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Background As infection is a common complication and cause of death in hematological disease, early detection of microorganisms causing infections is particularly important for the improvement of prognosis. The newly emerged metagenomic next-generation sequencing (mNGS) technology has the advantages of simple operation, small sample size required, fast detection, unsusceptible to contamination. Moreover, it has better performance than culture methods in detecting marginal microorganisms. Objective To determine the causes of infections in patients with hematological diseases via analyzing the bacterial and viral pathogen spectra of infections in such patients detected using mNGS, to inform relevant clinical treatment. Methods Participants (n=53) were hematological disease patients who had clinical infections or suspected infections symptoms during the hospitalization in Department of Hematology, the First Affiliated Hospital of Guangxi Medical University from August 2018 to December 2020. Samples collected from them included whole blood, cerebrospinal fluid, pleural effusion, tissue, abdominal drainage fluid, joint fluid, sputum, fluid aspirated by puncture of the right lower extremity. For detecting microorganisms causing infections, mNGS technology was used for all patients (58 samples) , culture was used for 52 patients (55 samples) , G/GM test was used for 46 patients (50 samples) , and PCR test was used for 44 patients (48 samples) as well. Results The bacterial and viral pathogen spectra of infections detected by mNGS technology showed that the most common Gram-positive bacteria were Propionibacterium acnes (42 times) , Staphylococcus epidermidis (33 times) , and Staphylococcus hominis (32 times) , the most common Gram-negative bacteria were Acinetobacter johnsonii (26 times) , Burkholderia vietnamiensis (20 times) , and Burkholderia ubonensis (19 times) , the most common fungus was Malassezia restricta (28 times) , and the most common viruses were Cytomegalovirus (26 times) , Epstein-Barr virus (14 times) and Torque teno virus (19 times) . Toxoplasma gondii was detected in the blood and cerebrospinal fluid of a patient with severe thalassemia after hematopoietic stem cell transplantation. Compared to culture method, G/GM test, and PCR test, mNGS technology had a higher detection rate (P

Oil spill detection plays an important role in marine environment protection. The technique of global navigation satellite system-reflectometry (GNSS-R) has the advantage of a short revisit time, which could help with timely cleanup of marine oil pollution. The conventional GNSS-R oil spill detection algorithm can resolve only the dielectric constant of oil based on power ratio measurements, while that of water cannot be realized. This is because the dielectric constant of water is much larger than that of oil such that the range of the equation used in the conventional algorithm is inadequate. To resolve this problem, we proposed a new algorithm containing a new equation with a larger scope, which has never been applied previously to GNSS-R oil spill detection. We derived a lookup method to resolve the dielectric constant of both oil and water. To validate our method, a drone-borne GNSS-R experiment based on dual-frequency QZSS reflection signals was conducted on 17 July 2023 using experimental pools simulating oil spills. Raw IF data in the L1 and L5 bands, collected using dual antennas and a data recorder, were processed using a software-defined receiver to deduce the power ratios and SNR of the GNSS signals. Results showed that the proposed algorithm is capable of resolving the dielectric constants of the reflected surface. In addition, the L5 signal was found to provide more detail and better contrast than the L1 C/A signal. [ABSTRACT FROM AUTHOR]

For the transport networks only equipped with sparse or isolated detectors, short‐term traffic flow forecasting faces the following problems: (1) there are only temporal information and no spatial information; (2) the noises in the traffic flow significantly affect the forecasting performance. In this paper, a lag‐related noise shrinkage stacked long short‐term memory (LSTM) network is proposed for the traffic flow forecasting task only related to temporal information. To extract effective temporal features, the optimal time lags are selected in the traffic flow and converted into lag‐related multi‐dimensional data. Then, a discrete wavelet threshold denoising shrinkage algorithm is designed to filter the noises to construct a more reliable training set. A multi‐level stacked LSTM network is employed to learn the features of the training set to map the past traffic flow to the future flow. Four benchmark datasets are to evaluate the forecasting performance by extensive experiments. The comparison with the state‐of‐the‐art models demonstrates an average improvement of 7.28% in MAPE and 6.02% in RMSE. In addition, the proposed method has been applied in the Guilin Travel Network Bus Intelligent Dispatching System. It improves the utilization of the vehicles and reduces operating costs. [ABSTRACT FROM AUTHOR]

Based on delay-Doppler maps (DDMs) in raw counts generated by spaceborne global navigation satellite system reflectometry (GNSS-R) receivers, retrieving ocean surface wind speeds is feasible, so several spaceborne GNSS-R missions have been carried out. However, it is currently troubled by global data latency of several hours or even more due to the bottleneck in the satellite downlink. Consequently, this article, for the first time, presents an algorithm for spaceborne GNSS-R receivers to conduct the DDM calibration in orbit and then to retrieve ocean surface wind speeds in real time, which contributes to not only lightening the burden on downloading a wealth of scientific data but also broadcasting real-time ocean surface wind speeds to users. Since there is a power correlation between direct and reflected signals from the same GNSS satellite with respect to the GNSS-R receiver, this algorithm calibrates direct signal power first, and then it estimates the real-time GNSS transmitter effective isotropic radiated power at the reflected signal according to the normalized antenna pattern of the corresponding GNSS satellite. Afterward, DDMs in raw counts are calibrated. Finally, ocean surface wind speeds are computed using pretrained geophysical model functions. Exploiting the scientific data from the GNOS-II onboard China's FY-3E satellite, this algorithm is validated carefully, and final retrieved ocean surface wind speeds against collocated European Centre for Medium-Range Weather Forecasts wind speeds have an overall root-mean-square error of 1.68 m/s and 1.50 m/s for GPS-R and BDS-R, respectively. [ABSTRACT FROM AUTHOR]

The global navigation satellite system radio occultation (GNSS-RO) is an important means of space-based meteorological observation. It is necessary to test the Global Navigation Satellite System Occultation signal receiver on the ground before the deployment of space-based occultation detection systems. The current approach of testing the GNSS signal receiver on the ground is mainly the mountaintop-based testing approach, which has problems such as high cost and large simulation error. In order to overcome the limitations of the mountaintop-based test approach, this paper proposes an accurate, repeatable, and controllable GNSS atmospheric occultation simulation system and builds a load performance evaluation approach based on the ground-based GNSS atmospheric occultation simulation system on the basis of it. The GNSS atmospheric occultation simulation system consists of the visualization and interaction module, the GNSS-RO simulation signal generation module, the GNSS-RO simulator module, the GNSS-RO signal receiver module, and the GNSS-RO inversion and evaluation module, combined with the preset atmospheric model to generate GNSS-RO simulation signals with a high degree of simulation, and comparing the atmospheric parameters of the inversion performance of the GNSS-RO signal receiver with the parameters of the preset atmospheric model to obtain the error data. The overall performance of the GNSS-RO signal receiver can be evaluated based on the error information. The novel approach to evaluate the GNSS-RO signal receiver performance proposed in this paper is validated by using the FY-3E (FengYun-3E) receiver qualification parts that have been verified in orbit, and the results confirm that the approach can meet the requirements of the GNSS-RO receiver performance test. This study shows that the novel approach to evaluate the GNSS-RO signal receiver performance in terms of the ground-based atmospheric occultation simulation system can efficiently and accurately be used to carry out the receiver test and provides an effective solution for the ground-based test of GNSS-RO signal receivers. [ABSTRACT FROM AUTHOR]

This article proposes a single-frequency occultation method whose core is the reconstruction of a second frequency measurement. We process the actual received Galileo E1 single-frequency occultation observation data of FengYun3E to meet the urgent need for single-frequency Galileo occultation inversion of FengYun3 E/F/G/H satellites. Galileo single-frequency occultation events are globally distributed evenly and have stable quantities. The refractive index products and dry temperature products inverted from the single-frequency occultation data are reliable at altitudes of 5–30 km. The Galileo E1 single-frequency occultation process can effectively improve the output of FengYun3E/GNOS occultation products. These results validate the feasibility and correctness of using FengYun3/GNOS for the actual Galileo single-frequency occultation process. The atmospheric occultation products of Galileo single-frequency occultation increase the quantity of global occultation products and serve as a beneficial supplement to global numerical weather prediction data sources. [ABSTRACT FROM AUTHOR]

In the face of the difficulty in achieving high-quality integrated molding of longitudinally and transversely stiffened panels for helicopters by resin-matrix composite materials, we combine the prepreg process and the resin transfer molding (RTM) process to propose a hybrid resin transfer molding (HRTM) for composite stiffened panel structures. The HRTM process uses a mixture of prepreg and dry fabric to lay up a hybrid fiber preform, and involves injecting liquid resin technology. Using this process, a longitudinally and transversely stiffened panel structure is prepared, and the failure modes under compressive load are explored. The results show that at the injection temperature of the RTM resin, the prepreg resin dissolves slightly and has little effect on the viscosity of the RTM resin. Both resins have good miscibility at the curing temperature, which allows for the overall curing of the resin. A removable box core mold for the HRTM molding is designed, which makes it convenient for the mold to be removed after molding and is suitable for the overall molding of the composite stiffened panel. Ultrasonic C-scan results show that the internal quality of the composite laminates prepared using the HRTM process is good. A compression test proves that the composite stiffened panel undergoes sequential buckling deformation in different areas under compressive load, followed by localized debonding and delamination of the skin, and finally failure due to the fracture of the longitudinal reinforcement ribs on both sides. The compressive performance of the test specimen is in good agreement with the finite element simulation results. The verification results show that the HRTM process can achieve high-quality integrated molding of the composite longitudinally and transversely stiffened panel structure. [ABSTRACT FROM AUTHOR]