injected into the pores of the designed photonic crystal fiber. Finally, the sensor adopts a Mach-Zehnder interferometer structure combined with the ultra-high birefringence of the proposed petaloid photonic crystal fiber. Magnetic field and temperature can be simultaneously measured via observing the spectral response of the x-polarization state and y-polarization state. As indicated via simulation analysis, the sensor can realize sensitivities to magnetic fields and temperatures at -1.943 nm/mT and 0.0686 nm/°C in the x-polarization state and -1.421 nm/mT and 0.0914 nm/°C in the y-polarization state. The sensor can realize the measurement of multiple parameters including temperature and magnetic intensity and has the advantage of high sensitivity.

Shipborne variable-FOV, dual-wavelength, polarized ocean lidar: design and measurements in the Western Pacific.

For the requirement of high-precision vertical profile of the polarization and optical properties of natural seawater, a ship-borne variable-FOV, dual-wavelength, polarized ocean lidar system is designed to obtain the volume linear depolarization ratio (VDR), color ratio and optical parameter profiles of seawater. With the high signal-to-noise ratio, which benefits from the high power (355 nm with 120 mJ, 532 nm with 200 mJ) solid-state laser and a photon counting recorder with a sampling rate of 1 GHz, the attenuated backscattered signal of seawater in the western Pacific campaign reaches to the depth of 50 m, where a plankton layer presents. The receiver of lidar is capable of switching to wide and narrow field of view (FOV), respectively, to obtain the lidar attenuation coefficient Klidar, which is in good agreement with the beam attenuation coefficient of seawater c with a narrow FOV and diffuse attenuation coefficient Kd with a wide FOV. Besides, the Klidar, and the VDR, at two wavelengths of 355 nm and 532 nm are compared to explore the possibility of multi-wavelength of laser application in the ocean lidar. The VDR and the color ratio profiles have a desirable correlation with the in-situ measurement of chlorophyll a (Chla) and chromophoric dissolved organic matter (CDOM) profiles, respectively. With the combination of the Klidar, the VDR and the color ratio profiles, measured in different regions and time periods during the campaign, the multi-wavelength and polarization lidar shows its potential to explore various ocean compositions, such as the ocean particles size shape, the species and vertical migration characteristics of planktons, and the profile distribution of the ocean compositions.

Coherent high-spectral-resolution lidar for the measurement of the atmospheric Mie-Rayleigh-Brillouin backscatter spectrum.

In this study, a 1550 nm coherent high-spectral-resolution lidar (CHSRL) is developed to measure the optical properties of aerosols and atmospheric wind profiles in the atmospheric boundary layer. To determine the optical properties, a coherent frequency discriminator based on the fast Fourier transform is designed in the CHSRL to separate the Mie and the Rayleigh-Brillouin backscatter spectra to fulfill the needs of high-spectral measurements. The atmospheric wind velocity is retrieved using the simultaneously measured Doppler shift. This non-optical frequency discriminator is a feasible and low-cost solution compared to a narrow-bandwidth optical filter, such as a Fabry-Perot interferometer or an atomic filter. However, shot, amplifier spontaneous emission, and detector noise interfere with the Rayleigh-Brillouin spectrum. Therefore, a spectrum correction algorithm is proposed to recover the interfered Rayleigh-Brillouin spectrum, and the measurement results of the spectral line agree well with those modeled with Tenti S6 at different central frequencies. Finally, field observations for comparison are conducted with the co-located CHSRL, Raman lidar, and coherent Doppler wind lidar. The comparison results indicate that the correlation coefficient of the aerosol backscatter coefficient is 0.84. The correlation coefficient and standard deviation of wind velocity are 0.98 and 0.13 m · s-1, respectively.

Temperature self-calibrated pH sensor based on GO/PVA-coated MZI cascading FBG.

A temperature self-calibrated potential of hydrogen (pH) sensor based on the single mode fiber-tapered dual core photonic crystal fiber-single mode fiber (SMF-TDCPCF-SMF) structure cascaded with a fiber Bragg grating (FBG) is proposed and demonstrated. The TDCPCF structure formed Mach-Zehnder interferometer (MZI) is modified with a coating of graphene oxide/polyvinyl alcohol (GO/PVA) hybrid hydrogel to realize the measurement of pH, and the uncoated FBG is used to calibrate temperature. In our experiment, the sensitivity coefficient of 0.69 nm/pH with R2=0.99 and the hysteresis loss of less than 0.007 are achieved within the pH range from pH 4.00 to pH 9.85. The measured response time from pH 7.00 to pH 4.00, 6.00 and 9.85 are no higher than 10s. Moreover, the resonant wavelengths of MZI and FBG also exhibit good linear relationship with the temperature sensitivity coefficient of 0.15 nm/°C (R2=0.99) and 0.09 nm/°C (R2=0.97) respectively. It is demonstrated successfully that the proposed sensor has broad application prospects in the field of environmental monitoring, biological sensing and chemical analysis, due to the good performance of the temperature self-calibrated pH monitoring, repeatability, linearity, response time and reversibility.

Active and passive optical remote sensing of the aquatic environment: introduction to the feature issue.

Through decades of efforts and practices, we have achieved great progress in understanding ocean biology and biogeochemistry through satellite measurements of ocean (water) color, or passive remote sensing. These include detailed global maps of the distribution of surface phytoplankton, the production of newly formed particulate organic matter through photosynthesis (i.e., primary production), as well as the change and feedback of phytoplankton in a changing climate, to name a few. However, these results are still far from a full account of ocean biology and biogeochemistry, where we want more detailed information of phytoplankton (e.g., types and sizes), as well as information in the vertical dimension. For such, we are happy to see new developments in ocean optics and ocean color remote sensing. These include, but certainly are not limited to, hyperspectral sensors, measurements via polarized setups, as well as ocean lidar systems. In particular, through pumping laser light into deeper ocean, lidar has demonstrated great potential to fill the gap of passive ocean color remote sensing. These developments in technology are providing exciting new findings where breakthroughs in ocean biogeochemistry are on the horizon. Thus, we organized this feature issue in Applied Optics to summarize a few recent developments and achievements, where readers and the community can easily capture progress on both fronts, as well as the potential and advantages of the fusion of passive and active optical sensing. Specifically, this issue contains 12 papers describing research in both active and passive optical remote sensing of aquatic environment. They are still limited in number and subject, but are expected to stimulate the ocean color community with findings relevant for satellite applications.

Aircraft wake vortex and turbulence measurement under near-ground effect using coherent Doppler lidar.

This paper evaluates the wake vortex characteristics using pulsed coherent Doppler lidar (PCDL) under near-ground effect (NGE). A wake vortex visualization demonstrator (V2D) is developed in order to visualize wake vortex in real-time. The combination of radial velocity distribution and FFT spectrum characterization are used to identify the core position of wake vortex. The velocity envelope and Burnham-Hallock model correction are used to retrieve the circulation of wake vortex under NGE. The circulation error, which is caused by PCDL scanning mode, is simulated and corrected. To investigate the dissipation rate's effect on wake vortex in real atmosphere, the cross wind and atmospheric turbulence are concurrently retrieved from the same measurement of wake vortex by using structure function. The statistics of wake vortex parameters are analyzed, based on the measurement campaign at Beijing Capital International Airport (BCIA) in 2017.

High-sensitivity refractive index and temperature sensor based on cascaded dual-wavelength fiber laser and SNHNS interferometer.

A novel differential intensity-measurement high-sensitivity refractive index (RI) sensor based on cascaded dual-wavelength fiber laser and single-mode-no-core-hollow-core-no-core-single-mode (SNHNS) structure is proposed and demonstrated. The sensing unit consists of one uniform fiber Bragg grating (FBG) and an SNHNS structure as all-fiber interferometer filter. The dual-wavelength fiber laser has a ring cavity composed of two FBGs with central wavelengths of 1550.10nm and 1553.61nm. Through monitoring the wavelength shift and the output power difference of the dual-wavelength fiber laser, the simultaneous measurement for RI and temperature is realized. In our experiment, the proposed fiber laser sensor exhibits high RI sensitivities of -193.1dB/RIU and 174.8dB/RIU in the range of 1.334-1.384. The relative variation of output power at the two FBG wavelengths shows a higher RI sensitivity of -367.9dB/RIU with better stability, which is greater than the traditional modal interferometer structure. Meanwhile, the temperature sensitivity of the proposed sensor is 8.53 × 10-3nm/°C, and the changes of laser output power caused by temperature are -0.223dB/°C and 0.215dB/°C.

Doppler lidar investigation of wind turbine wake characteristics and atmospheric turbulence under different surface roughness.

Four field experiments based on Pulsed Coherent Doppler Lidar with different surface roughness have been carried out in 2013-2015 to study the turbulent wind field in the vicinity of operating wind turbine in the onshore and offshore wind parks. The turbulence characteristics in ambient atmosphere and wake area was analyzed using transverse structure function based on Plane Position Indicator scanning mode. An automatic wake processing procedure was developed to determine the wake velocity deficit by considering the effect of ambient velocity disturbance and wake meandering with the mean wind direction. It is found that the turbine wake obviously enhances the atmospheric turbulence mixing, and the difference in the correlation of turbulence parameters under different surface roughness is significant. The dependence of wake parameters including the wake velocity deficit and wake length on wind velocity and turbulence intensity are analyzed and compared with other studies, which validates the empirical model and simulation of a turbine wake for various atmosphere conditions.

High sensitivity axial strain and temperature sensor based on dual-frequency optoelectronic oscillator using PMFBG Fabry-Perot filter.

A dual-frequency optoelectronic oscillator (OEO) incorporating a polarization-maintaining fiber Bragg grating (PMFBG) Fabry-Perot filter for high-sensitivity and high-speed axial strain and temperature sensing is proposed and experimentally demonstrated. In the OEO loop, two oscillation frequencies are determined by a PMFBG Fabry-Perot filter with two ultra-narrow notches and two laser sources which operate as a dual-passband microwave photonic filter. The fiber birefringence affected by axial strain is far less than the temperature. Through monitoring the variations of two oscillating frequencies and beat frequency, the simultaneous measurement for the axial strain and temperature is realized. The sensitivities of the proposed OEO sensor for axial strain and temperature are experimentally measured to be as high as 100.6 or 100.5 MHz/µÎµ and -41 MHz/°C, respectively.

Fiber ring laser based on MMF-PMFBG-MMF filter for three parameters sensing.

A dual-wavelength fiber ring laser based on multimode fiber-polarization maintaining fiber Bragg grating-multimode fiber (MMF-PMFBG-MMF) filter for simultaneously axial strain, temperature and refractive index (RI) sensing is proposed and experimentally demonstrated. In the ring laser, stable dual-wavelength lasing is determined by the MMF-PMFBG-MMF filter with two polarization states. The fiber birefringence affected by axial strain is far less than the effect of the temperature. Through monitoring the variations of each wavelength shift and output power, the simultaneous measurement for the axial strain, temperature and RI is realized. In our experiment, the proposed fiber laser sensor exhibits an axial strain sensitivity of 1.16 × 10-3nm/µÎµ and an RI sensitivity of 81.2dB/RIU. Meanwhile, the temperature sensitivities of two wavelengths are experimentally measured to be 9.74 × 10-3nm/°C and 9.2 × 10-3nm /°C, respectively.

Wind turbine wake visualization and characteristics analysis by Doppler lidar.

Wind power generation is growing fast as one of the most promising renewable energy sources that can serve as an alternative to fossil fuel-generated electricity. When the wind turbine generator (WTG) extracts power from the wind, the wake evolves and leads to a considerable reduction in the efficiency of the actual power generation. Furthermore, the wake effect can lead to the increase of turbulence induced fatigue loads that reduce the life time of WTGs. In this work, a pulsed coherent Doppler lidar (PCDL) has been developed and deployed to visualize wind turbine wakes and to characterize the geometry and dynamics of wakes. As compared with the commercial off-the-shelf coherent lidars, the PCDL in this work has higher updating rate of 4 Hz and variable physical spatial resolution from 15 to 60 m, which improves its capability to observation the instantaneous turbulent wind field. The wind speed estimation method from the arc scan technique was evaluated in comparison with wind mast measurements. Field experiments were performed to study the turbulent wind field in the vicinity of operating WTGs in the onshore and offshore wind parks from 2013 to 2015. Techniques based on a single and a dual Doppler lidar were employed for elucidating main features of turbine wakes, including wind velocity deficit, wake dimension, velocity profile, 2D wind vector with resolution of 10 m, turbulence dissipation rate and turbulence intensity under different conditions of surface roughness. The paper shows that the PCDL is a practical tool for wind energy research and will provide a significant basis for wind farm site selection, design and optimization.

Mobile multi-wavelength polarization Raman lidar for water vapor, cloud and aerosol measurement.

Aiming at the detection of atmospheric water vapor mixing ratio, depolarization ratio, backscatter coefficient, extinction coefficient and cloud information, the Water vapor, Cloud and Aerosol Lidar (WACAL) is developed by the lidar group at Ocean University of China. The lidar consists of transmitter, receiver, data acquisition and auxiliary system. For the measurement of various atmospheric physical properties, three channels including Raman channel, polarization channel and infrared channel are integrated in WACAL. The integration and working principle of these channels are introduced in details. The optical setup, the housekeeping of the system and the data retrieval routines are also presented. After the completion of the construction of the lidar, the WACAL system was installed in Ocean University of China (36.165°N, 120.5°E), Qingdao for the measurement of atmosphere during 2013 and 2014. The measurement principles and some case studies corresponding to various atmospheric physical properties are provided. Finally, the result of one continuous measurement example operated on 13 June 2014 is presented. The WACAL can measure the aerosol and cloud optical properties as well as the water vapor mixing ratio. It is useful for studying the direct and indirect effects of the aerosol on the climate change.

Inhibition of prostatic cancer growth by ginsenoside Rh2.

Ginsenoside Rh2 (GRh2) has been reported to have therapeutic effects on some types of cancer, but its effect on prostatic cancer has not been extensively evaluated. Here, we show that GRh2 can substantially inhibit the growth of prostatic cancer in vivo and in vitro. Moreover, the inhibition of the tumor growth appeared to result from a combined inhibitory effect on tumor cell proliferation and tumor cell invasiveness. Further analyses suggest that GRh2 seemed to activate transforming growth factor ß (TGFß) receptor signaling in prostatic cancer cells, which subsequently inhibits cell proliferation and invasion through regulating cell-cycle controllers and (MMPs), respectively. Taken together, our data reveal an essential anti-prostatic cancer effect of GRh2 and demonstrate that this effect is through augment of TGFß receptor signaling in the prostatic cancer cells. GRh2 thus appears to be a promising therapy for prostatic cancer.

A Time-Consistency Curriculum for Learning From Instance-Dependent Noisy Labels.

Many machine learning algorithms are known to be fragile on simple instance-independent noisy labels. However, noisy labels in real-world data are more devastating since they are produced by more complicated mechanisms in an instance-dependent manner. In this paper, we target this practical challenge of Instance-Dependent Noisy Labels by jointly training (1) a model reversely engineering the noise generating mechanism, which produces an instance-dependent mapping between the clean label posterior and the observed noisy label and (2) a robust classifier that produces clean label posteriors. Compared to previous methods, the former model is novel and enables end-to-end learning of the latter directly from noisy labels. An extensive empirical study indicates that the time-consistency of data is critical to the success of training both models and motivates us to develop a curriculum selecting training data based on their dynamics on the two models' outputs over the course of training. We show that the curriculum-selected data provide both clean labels and high-quality input-output pairs for training the two models. Therefore, it leads to promising and robust classification performance even in notably challenging settings of instance-dependent noisy labels where many SoTA methods could easily fail. Extensive experimental comparisons and ablation studies further demonstrate the advantages and significance of the time-consistency curriculum in learning from instance-dependent noisy labels on multiple benchmark datasets.

[Detection rates of atherosclerosis by carotid versus lower limb ultrasonography in newly diagnosed type 2 diabetics].

OBJECTIVE: To compare the detection rates of atherosclerosis by carotid versus lower limb ultrasound in newly diagnosed type 2 diabetics and analyze the relationship between atherosclerosis and cardio-cerebrovascular events. METHODS: A total of 148 newly diagnosed type 2 diabetics were recruited. Both carotid and lower extremity atherosclerosis were assessed by Doppler ultrasound. Diabetic atherosclerosis was defined as the presence of either carotid or lower extremity plaques in any of the above-mentioned arterial segments. A kappa value was computed to document the agreement between isolated carotid (or lower limb) atherosclerosis and diabetic atherosclerosis. The prevalence of cardio-cerebrovascular events was compared among different distribution types of atherosclerosis. RESULTS: According to the diagnostic criteria, the prevalence of diabetic atherosclerosis was 66.2% in the newly diagnosed type 2 diabetes. Based on carotid or lower extremity ultrasound, the prevalence of diabetic atherosclerosis was 27.0% and 62.2% respectively in newly diagnosed type 2 diabetes. The kappa values for the agreement between carotid/lower limb atherosclerosis and diabetic atherosclerosis were 0.32/0.91 (95% confidence interval 0.22-0.42 for carotid vs 0.84-0.98 for lower extremity). The combination of carotid and lower extremity arterial atherosclerosis was associated with a significantly increased detection rate of cardio-cerebrovascular events (26.5%) versus those with either carotid or lower extremity arterial atherosclerosis (0% and 10.3% respectively). CONCLUSION: The combination of carotid and lower extremity ultrasonography can more accurately reflect the atherosclerotic lesions in type 2 diabetes. Due to a higher prevalence of cardio-cerebrovascular events, type 2 diabetics with both carotid and lower extremity atherosclerosis should be managed more aggressively to reduce the risk of cardio-cerebrovascular events.

A Parametrical Model for Instance-Dependent Label Noise.

In label-noise learning, estimating the transition matrix is a hot topic as the matrix plays an important role in building statistically consistent classifiers. Traditionally, the transition from clean labels to noisy labels (i.e., clean-label transition matrix (CLTM)) has been widely exploited on class-dependent label-noise (wherein all samples in a clean class share the same label transition matrix). However, the CLTM cannot handle the more common instance-dependent label-noise well (wherein the clean-to-noisy label transition matrix needs to be estimated at the instance level by considering the input quality). Motivated by the fact that classifiers mostly output Bayes optimal labels for prediction, in this paper, we study to directly model the transition from Bayes optimal labels to noisy labels (i.e., Bayes-Label Transition Matrix (BLTM)) and learn a classifier to predict Bayes optimal labels. Note that given only noisy data, it is ill-posed to estimate either the CLTM or the BLTM. But favorably, Bayes optimal labels have no uncertainty compared with the clean labels, i.e., the class posteriors of Bayes optimal labels are one-hot vectors while those of clean labels are not. This enables two advantages to estimate the BLTM, i.e., (a) a set of examples with theoretically guaranteed Bayes optimal labels can be collected out of noisy data; (b) the feasible solution space is much smaller. By exploiting the advantages, this work proposes a parametrical model for estimating the instance-dependent label-noise transition matrix by employing a deep neural network, leading to better generalization and superior classification performance.