Explore the vast range of titles available.

Feature extraction and recognition of underwater targets are important in military and civilian areas. This paper studied water surface acoustic wave (WSAW) detection by a millimeter wave (mmWave) radar. The mmWave-based endpoint detection method of the WSAW was introduced. Simulated results show that the continuous wavelet transform (CWT) method has a better detection performance. A 77 GHz large aperture antenna mmWave radar sensor and an underwater acoustic transmitter have been applied to conduct laboratory experiments. Still water surface experimental results verify that the CWT method has better detection capability, and the mmWave radar can accurately detect even 155 nm WSAW. Wavy water surface experimental results demonstrate the ability of the mmWave radar to analyze the time-frequency feature of the weak WSAW signal. These works indicate the potential of mmWave radar for the cross-medium detection and recognition of underwater targets.

The amount of precipitation directly affects the ecological balance and the economic benefits of the region. However, the highly nonlinear and stochastic nature of precipitation time series data limits the accuracy of predictions. Therefore, improving the prediction accuracy of regional precipitation is crucial for formulating disaster prevention and mitigation measures, as well as for responding to climate change. To achieve a scientific and effective prediction of regional precipitation, this study proposed a precipitation prediction model based on the CEEMDAN-TVMD-IPO-BiLSTM framework. The model first decomposed the original precipitation data using the CEEMDAN decomposition algorithm, output the modal components and residual components, and then used the topology optimization algorithm (TTAO) to optimize the VMD, and decomposed the high-dimensional sequence in the first decomposition result for the second time. An improved parrot optimizer (IPO) algorithm based on chaotic Cat and Cauchy-Gaussian variation was introduced to optimize the bidirectional long short-term memory neural network (BiLSTM). This precisely constructed prediction model was utilized to predict regional precipitation, with historical monthly precipitation data from three representative cities in China—Guangzhou in the east region, Changsha in the central region, and Emeishan in the west region—used to validate the model’s accuracy and robustness. Experimental results indicated that the proposed CEEMDAN-TVMD-IPO-BiLSTM model achieved RMSE values of 32.373, 14.445, and 22.447 for the three cities, respectively, with corresponding R² values of 0.960, 0.972, and 0.977, outperforming other models. This demonstrated its advantages in monthly precipitation prediction, allowing for a better characterization of precipitation fluctuation patterns and providing scientific references for formulating policies to combat droughts and floods.

Gasdermin E (GSDME) is a pyroptotic cell death effector and a promising target for pyroptotic tissue injury. Here we perform high-throughput screening and demonstrate that methylcobalamin (MeCbl), an endogenous coenzyme form of vitamin B12, is a specific GSDME inhibitor and highly effective against cholestatic liver failure. MeCbl specifically blocks GSDME cleavage by directly binding with GSDME. In cholestasis-, cisplatin- or concanavalin A (Con A)-induced male mouse models, MeCbl significantly suppresses liver transaminase activities and inflammation, alleviates hepatocyte death, and reduces mortality of mice by blocking GSDME cleavage. The conserved Cys180 residue in GSDME is essential for caspase-3/GzmB recognition. MeCbl in base-off conformation coordinates to Cys180 to prevent caspase-3/GzmB-GSDME interactions and thereby GSDME-mediated pyroptosis. In summary, our study discovers MeCbl as a specific GSDME inhibitor that is promisingly to be developed as an effective drug against cholestatic liver failure, and other GSDME triggered sterile inflammation and/or organ failure. Gasdermin E (GSDME) is a pyroptotic cell death effector and a promising target for pyroptotic tissue injury. Here, the authors show that methylcobalamin in base-off conformation coordinates to Cys180 in GSDME to prevent caspase-3/GzmB-GSDME interactions and thereby GSDME-mediated liver failure.

High-frequency (HF) radars are routinely used for remotely sensing ocean surface currents. However, the performance of the most widely used direction-finding HF radar is degraded due to the effect of the inevitable deviations of actual antenna pattern on the direction of arrival (DOA) estimation. In this paper, we quantify the DOA estimation error resulting from the deviation of the actual antenna pattern from the ideal one. Theoretical analysis and field experiment results suggest that the ratio of the deviations for the two loops dominates the DOA estimation error. Thus, eliminating the effect of the antenna pattern deviations on DOA estimation error is transformed into eliminating the effect of this ratio. From this, a calibration method based on the time-averaged local spatial coverage rate (TLSCR) is proposed to reduce the effect of the antenna pattern deviations on current extraction, which uses the ideal antenna pattern to estimate the DOA of the echoes. To validate this proposed calibration method, we assess the radar-derived radial velocities by comparing with in situ observations. The comparison results indicate that the proposed TLSCR calibration method can effectively reduce the DOA estimation error and improve the performance of the direction-finding HF radar in current observation.

With the increasing penetration of distributed energy resources in power systems, the coupling between transmission and distribution networks has become increasingly complex. How to ensure short-term voltage stability (STVS) and maintain the supply–demand flexibility balance under complex transmission–distribution interactions and uncertain renewable generation has become a key challenge that must be addressed for coordinated transmission–distribution operation. To this end, this paper proposes a transmission–distribution coordinated optimal scheduling strategy that accounts for STVS and the supply–demand flexibility balance. First, the causes of short-term voltage instability were analyzed, and a time-domain simulation model of the power system was developed that incorporates the active voltage support capability of distribution networks. Second, an improved flexibility demand model was established based on the probability-box (p-box) method. Then, economic models for the transmission network and the distribution network were formulated, and a coordinated transmission–distribution operation model was constructed by considering both the short-term voltage instability risk and the supply–demand flexibility imbalance risk. Finally, a test system was built by connecting two modified IEEE 13-node feeders to buses 14 and 13 of the IEEE 14-bus system, and simulation studies were conducted. The results demonstrate that the proposed coordinated scheduling strategy can effectively reduce the risk of short-term voltage instability and ensure flexibility balance across the transmission and distribution networks.

Mapping wind with high-frequency (HF) radar is still a challenge. The existing second-order spectrum based wind speed extraction method has the problems of short detection distances and low angular resolution for broad-beam HF radar. To solve these problems, we turn to the first-order Bragg spectrum power and propose a space recursion method to map surface wind. One month of radar and buoy data are processed to build a wind spreading function model and a first-order spectrum power model describing the relationship between the maximum of first-order spectrum power and wind speed in different sea states. Based on the theoretical propagation attenuation model, the propagation attenuation is calculated approximately by the wind speed in the previous range cell to compensate for the first-order spectrum in the current range-azimuth cell. By using the compensated first-order spectrum, the final wind speed is extracted in each cell. The first-order spectrum and wind spreading function models are tested using one month of buoy data, which illustrates the applicability of the two models. The final wind vector map demonstrates the potential of the method.

Wind speed is an important sea surface dynamic parameter which influences a wide variety of oceanic applications. Wave height and wind direction can be extracted from high frequency radar echo spectra with a relatively high accuracy, while the estimation of wind speed is still a challenge. This paper describes an artificial neural network based method to estimate the wind speed in HF radar which can be trained to store the specific but unknown wind-wave relationship by the historical buoy data sets. The method is validated by one-month-long data of SeaSonde radar, the correlation coefficient between the radar estimates and the buoy records is 0.68, and the root mean square error is 1.7 m/s. This method also performs well in a rather wide range of time and space (2 years around and 360 km away). This result shows that the ANN is an efficient tool to help make the wind speed an operational product of the HF radar.

The high-frequency radars (HFRs) receiving the sea echoes backscattered from the fluctuating ocean surface to remotely sense ocean surface currents are a popular and powerful tool in oceanic observation. Dominant error source in current measurement for HFR systems has been recognized to be the direction of arrival (DOA) determination of the sea echoes. To eliminate this error and therefore improve the performance of direction-finding HFR system in current measurement, we have investigated a dual monopole-cross-loop (MCL) antenna array in current observation. Simulations indicated that the dual MCL antenna array has a better performance than the conventional single MCL antenna system in current mapping, especially for the complex current profile. And comparisons of radar field data and buoy measurements suggested that the RMSE value was larger than 15 cm/s for the conventional MCL antenna. But it decreased to 12.64 cm/s for the dual MCL antenna array. Moreover, the temporal coverage rate also showed the benefit of using this antenna system in current mapping. The results demonstrated that it is advisable to adopt the dual MCL antenna array in operational applications.

ABSTRACT A human parechovirus (HPeV), CH-ZXY1, was detected in feces from a child with diarrhea. Phylogenetic trees over three different genomic regions revealed discordant topological structures. Recombination analysis indicates that CH-ZXY1 is a recombinant resulting from recombination between HPeV5 and HPeV1, which was confirmed by PCR covering the recombination breakpoint.

This study compared the efficiencies of two widely used automatic eddy detection algorithms—that is, the winding-angle (WA) method and the vector geometry (VG) method—and investigated the submesoscale eddy properties using surface current observations derived from high-frequency radars (HFRs) in the Taiwan Strait. The results showed that the WA method using the streamline and the VG method based on the streamfunction field have almost the same capacity for identifying eddies, but the former is more competent than the latter in capturing the eddy size. The two algorithms simultaneously identified 1080 submesoscale eddies, with the centers and boundaries determined only by the WA method, and they were further used to investigate the eddy properties. In general, no significant difference was observed between the cyclonic and anticyclonic eddies in terms of radius, life span, and kinematics, as well as the evolution during their life cycles. The typical radius of the eddy in this region was 3–18 km. And a strong correlation was observed between the life span and the radius. The spatial distribution of the eddies indicated that topography played a significant role in the generation of the eddies. And the trajectories of the eddies suggested that all the eddies in this area mostly tended to move southeastward. Statistically, three different stages of the eddy’s life span could be identified by the significant growth and decay of the radius and the mean kinetic energy. This study shows the great capability of HFRs in oceanography research and applications, especially for observing the submesocale dynamics.