River Surface Velocity Measurement for Rapid Levee Breach Emergency Response Based on DFP-P-LK Algorithm.

In recent years, the increasing frequency of climate change and extreme weather events has significantly elevated the risk of levee breaches, potentially triggering large-scale floods that threaten surrounding environments and public safety. Rapid and accurate measurement of river surface velocities is crucial for developing effective emergency response plans. Video image velocimetry has emerged as a powerful new approach due to its non-invasive nature, ease of operation, and low cost. This paper introduces the Dynamic Feature Point Pyramid Lucas-Kanade (DFP-P-LK) optical flow algorithm, which employs a feature point dynamic update fusion strategy. The algorithm ensures accurate feature point extraction and reliable tracking through feature point fusion detection and dynamic update mechanisms, enhancing the robustness of optical flow estimation. Based on the DFP-P-LK, we propose a river surface velocity measurement model for rapid levee breach emergency response. This model converts acquired optical flow motion to actual flow velocities using an optical flow-velocity conversion model, providing critical data support for levee breach emergency response. Experimental results show that the method achieves an average measurement error below 15% within the velocity range of 0.43 m/s to 2.06 m/s, demonstrating high practical value and reliability.

Guiding near-source elastic waves in a semi-infinite medium.

In this work, we propose elastic metamaterials with phase discontinuities to steer the propagation of near-source bulk waves in a semi-infinite elastic medium. Our design exploits an array of embedded subwavelength resonators with tailored masses to attain a complete phase shift spanning [Formula: see text]. This phase control allows for diverse wave functionalities, such as directional refraction and energy focusing. Through the use of dispersion diagrams and the generalized Snell's law, along with a multiple scattering formulation, we analytically demonstrate the effectiveness of our design in achieving the desired wavefront manipulation. The proposed design has the potential to advance the field of guiding elastic waves using metamaterials and find practical applications in areas such as isolating ground-borne vibrations in densely urbanized regions and energy harvesting. This article is part of the theme issue 'Current developments in elastic and acoustic metamaterials science (Part 1)'.

The contact force between lunar-based equipment and lunar soil.

Lunar-based equipment plays a vital role in the exploration of the moon because it undertakes the tasks of moving, transporting, digging, and so on. In order to control the gait of lunar-based equipment more precisely and guarantee mobile stability, the contact mechanism between its foot and lunar soil is worthy of in-depth study. In this paper, a contact model is proposed to predict the stress, strain, and displacement both on the contact surface and in the lunar soil when the foot is under vertical load. The axial stress in the proposed contact model is verified through the experiment and its accuracy in the lunar equipment is verified through simulation. The error is in a reasonable range and the influence depth of load conforms to the experiment results. This paper provides a relatively accurate model to describe the contact force between the lunar-based equipment's foot and the lunar soil and will promote the research of lunar exploration.

Single-Frequency GNSS Integer Ambiguity Solving Based on Adaptive Genetic Particle Swarm Optimization Algorithm.

Carrier phase measurements currently play a crucial role in achieving rapid and highly accurate positioning of global navigation satellite systems (GNSS). Resolving the integer ambiguity correctly is one of the key steps in this process. To address the inefficiency and slow search problem during ambiguity solving, we propose a single-frequency GNSS integer ambiguity solving based on an adaptive genetic particle swarm optimization (AGPSO) algorithm. Initially, we solve for the floating-point solution and its corresponding covariance matrix using the carrier-phase double difference equation. Subsequently, we decorrelate it using the inverse integer Cholesky algorithm. Furthermore, we introduce an improved fitness function to enhance convergence and search performance. Finally, we combine a particle swarm optimization algorithm with adaptive weights to conduct an integer ambiguity search, where each generation selectively undergoes half-random crossover and mutation operations to facilitate escaping local optima. Comparative studies against traditional algorithms and other intelligent algorithms demonstrate that the AGPSO algorithm exhibits faster convergence rates, improved stability in integer ambiguity search results, and in practical experiments the baseline accuracy of the solution is within 0.02 m, which has some application value in the practical situation of short baselines.

Research on the Improvement of Semi-Global Matching Algorithm for Binocular Vision Based on Lunar Surface Environment.

The low light conditions, abundant dust, and rocky terrain on the lunar surface pose challenges for scientific research. To effectively perceive the surrounding environment, lunar rovers are equipped with binocular cameras. In this paper, with the aim of accurately detect obstacles on the lunar surface under complex conditions, an Improved Semi-Global Matching (I-SGM) algorithm for the binocular cameras is proposed. The proposed method first carries out a cost calculation based on the improved Census transform and an adaptive window based on a connected component. Then, cost aggregation is performed using cross-based cost aggregation in the AD-Census algorithm and the initial disparity of the image is calculated via the Winner-Takes-All (WTA) strategy. Finally, disparity optimization is performed using left-right consistency detection and disparity padding. Utilizing standard test image pairs provided by the Middleburry website, the results of the test reveal that the algorithm can effectively improve the matching accuracy of the SGM algorithm, while reducing the running time of the program and enhancing noise immunity. Furthermore, when applying the I-SGM algorithm to the simulated lunar environment, the results show that the I-SGM algorithm is applicable in dim conditions on the lunar surface and can better help a lunar rover to detect obstacles during its travel.

Greenhouse gas emissions from U.S. crude oil pipeline accidents: 1968 to 2020.

Crude oil pipelines are considered as the lifelines of energy industry. However, accidents of the pipelines can lead to severe public health and environmental concerns, in which greenhouse gas (GHG) emissions, primarily methane, are frequently overlooked. While previous studies examined fugitive emissions in normal operation of crude oil pipelines, emissions resulting from accidents were typically managed separately and were therefore not included in the emission account of oil systems. To bridge this knowledge gap, we employed a bottom-up approach to conducted the first-ever inventory of GHG emissions resulting from crude oil pipeline accidents in the United States at the state level from 1968 to 2020, and leveraged Monte Carlo simulation to estimate the associated uncertainties. Our results reveal that GHG emissions from accidents in gathering pipelines (~720,000 tCO2e) exceed those from transmission pipelines (~290,000 tCO2e), although significantly more accidents have occurred in transmission pipelines (6883 cases) than gathering pipelines (773 cases). Texas accounted for over 40% of total accident-related GHG emissions nationwide. Our study contributes to enhanced accuracy of the GHG account associated with crude oil transport and implementing the data-driven climate mitigation strategies.

An inventory of greenhouse gas emissions due to natural gas pipeline incidents in the United States and Canada from 1980s to 2021.

Natural gas is believed to be a critical transitional energy source. However, natural gas pipelines, once failed, will contribute to a large amount of greenhouse gas (GHG) emissions, including methane from uncontrolled natural gas venting and carbon dioxide from flared natural gas. However, the GHG emissions caused by pipeline incidents are not included in the regular inventories, making the counted GHG amount deviate from the reality. This study, for the first time, establishes an inventory framework for GHG emissions including all natural gas pipeline incidents in the two of the largest gas producers and consumers in North America (United States and Canada) from 1980s to 2021. The inventory comprises GHG emissions resulting from gathering and transmission pipeline incidents in a total of 24 states or regions in the United States between 1970 and 2021, local distribution pipeline incidents in 22 states or regions between 1970 and 2021, as well as natural gas pipeline incidents in a total of 7 provinces or regions in Canada between 1979 and 2021. These datasets can improve the accuracy of regular emission inventories by covering more emission sources in the United States and Canada and provide essential information for climate-oriented pipeline integrity management.

An Adaptive and Robust Control Strategy for Real-Time Hybrid Simulation.

A real-time hybrid simulation (RTHS) is a promising technique to investigate a complicated or large-scale structure by dividing it into numerical and physical substructures and conducting cyber-physical tests on it. The control system design of an RTHS is a challenging topic due to the additional feedback between the physical and numerical substructures, and the complexity of the physical control plant. This paper proposes a novel RTHS control strategy by combining the theories of adaptive control and robust control, where a reformed plant which is highly simplified compared to the physical plant can be used to design the control system without compromising the control performance. The adaptation and robustness features of the control system are realized by the bounded-gain forgetting least-squares estimator and the sliding mode controller, respectively. The control strategy is validated by investigating an RTHS benchmark problem of a nonlinear three-story steel frame The proposed control strategy could simplify the control system design and does not require a precise physical plant; thus, it is an efficient and practical option for an RTHS.

[Study on UPLC fingerprint of Xiasangju Granules].

OBJECTIVE: To establish a UPLC fingerprint method of Xiasangju Granules. METHODS: UPLC analysis was performed on a Waters ACQUITY UPLC H-Class system and carried out at 30 °C on a Waters Column ACQUITY UPLC BEH C18 (2.1 mm x 50 mm, 1.7 µm). A binary gradient elution system was composed of acetonitrile (phase A)and 0.5% acetic acid solution (phase B). Detection was performed at the wavelength of 320 nm,the mobile flow rate was at 0.4 mL/min. A matrix including 16 variations (characteristic peaks area)and 12 samples was constructed for similarity evaluation, cluster analysis and principle component analysis. RESULTS: The results showed that the collected samples had a good similarity. A specificity fingerprint was produced and 16 characteristic peaks were designated. 12 samples were divided into 6 groups. CONCLUSION: It is a reliable, available and quick method for quality control of Xiasangju Granules.

[Study on HPLC fingerprint of Prunella vulgaris].

OBJECTIVE: To establish HPLC fingerprint of Prunella vulgaris and provide evidence for quality control and identification of the Chinese crude drug. METHODS: The HPLC method was used, chromatography conditions were Agilent Eclipse XDB-C18 (4.6 mm x 250 mm, 5 microm) column with gradient mobile phase of acetonitrile-0.1% acetic acid, UV detection wavelength was 290 nm and the column temperature was 30 degrees C with the flow rate of 1.0 mL/min, the sample injection was 10 microL. RESULTS: HPLC fingerprints of 19 samples of Prunella vulgaris were established. 14 common peaks were selected as the fingerprint peaks in all samples. Among the obtained fingerprints, most of the detected peaks were separated effectively. 19 samples had high similarities. CONCLUSION: The established HPLC fingerprint has desirable accuracy, repeatability and stability, which can be used for one of the quality control methods of Prunella vulgaris.

[Effects of yanlieping formula on mice with chronic nonbacterial prostatitis].

OBJECTIVES: To study the mechanism of Yanlieping Formula in treating chronic nonbacterial prostatitis. METHODS: Thirty-two C57BL/6 mice were divided into Chinese Traditional Medicine group(Yanlieping group, 10 mice), treatment control group(Cernilton group, 10 mice), model group(6 mice) and normal group(6 mice). The animal model was created by using immunologic adjuvant, and Yanlieping (0.84 g per mouse), Cernilton (7.5 mg per mouse), distilled water(1.05 ml per mouse) and distilled water (0.5 ml per mouse) were respectively administered to the four groups every day for one month. The prostate weight, pathological changes, TNF-alpha and IL-2 in serum were observed. RESULTS: The prostate weight in Yanlieping group and Cernilton group became significantly lower than in the model group(P < 0.05). Pathologic sign of chronic inflammation became better significantly(Yanlieping group showed more significant improvement). The expression of IL-2 in Yanlieping group and Cernilton group were downregulated significantly. And the expression of TNF-alpha in Yianlieping group was higher than that of the model group and the normal group (P < 0.05). CONCLUSIONS: The mechanism of Yanlieping Formula in treating chronic prostatitis may lie in the max urethral close pressure reduction, anti-inflammation, local blood circulation improvement.