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Ultra-short baseline (USBL) underwater positioning systems are widely used in marine scientific research and ocean engineering. Angle misalignment is a main error that reduces the accuracy of USBL underwater positioning. The conventional angle-calibration method assumes that the transponder position obtained by USBL positioning is an errorless coefficient matrix. However, errors inevitably exist in the estimation of the transponder’s position via USBL positioning, and the precision varies at different epochs. Ignoring the error in the transponder’s position will significantly reduce the precision of the angle misalignment estimation. In this paper, a new angle-calibration method is proposed for precise USBL underwater positioning. The angle alignment model is derived by treating the transponder’s position obtained by USBL positioning as an observation, and the stochastic model is then established according to the bearing angles. Robust estimation is likewise applied to further improve the precision of the angle misalignment estimation. To verify the performance of the proposed method, a sea experiment was performed. The results show that the new method has high calibration accuracy and robustness. The estimation precision of this method is improved by 0.0457°~0.6896° in heading, 0.0125°~0.8072° in roll, and 0.0077°~0.9436° in pitch, compared with that of the conventional angle alignment method.

The dynamic physical simulation of natural gas accumulation process is one of the important means to reveal the mechanism of natural gas migration and accumulation and to summarize its distribution law. However, due to the characteristics of natural gas itself including "easy to leak, difficult to move and difficult to observe" have become holdbacks for the physical simulation of natural gas migration and accumulation. In order to reveal the migration and accumulation mechanisms of fault-controlled gas reservoirs, and to summarize the formation sequence and distribution pattern of gas reservoirs, typical reservoirs in Dongping, Mahai and Nanbaxian areas in the northwestern part of Tarim Basin were taken as examples to establish a geological evolution model for each reservoir. Aiming at the problems of gas reservoir simulation, an adjustable simulation device for gas migration and accumulation was designed, which could realize the dynamic process of structural change and clarify the phenomenon of gas charging and migration, and the formation process of typical gas reservoirs such as Dongping, and Mahai-Nanbaxian, etc. was successfully simulated. It is clear that the fault not only acts as a channel for gas migration and power transmission, but also controls the evolution sequence and distribution pattern. The formation and evolution sequence models of two different types of natural gas reservoirs, named "late accumulation" and "long-term accumulation", were proposed, the mechanism of natural gas migration and accumulation driven by "fault transmission and high pressure" was revealed, and the vertical preservation sequence featured by "co-existence of natural gas in both deep and shallow formations, and the deeper formations are more favorable for preservation" was concluded. A new concept of natural gas exploration was put forward that "if there are shallow gas reservoirs, there must be deep ones", and we can find natural gas from shallow to deep formations.

Because the conventional Temperature Drift Error (TDE) estimation model for Capacitive MEMS Gyros (CMGs) has inadequate Temperature Correlated Quantities (TCQs) and inaccurate parameter identification to improve their bias stability, its novel model based on thermal stress deformation analysis is presented. Firstly, the TDE of the CMG is traced precisely by analyzing its structural deformation under thermal stress, and more key decisive TCQs are explored, including ambient temperature variation ∆T and its square ∆T2, as well its square root ∆T1/2; then, a novel TDE estimation model is established. Secondly, a Radial Basis Function Neural Network (RBFNN) is applied to identify its parameter accurately, which eliminates local optimums of the conventional model based on a Back-Propagation Neural Network (BPNN) to improve bias stability. By analyzing heat conduction between CMGs and the thermal chamber with heat flux analysis, proper temperature control intervals and reasonable temperature control periods are obtained to form a TDE precise test method to avoid time-consuming and expensive experiments. The novel model is implemented with an adequate TCQ and RBFNN, and the Mean Square Deviation (MSD) is introduced to evaluate its performance. Finally, the conventional model and novel model are compared with bias stability. Compared with the conventional model, the novel one improves CMG’s bias stability by 15% evenly. It estimates TDE more precisely to decouple Si-based materials’ temperature dependence effectively, and CMG’s environmental adaptability is enhanced to widen its application under complex conditions.

It has important theoretical and practical significance to clarify the causes and distribution of oil and gas. This paper focused on the key scientific issues in the current petroleum genesis research, guided by the general principles of global tectonics and petroleum geology. Various petroleum genesis hypotheses have been sorted out, merged, integrated and innovated, thus a hypothesis framework of organic-inorganic coupling causes for petroleum was introduced. The main factors are that oil (including natural gas) is a renewable resource with multiple origins and has huge reserves. The formation and distribution of petroleum is the result of the coupling of four pairs of hydrocarbon-forming factors, including basin and mantle uplift, deep and shallow fluids, organic and inorganic hydrocarbon generation mechanisms, deep faults and sealing conditions. The higher degree of organic-inorganic cause coupling indicates the richer the oil and gas. The basin and the area below its basement are the locations with the best degree of coupling, followed by the deep and large fault development areas with good sealing conditions in the surrounding areas of the basin. The matching of deep and large faults with sealing conditions is an important factor constraining hydrocarbon accumulation. Large-scale traps with good sealing conditions in long-term, multi-period or recent active deep and large fault development areas are the most favorable targets for major exploration successes.

Since the traditional real-time kinematic positioning method is limited by the reduced satellite visibility from the deprived navigational environments, we, therefore, propose an improved RTK method with multiple rover receivers sharing a common clock. The proposed method can enhance observational redundancy by blending the observations from each rover receiver together so that the model strength will be improved. Integer ambiguity resolution of the proposed method is challenged in the presence of several inter-receiver biases (IRB). The IRB including inter-receiver code bias (IRCB) and inter-receiver phase bias (IRPB) is calibrated by the pre-estimation method because of their temporal stability. Multiple BeiDou Navigation Satellite System (BDS) dual-frequency datasets are collected to test the proposed method. The experimental results have shown that the IRCB and IRPB under the common clock mode are sufficiently stable for the ambiguity resolution. Compared with the traditional method, the ambiguity resolution success rate and positioning accuracy of the proposed method can be improved by 19.5% and 46.4% in the restricted satellite visibility environments.

Based on the statistical stability of the inter-system bias (ISB), we propose a tightly coupled Differential Global Navigation Satellite System (DGNSS) positioning method by using ionosphere-free combination for the long baseline applications. The proposed method is compatible with the traditional Radio Beacon (RBN) base station implementation. The tightly coupled DGNSS positioning method is utilized at the long baseline rover by eliminating the effect of ionosphere delay with ionosphere-free (IF) based differential ISB calibration. The improved positioning model strength can be obtained with the proposed method when compared with the traditional loosely coupled method, particularly under the satellite-deprived environment. GNSS datasets of different baselines were collected to test the proposed method. The results of the ISB stability show that the ISB has long-term stability and needs to be calibrated when the receiver is rebooted. The positioning results show that when compared with the IF-based loosely coupled method, the IF-based tightly coupled DGNSS method based on ISB calibration can obtain better positioning performance of accuracy and continuity within 240 km baselines.

Continuity, real-time, and accuracy are the key technical indexes of evaluating comprehensive performance of a strapdown inertial navigation system (SINS). However, Schuler, Foucault, and Earth periodic oscillation errors significantly cut down the real-time accuracy of SINS. A method for oscillation error restriction of SINS based on forecasted time series is proposed by analyzing the characteristics of periodic oscillation errors. The innovative method gains multiple sets of navigation solutions with different phase delays in virtue of the forecasted time series acquired through the measurement data of the inertial measurement unit (IMU). With the help of curve-fitting based on least square method, the forecasted time series is obtained while distinguishing and removing small angular motion interference in the process of initial alignment. Finally, the periodic oscillation errors are restricted on account of the principle of eliminating the periodic oscillation signal with a half-wave delay by mean value. Simulation and test results show that the method has good performance in restricting the Schuler, Foucault, and Earth oscillation errors of SINS.

The stationary reference receiver with precisely known coordinates is difficult to establish in some special real-time relative positioning applications. To improve the relative position estimation accuracy and the reliability simultaneously for the RTK without a precisely known reference receiver, multiple receivers mounted on a moving platform are used as the base station. A code and phase measurement fusion model is proposed to reduce the communication burden and generate measurements at any virtual position where it is inconvenient to install the GPS receiver. To keep the integer property of the ambiguity of fused phase measurements, the RTK method with the moving reference receivers is proposed by implementing the integer ambiguity transformation and error absorption strategy based on the known geometry of multiple receivers. Static and kinematic experiments were carried out to evaluate the performance of the proposed relative positioning method. When compared with the single-receiver solution, static results have shown that the proposed method can improve position accuracy by 15.9% and 15.7% for the horizontal and the vertical component, respectively. The kinematic results have shown that the proposed method can achieve position accuracy enhancement by 26.9% for the vertical component.

This study focuses on mitigating the multipath, especially the short-delay multipath of the BeiDou navigation satellite system under impulsive noise conditions. A modified least mean p-norm (LMP) algorithm is developed to reduce the convergence time with the same steady-state error by predicting the updating trend of weights. The modified normalized power and the normalized polynomial least mean pth power are also directly provided according to a similar principle. According to the research work, an average filter has been utilized to improve the processing gain of designed mitigation scheme. Some significant simulation results verified the performance of the proposed adaption algorithm. Multipath parameter estimation tests have been conducted under different noise levels. Some comparative statistics performance assessments are quantified and verified under impulsive and additional white Gaussian noise environments. Results with various window widths of the average filtering and carrier-to-noise ratios indicate that the proposed scheme is able to improve the performance of the short-delay multipath mitigation under normal and degraded environments.

The ionospheric bias and the combined observation noise are two crucial factors affecting the reliability of the triple-carrier ambiguity resolution (TCAR). In order to obtain a better reliability of TCAR, a new ionosphere-free and variance-restricted TCAR method is proposed through exploring the ambiguity link between each step of TCAR. The method constructs an ionosphere-free combination and simultaneously restricts the combined observation noise with respect to the wavelength to a sufficiently low level for each step of TCAR. The performance of the proposed method is tested by the datasets from the BeiDou navigation satellite system (BDS), with the baseline varying from 7.7 km to 68.8 km. Comparing with the state-of-the-art TCAR methods, the experimental results indicate that the proposed method can obtain a better performance of ambiguity resolution, even though the double-differenced ionospheric delay increases up to 72.4 cm at the baseline of 68.8 km.

Real-time single frequency precise point positioning (PPP) is a promising technique for high-precision navigation with sub-meter or even centimeter-level accuracy because of its convenience and low cost. The navigation performance of single frequency PPP heavily depends on the real-time availability and quality of correction products for satellite orbits and satellite clocks. Satellite-based augmentation system (SBAS) provides the correction products in real-time, but they are intended to be used for wide area differential positioning at 1 meter level precision. By imposing the constraints for ionosphere error, we have developed a real-time single frequency PPP method by sufficiently utilizing SBAS correction products. The proposed PPP method are tested with static and kinematic data, respectively. The static experimental results show that the position accuracy of the proposed PPP method can reach decimeter level, and achieve an improvement of at least 30% when compared with the traditional SBAS method. The positioning convergence of the proposed PPP method can be achieved in 636 epochs at most in static mode. In the kinematic experiment, the position accuracy of the proposed PPP method can be improved by at least 20 cm relative to the SBAS method. Furthermore, it has revealed that the proposed PPP method can achieve decimeter level convergence within 500 s in the kinematic mode.

Aim: We aimed to explore whether the combination of CLP290 and bumetanide maximally improves neuropathic pain following spinal cord injury (SCI) and its possible molecular mechanism. Methods: Rats were randomly divided into five groups: Sham, SCI + vehicle, SCI + CLP290, SCI + bumetanide, and SCI + combination (CLP290 + bumetanide). Drug administration commenced on the 7th day post‐injury (7 dpi) and continued for 14 days. All rats underwent behavioral assessments for 56 days to comprehensively evaluate the effects of interventions on mechanical pain, thermal pain, cold pain, motor function, and other relevant parameters. Electrophysiological assessments, immunoblotting, and immunofluorescence detection were performed at different timepoints post‐injury, with a specific focus on the expression and changes of KCC2 and NKCC1 proteins in the lumbar enlargement of the spinal cord. Results: CLP290 and bumetanide alleviated SCI‐associated hypersensitivity and locomotor function, with the combination providing enhanced recovery. The combined treatment group exhibited the most significant improvement in restoring Rate‐Dependent Depression (RDD) levels. In the combined treatment group and the two individual drug administration groups, the upregulation of potassium chloride cotransporter 2 (K+‐Cl−cotransporter 2, KCC2) expression and downregulation of sodium potassium chloride cotransporter 1 (Na+‐K+‐Cl−cotransporter 1, NKCC1) expression in the lumbar enlargement area resulted in a significant increase in the KCC2/NKCC1 ratio compared to the SCI + vehicle group, with the most pronounced improvement seen in the combined treatment group. Compared to the SCI + vehicle group, the SCI + bumetanide group showed no significant paw withdrawal thermal latency (PWTL) improvement at 21 and 35 dpi, but a notable enhancement at 56 dpi. In contrast, the SCI + CLP290 group significantly improved PWTL at 21 days, with non‐significant changes at 35 and 56 days. At 21 dpi, KCC2 expression was marginally higher in monotherapy groups versus SCI + vehicle, but not significantly. At 56 dpi, only the SCI + bumetanide group showed a significant difference in KCC2 expression compared to the control group. Conclusion: Combined application of CLP290 and bumetanide effectively increases the ratio of KCC2/NKCC1, restores RDD levels, enhances GABAA receptor‐mediated inhibitory function in the spinal cord, and relieves neuropathic pain in SCI; Bumetanide significantly improves neuropathic pain in the long term, whereas CLP290 demonstrates a notable short‐term effect. [ABSTRACT FROM AUTHOR]

Sugarcane, a vital cash crop, contributes significantly to the world's sugar supply and raw materials for biofuel production, playing a significant role in the global sugar industry. However, sustainable productivity is severely hampered by biotic and abiotic stressors. Genetic engineering has been used to transfer useful genes into sugarcane plants to improve desirable traits and has emerged as a basic and applied research method to maintain growth and productivity under different adverse environmental conditions. However, the use of transgenic approaches remains contentious and requires rigorous experimental methods to address biosafety challenges. Clustered regularly interspaced short palindromic repeat (CRISPR) mediated genome editing technology is growing rapidly and may revolutionize sugarcane production. This review aims to explore innovative genetic engineering techniques and their successful application in developing sugarcane cultivars with enhanced resistance to biotic and abiotic stresses to produce superior sugarcane cultivars. [ABSTRACT FROM AUTHOR]

Spinal cord injury (SCI) results in a large amount of tissue cell debris in the lesion site, which interacts with various cytokines, including inflammatory factors, and the intrinsic glial environment of the central nervous system(CNS) to forman inhibitory microenvironment that impedes nerve regeneration. The efficient clearance of tissue debris is crucial for the resolution of the inhibitory microenvironment after SCI. Macrophages are themain cells responsible for tissue debris removal after SCI. However, the high lipid content in tissue debris and the dysregulation of lipid metabolism within macrophages lead to their transformation into foamy macrophages during the phagocytic process. This phenotypic shift is associated with a further pro-inflammatory polarization that may aggravate neurological deterioration and hamper nerve repair. In this review, we summarize the phenotype and metabolism of macrophages under inflammatory conditions, as well as the mechanisms and consequences of foam cell formation after SCI. Moreover, we discuss two strategies for foamcell modulation and several potential therapeutic targets that may enhance the treatment of SCI. [ABSTRACT FROM AUTHOR]

Background: Systemic inflammation and glucose metabolism have been closely related to the survival of cancer patients. Therefore, we aimed to evaluate whether preoperative glucose-to-lymphocyte ratio (GLR) can be used to predict the survival of cancer patients. Methods: We retrospectively examined 2172 cancer patients who underwent surgery from January 1, 2014, to December 31, 2016. There were 240 patients with non-small cell lung cancer (NSCLC), 378 patients with colorectal cancer (CRC), 221 patients with breast cancer (BC), 335 patients with gastric cancer (GC), 270 patients with liver cancer, 233 patients with esophageal cancer (EC), 295 patients with renal cancer, and 200 patients with melanoma. The formula for preoperative GLR calculation was as follows: GLR=glucose/lymphocyte count. The overall survival (OS) was estimated using the Kaplan-Meier method. The predictive factors for OS were determined using multivariate analysis. Results: The Kaplan-Meier analysis showed that the median survival time in the high-GLR group was much shorter than that of those in the low-GLR group for different cancers. Cox multivariate regression analysis reveals that preoperative GLR was an independent factor for predicting overall survival in different tumor types. Conclusion: Elevated preoperative GLR was remarkably associated with a poorer prognosis in patients with NSCLC, CRC, breast cancer, gastric cancer, kidney cancer, liver cancer, esophageal cancer, and melanoma. Preoperative GLR promises to be an essential predictor of survival for cancer patients. [ABSTRACT FROM AUTHOR]