Baicalin Attenuates Oxygen–Glucose Deprivation/Reoxygenation–Induced Injury by Modulating the BDNF-TrkB/PI3K/Akt and MAPK/Erk1/2 Signaling Axes in Neuron–Astrocyte Cocultures

Background: Baicalin (BCL), a candidate drug for ischemic stroke, has been indicated to protect neurons by promoting brain-derived neurotrophic factor (BDNF). However, the cellular source of BDNF release promoted by baicalin and its detailed protective mechanism after ischemia/reperfusion remains to be studied. The aim of this study was to investigate the neuroprotective mechanisms of baicalin against oxygen–glucose deprivation/reoxygenation (OGD/R) in a neuron–astrocyte coculture system and to explore whether the BDNF-TrkB pathway is involved.Methods and Results: A neuron–astrocyte coculture system was established to elucidate the role of astrocytes in neurons under OGD/R conditions. The results demonstrated that astrocytes became reactive astrocytes and released more BDNF in the coculture system to attenuate neuronal apoptosis and injury after OGD/R. BCL maintained the characteristics of reactive astrocytes and obviously increased the expression of cyclic AMP response element-binding protein (CREB) and the levels of BDNF in the coculture system after OGD/R. To further verify whether BDNF binding to its receptor tyrosine kinase receptor B (TrkB) was required for the neuroprotective effect of baicalin, we examined the effect of ANA-12, an antagonist of TrkB, on NA system injury, including oxidative stress, inflammation, and apoptosis induced by OGD/R. The results showed that treatment of NA systems with ANA-12 significantly attenuated the neuroprotection of BCL. The phosphatidylinositol 3-kinase (PI3K)/protein kinase B (Akt) and mitogen-activated protein kinase (MAPK)/extracellular signal-regulated kinase (ERK) pathways are two important downstream cascades of signaling pathways activated by BDNF binding to TrkB. We investigated the expressions of TrkB, PI3K, Akt, MAPK, and ERK. The results demonstrated that baicalin significantly increased the expressions of TrkB, PI3K/AKT, and MAPK/ERK.Conclusion: The neuroprotective effects of baicalin against oxidative stress, inflammation, and apoptosis were improved by astrocytes, mainly mediated by increasing the release of BDNF and its associated receptor TrkB and downstream signaling regulators PI3K/Akt and MAPK/ERK1/2

Evaluation of an Ocean Reanalysis System in the Indian and Pacific Oceans

This paper describes an ocean reanalysis system in the Indian and Pacific oceans (IPORA) and evaluates its quality in detail. The assimilation schemes based on ensemble optimal interpolation are employed in the hybrid coordinate ocean model to conduct a long-time reanalysis experiment during the period of 1993–2020. Different metrics including comparisons with satellite sea surface temperature, altimetry data, observed currents, as well as other reanalyses such as ECCO and SODA are used to validate the performance of IPORA. Compared with the control experiment without assimilation, IPORA greatly reduces the errors of temperature, salinity, sea level anomaly, and current fields, and improves the interannual variability. In contrast to ECCO and SODA products, IPORA captures the strong signals of SLA variability and reproduces the linear trend of SLA very well. Meanwhile, IPORA also shows a good consistence with observed currents, as indicated by an improved correlation and a reduced error

A Simple Bias Correction Scheme in Ocean Data Assimilation

The mode bias is present and time-dependent due to imperfect configurations. Data assimilation is the process by which observations are used to correct the model forecast, and is affected by the bias. How to reduce the bias is an important issue. This paper investigates the roles of a simple bias correction scheme in ocean data assimilation. In this scheme, the misfits between modeled and monthly temperature and salinity with interannual variability from the Met Office Hadley Centre subsurface temperature and salinity data set (EN4.2.2) are used for the innovations in assimilation via the Ensemble Optimal Interpolation method. Two assimilation experiments are implemented to evaluate the impacts of bias correction. The first experiment is a data assimilation system without bias correction. In the second experiment, the bias correction is applied in assimilation. For comparison, the nature run with no assimilation and no bias correction is also conducted. When the bias correction is not applied, the assimilation alone leads to a rising trend in the heat and salt content that is not found in the observations. It is a spurious temporal variability due to the effect of the bias on the data assimilation. Meanwhile, the assimilation experiment without bias correction also produces significant negative impacts on the subsurface salinity. The experiment with bias correction performs best with notable improvements over the results of the other two experiments

Torque Ripple Suppression of Brushless DC Motor Drive System Based on Improved Harmonic Injection Active Disturbance Rejection Control

The positioning accuracy and speed stability of the brushless DC motor (BLDC motor), as the drive element of the optomechanically scanned system (OMSS), are closely interrelated to the final imaging quality of the system. Active disturbance rejection control (ADRC) with strong anti-interference ability, fast response and good robustness is one of the extensively used control strategies. However, the performance of ADRC working in a complicated environment will be limited due to the controller structure, parameter tuning and the influence of multi-source nonlinear disturbance. Therefore, an improved ADRC method is proposed, which can switch between ‘point-to-point control mode’ and ‘stable speed control mode’ according to the system requirements. To further suppress the torque ripple and improve the control performance of the system, an improved harmonic injection scheme is added, and the parameters of improved ADRC are tuned by a slime mould algorithm based on a Levy flight operator (LF-SMA). The stability of the proposed ADRC is proved by Lyapunov stability theory. The experimental results show that the proposed control scheme could be available to reduce the torque ripple of the system

Determination of Field of View of a Dawn–Dusk Sun-Synchronous Orbit Satellite Based on Improved Observation Mode

We report a method for determining the field of view (FOV) of a dawn–dusk sun-synchronous orbit satellite based on an improved observation mode. The target trajectory distribution model in geosynchronous orbit (GEO) is established, the natural rendezvous mode is improved, and the observation mode of the satellite is determined. A scheme for determining the thresholds of cross-orbit field of view (COFOV) and the along-orbit field of view (AOFOV) was developed. The result shows that the coverage of the satellite can reach more than 95% when the improved observation mode is used to observe the GEO target. When the revisit period of the satellite is one day, the threshold of the COFOV is 15°, and the threshold of the AOFOV is 12°

Determination of Field of View of a Dawn–Dusk Sun-Synchronous Orbit Satellite Based on Improved Observation Mode

We report a method for determining the field of view (FOV) of a dawn–dusk sun-synchronous orbit satellite based on an improved observation mode. The target trajectory distribution model in geosynchronous orbit (GEO) is established, the natural rendezvous mode is improved, and the observation mode of the satellite is determined. A scheme for determining the thresholds of cross-orbit field of view (COFOV) and the along-orbit field of view (AOFOV) was developed. The result shows that the coverage of the satellite can reach more than 95% when the improved observation mode is used to observe the GEO target. When the revisit period of the satellite is one day, the threshold of the COFOV is 15°, and the threshold of the AOFOV is 12°

Resonant Coupling of Hermite-Gaussian Transverse Modes in the Triangular Cavity of a Cavity Ring-down Spectroscope

During resonance in resonant cavities, such as those used in laser or cavity ring-down spectroscopes (CRDS), resonant coupling between higher-order transverse modes and fundamental modes can seriously affect the quality of the beam and introduce measurement errors. Several coupling models, such as thermal deformation coupling and scattering coupling, have been established according to existing coupling theory and specific application scenarios; however, these coupling models have not been attributed to a unified theory. In this paper, we reveal that the same resonant coupling excitation factors exist under different types of environmental perturbation. The conditions and range of resonant coupling in a CRDS ring-down cavity are systematically analyzed, and a preferential coupling model of the middle-order modes is proposed. The time-domain characteristics of the CRDS are used in experiments to analyze the resonant coupling between the modes in a weak energy system. The order and coupling range of the middle-order modes involved in resonant coupling are verified using the modal filtering characteristics of the triangular cavity; this paper presents a unified explanation for various types of resonant coupling and also provides a new approach to resonant coupling experiments performed in high-finesse resonant cavities

Effect of Fiber Optic Plate on Centroid Locating Accuracy of Monocentric Imager

We propose a method for obtaining the centroid locating accuracy (CLA) of a monocentric imager with a fiber optic plate (FOP) as a relay image transmission element in order to reduce the loss of CLA due to the addition of FOP. We constructed a two-stage image transmission coupling model of spherical focal surface (FOP) image sensor. By analyzing the influences of FOP parameters, including the fill factor and the fiber diameter, and FOP in-plane displacements, including rotation and translation on CLA, the loss of the lowest CLA that the monocentric imager can withstand caused by the addition of the FOP was reduced by 20%

Hyperspectral Band Selections for Enhancing the Discrimination of Difficult Targets Using Local Band Index and Particle Swarm Optimization

Due to their similar color and material variability, some ground objects have similar characteristics and overlap in some bands. This leads to a drop in the classification accuracy of hyperspectral images. To address this problem, we simulated hyperspectral images of vegetation and objects with similar colors by mixed pixel calculation to test the classification performance of the dimensionality reduction method for samples with close spectra. In addition, we proposed a novel wavelength selection algorithm called the LBI-BPSO (Binary Particle Swarm Optimization with Local Band Index), which combines the information amount and inter-class separability. The novelty of this study is in its proposal of an improvement of IOIF using inter-class distance. Based on the calculation of the information content by the local band index, the inter-class distance was introduced to measure the inter-class separability of ground objects, and a reasonable fitness function is proposed. It can obtain the wavelength combination of two DR criteria, which considers the larger amount of information and better sample separability. The classification performance of the simulation dataset is verified by comparing LBI-BPSO with Partitioned Relief-F, IOIF (Improved Optimum Index Factor) and GA-BPSO (Particle Swarm Optimization with a Genetic Algorithm). Under the conditions that the signal-to-noise ratio is 1000, compared with IOIF, the OA of LBI-BPSO improved by 2.90%, the AA improved by 2.75%, and the Kappa coefficient improved by 3.91%. LBI-BPSO also showed the best results in the analysis of different abundances and signal-to noise-ratios. The results show that the new wavelength selection algorithm LBI-BPSO, which combines the amount of information and inter-class separability, is more effective than IOIF and GA-BPSO in classifying objects with similar colors and effectively improves the classification accuracy

Hyperspectral Band Selections for Enhancing the Discrimination of Difficult Targets Using Local Band Index and Particle Swarm Optimization

Due to their similar color and material variability, some ground objects have similar characteristics and overlap in some bands. This leads to a drop in the classification accuracy of hyperspectral images. To address this problem, we simulated hyperspectral images of vegetation and objects with similar colors by mixed pixel calculation to test the classification performance of the dimensionality reduction method for samples with close spectra. In addition, we proposed a novel wavelength selection algorithm called the LBI-BPSO (Binary Particle Swarm Optimization with Local Band Index), which combines the information amount and inter-class separability. The novelty of this study is in its proposal of an improvement of IOIF using inter-class distance. Based on the calculation of the information content by the local band index, the inter-class distance was introduced to measure the inter-class separability of ground objects, and a reasonable fitness function is proposed. It can obtain the wavelength combination of two DR criteria, which considers the larger amount of information and better sample separability. The classification performance of the simulation dataset is verified by comparing LBI-BPSO with Partitioned Relief-F, IOIF (Improved Optimum Index Factor) and GA-BPSO (Particle Swarm Optimization with a Genetic Algorithm). Under the conditions that the signal-to-noise ratio is 1000, compared with IOIF, the OA of LBI-BPSO improved by 2.90%, the AA improved by 2.75%, and the Kappa coefficient improved by 3.91%. LBI-BPSO also showed the best results in the analysis of different abundances and signal-to noise-ratios. The results show that the new wavelength selection algorithm LBI-BPSO, which combines the amount of information and inter-class separability, is more effective than IOIF and GA-BPSO in classifying objects with similar colors and effectively improves the classification accuracy