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Salt-induced erosion from de-icing salts in Northern China and sea salt in Eastern coastal areas significantly compromises asphalt pavement integrity. A selection was made of four different types of foamed asphalt with different levels of water content, two types of aged asphalt, and three typical minerals (α-quartz, calcite, and bauxite), in addition to three chloride salt solutions (NaCl, CaCl2, MgCl2). It was found that (1) in dry conditions, the moisture level of foamed asphalt noticeably influences the adhesive performance at the juncture between asphalt and aggregates. Unlike acidic minerals, the bond strength between alkaline and neutral minerals and foamed asphalt increases as the water content of the foamed asphalt rises; (2) chloride salt solutions presence and increased levels significantly reduced the bond strength between asphalt and aggregates, particularly impacting neutral and alkaline minerals (in the presence of 10 % NaCl solution, the work of adhesion was reduced by 83.82 % and 87.48 %, respectively); (3) the influence of diverse chloride salts on the interfacial adhesive performance of asphalt mixtures varied, with the three chloride salts reducing the asphalt-aggregate interfacial adhesion work by 44.52 %, 21.90 %, and 34.94 %, respectively. (4) the investigation determined that the mineral composition considerably influences the hygroscopic sensitivity of asphalt mixtures. Minerals of an acidic nature exhibit superior moisture resistance when juxtaposed with alkaline counterparts, recommending the adoption of acidic aggregates in scenarios demanding elevated mixture stability.

Abstract Throughout the history of coal mining in all countries of the world, large areas of goaf have been left behind, and sudden collapses and surface subsidence of large areas of goaf may occur, especially for mining areas with long mining cycles. The northern new district of the Liaoyuan mining area has been subjected to nearly half a century of mining activities, accompanied by a gradual accumulation of disasters, which have occurred frequently in recent years. In order to assess the stability of the goaf in the study area, this paper proposes a hybrid decision-making multi-factor integrated evaluation method. The distribution of underground goafs was determined using geophysical exploration techniques (seismic survey and transient electromagnetic method) and geological drilling exploration. First, an evaluation index system was established based on the specifications of the goaf, the ecological and geological environment, and the mining conditions; the system included 14 indicators. Two weight calculation methods, AHP-EWM, were employed to determine the comprehensive weight of each indicator by combining subjective and objective weights on the basis of improved game theory. Subsequently, the fuzzy comprehensive evaluation method was utilised to complete the stability rating of each block in the study area, and MapGIS and ArcGIS were employed to complete the drawing of the stability zoning map of the northern new district goaf. The study area was divided into three zones of stability, basic stability and instability, according to the critical value. These zones accounted for 23.03%, 36.45% and 40.52% of the total area of the study area, respectively. The comprehensive on-site investigation revealed a decrease in the size and number of collapse pits and the rate of damage to the houses from the unstable zone to the stable zone. This indicates that the results of the division are consistent with the actual situation. The classification results are consistent with the actual ground disaster situation, thus verifying the rationality and validity of the evaluation method. The results indicate that the stability of the study area is generally at the lower middle level.

Accidents caused by vehicles changing lanes occur frequently on highways. Moreover, frequent lane changes can severely impact traffic flow during peak commuting hours and on busy roads. A novel framework based on a multi-relational graph convolutional network (MR-GCN) is herein proposed to address these challenges. First, a dynamic multilevel relational graph was designed to describe interactions between vehicles and road objects at different spatio-temporal granularities, with real-time updates to edge weights to enhance understanding of complex traffic scenarios. Second, an improved spatio-temporal interaction graph generation method was introduced, focusing on spatio-temporal variations and capturing complex interaction patterns to enhance prediction accuracy and adaptability. Finally, by integrating a dynamic multi-relational graph convolutional network (DMR-GCN) with dynamic scene sensing and interaction learning mechanisms, the framework enables real-time updates of complex vehicle relationships, thereby improving behavior prediction’s accuracy and real-time performance. Experimental validation on multiple benchmark datasets, including KITTI, Apollo, and Indian, showed that our algorithmic framework achieves significant performance improvements in vehicle behavior prediction tasks, with Map, Recall, and F1 scores reaching 90%, 88%, and 89%, respectively, outperforming existing algorithms. Additionally, the model achieved a Map of 91%, a Recall of 89%, and an F1 score of 90% under congested road conditions in a self-collected high-speed traffic scenario dataset, further demonstrating its robustness and adaptability in high-speed traffic conditions. These results show that the proposed model is highly practical and stable in real-world applications such as traffic control systems and self-driving vehicles, providing strong support for efficient vehicle behavior prediction.

In intelligent traffic monitoring systems, the significant distance between cameras and their non-overlapping fields of view leads to several issues. These include incomplete tracking results from individual cameras, difficulty in matching targets across multiple cameras, and the complexity of inferring the global trajectory of a target. In response to the challenges above, a deep learning-based vehicle tracking algorithm called FairMOT-MCVT is proposed. This algorithm con-siders the vehicles’ characteristics as rigid targets from a roadside perspective. Firstly, a Block-Efficient module is designed to enhance the network’s ability to capture and characterize image features across different layers by integrating a multi-branch structure and depth-separable convolutions. Secondly, the Multi-scale Dilated Attention (MSDA) module is introduced to improve the feature extraction capability and computational efficiency by combining multi-scale feature fusion and attention mechanisms. Finally, a joint loss function is crafted to better distinguish between vehicles with similar appearances by combining the trajectory smoothing loss and velocity consistency loss, thereby considering both position and velocity continuity during the optimization process. The proposed method was evaluated on the public UA-DETRAC dataset, which comprises 1210 video sequences and over 140,000 frames captured under various weather and lighting conditions. The experimental results demonstrate that the FairMOT-MCVT algorithm significantly enhances multi-target tracking accuracy (MOTA) to 79.0, IDF1 to 84.5, and FPS to 29.03, surpassing the performance of previous algorithms. Additionally, this algorithm expands the detection range and reduces the deployment cost of roadside equipment, effectively meeting the practical application requirements.

The yellowfin tuna represents a significant fishery resource in the Pacific Ocean. Its resource endowment status and spatial variation mechanisms are intricately influenced by marine environments, particularly under varying climate events. Consequently, investigating the spatial variation patterns of dominant environmental factors under diverse climate conditions, and understanding the response of yellowfin tuna catch volume based on the spatial heterogeneity among these environmental factors, presents a formidable challenge. This paper utilizes comprehensive 5°×5° yellowfin tuna longline fishing data and environmental data, including seawater temperature and salinity, published by the Western and Central Pacific Fisheries Commission (WCPFC) and the Inter-American Tropical Tuna Commission (IATTC) for the period 2000–2021 in the Pacific Ocean. In conjunction with the Niño index, a multiscale geographically weighted regression model based on geographically weighted principal component analysis (GWPCA-MGWR) and spatial association between zones (SABZ) is employed for this study. The results indicate the following: (1) The spatial distribution of dominant environmental factors affecting the catch of Pacific yellowfin tuna is primarily divided into two types: seawater temperature dominates in the western Pacific Ocean, while salinity dominates in the eastern Pacific Ocean. When El Niño occurs, the area with seawater temperature as the dominant environmental factor in the western Pacific Ocean further extends eastward, and the water layers where the dominant environmental factors are located develop to deeper depths; when La Niña occurs, there is a clear westward expansion in the area with seawater salinity as the dominant factor in the eastern Pacific Ocean. This change in the spatial distribution pattern of dominant factors is closely related to the movement of the position of the warm pool and cold tongue under ENSO events. (2) The areas with a higher catch of Pacific yellowfin tuna are spatially associated with the dominant environmental factor of mid-deep seawater temperature (105–155 m temperature) to a greater extent than other factors, the highest correlation exceeds 70%, and remain relatively stable under different ENSO events. The formation of this spatial association pattern is related to the vertical movement of yellowfin tuna as affected by subsurface seawater temperature. (3) The GWPCA-MGWR model can fully capture the differences in environmental variability among subregions in the Pacific Ocean under different climatic backgrounds, intuitively reflect the changing areas and influencing boundaries from a macro perspective, and has a relatively accurate prediction on the trend of yellowfin tuna catch in the Pacific Ocean.

Abstract The electrolyte solvation structure and the solid-electrolyte interphase (SEI) formation are critical to dictate the morphology of lithium deposition in organic electrolytes. However, the link between the electrolyte solvation structure and SEI composition and its implications on lithium morphology evolution are poorly understood. Herein, we use a single-salt and single-solvent model electrolyte system to systematically study the correlation between the electrolyte solvation structure, SEI formation process and lithium deposition morphology. The mechanism of lithium deposition is thoroughly investigated using cryo-electron microscopy characterizations and computational simulations. It is observed that, in the high concentration electrolytes, concentrated Li+ and anion-dominated solvation structure initiate the uniform Li nucleation kinetically and favor the decomposition of anions rather than solvents, resulting in inorganic-rich amorphous SEI with high interface energy, which thermodynamically facilitates the formation of granular Li. On the contrary, solvent-dominated solvation structure in the low concentration electrolytes tends to exacerbate the solvolysis process, forming organic-rich mosaic SEI with low interface energy, which leads to aggregated whisker-like nucleation and growth. These results are helpful to tackle the long-standing question on the origin of lithium dendrite formation and guide the rational design of high-performance electrolytes for advanced lithium metal batteries.

Abstract Aim Current study was to evaluate relationship between baseline serum lipoprotein (a) [Lp(a)] level and prognosis in patients with heart failure with reduced ejection fraction (HFrEF) and to explore whether the relationship would be modified by baseline high‐sensitivity C‐reactive protein (Hs‐CRP) level. Methods and results This is an observational prospective study. HFrEF patients from outpatient clinic were consecutively recruited (n = 362). Based on Lp(a) cutoff (30 mg/dL), patients were divided into normal and high Lp(a) groups; and based on Hs‐CRP cutoff (3 mg/dL), patients were divided into low‐degree and high‐degree groups. The 1 year rate of HF rehospitalization was similar between these two groups (22.7% vs. 24.1%, P = 0.18), while the 1 year rate of cardiovascular mortality was higher in Lp(a) ≥ 30 mg/dL versus Lp(a)

Abstract Background Hypertension is known as a major factor for global mortality. We aimed to investigate the role of Cullin3 (CUL3) in the regulation of hypertension. Material and methods Human vascular smooth muscle cells (VSMCs) were treated with Angiotensin II (Ang II) to establish a hypertension in vitro model. Cell viability was detected by a cell counting kit-8 (CCK-8) assay. The content of reactive oxygen species (ROS) was evaluated by kit. Transwell assay and TUNEL staining were, respectively, used to assess cell migration and apoptosis. Additionally, the expression of sonic hedgehog (SHH) signaling-related proteins (SHH, smoothened homolog (Smo) and glioblastoma (Gli)) and CUL3 was tested with western blotting. Following treatment with Cyclopamine (Cycl), an inhibitor of SHH signaling, in Ang II-induced VSMCs, cell viability, migration, apoptosis and ROS content were determined again. Then, VSMCs were transfected with CUL3 plasmid or/and treated with sonic hedgehog signaling agonist (SAG) to explore the impacts on Ang II-induced VSMCs damage. In vivo, a hypertensive mouse model was established. Systolic blood pressure and diastolic blood pressure were determined. The histopathologic changes of abdominal aortic tissues were examined using H&E staining. The expression of SHH, Smo, Gli and CUL3 was tested with western blotting. Results Significantly increased proliferation, migration and apoptosis of VSMCs were observed after Ang II exposure. Moreover, Ang II induced upregulated SHH, Smo and Gli expression, whereas limited increase in CUL3 expression was observed. The content of ROS in Ang II-stimulated VSMCs presented the same results. Following Cycl treatment, the high levels of proliferation and migration in Ang II-treated VSMCs were notably remedied while the apoptosis and ROS concentration were further increased. Moreover, Cycl downregulated SHH, Smo, Gli and CUL3 expression. Above-mentioned changes caused by Ang II were reversed following SAG addition. Indeed, SAG treatment combined with restoration of CUL3 expression inhibited proliferation, migration, apoptosis and ROS level in Ang II-stimulated VSMCs. In vivo, SAG aggravated the histopathological changes of the aorta and with a worse tendency after both SAG intervention and CUL3 silencing. By contrast, SAG treatment and rebound in CUL3 expression alleviated the vascular damage. Conclusions Collectively, restoration of CUL3 gene expression protected against hypertension through enhancing the effects of SHH activation in inhibition of apoptosis and oxidative stress for hypertension and alleviating the dysfunction of VSMCs.

The global navigation satellite system (GNSS) wave buoys currently in use can measure ocean surface waves but have major drawbacks regarding their real-time high-precision application due to the communication burden and high differential correction service costs; these issues have heavily limited the large-scale deployment of GNSS wave buoys globally. In this work, we propose a global real-time low-cost centimeter-level precise wave measurement method using onboard GNSS variometric velocities and segment wave parameter retrievals. The proposed novel method can achieve buoy velocities with millimeter-level accuracies using freely available broadcast ephemerides and clocks. In addition, surface wave parameters can be accurately retrieved online in real time at a GNSS variometric sampling rate of 2.5 Hz or above. The variometric approach retrieved significant wave height and mean wave period differences of 3.4 cm and 0.16 s, respectively, compared to those measured by the classical Datawell wave buoy, reaching the performance of precise point positioning results that can be obtained using precise ephemerides and clocks. In addition, the proposed method markedly outperformed the Doppler approach, especially in terms of the buoy velocity accuracy and displacement determination. The proposed GNSS variometric approach has promising application potential in real-time precise surface wave measurement applications at remarkably low costs, thus strongly supporting global ocean observations.

The role that underwater image translation plays assists in generating rare images for marine applications. However, such translation tasks are still challenging due to data lacking, insufficient feature extraction ability, and the loss of content details. To address these issues, we propose a novel multi-scale image translation model based on style-independent discriminators and attention modules (SID-AM-MSITM), which learns the mapping relationship between two unpaired images for translation. We introduce Convolution Block Attention Modules (CBAM) to the generators and discriminators of SID-AM-MSITM to improve its feature extraction ability. Moreover, we construct style-independent discriminators that enable the discriminant results of SID-AM-MSITM to be not affected by the style of images and retain content details. Through ablation experiments and comparative experiments, we demonstrate that attention modules and style-independent discriminators are introduced reasonably and SID-AM-MSITM performs better than multiple baseline methods.

Drug addiction is a serious problem globally, recently exacerbated by the COVID-19 pandemic. Glial cell-derived neurotrophic factor (GDNF) is considered a potentially effective strategy for the treatment of addiction. Previous animal experiments have proven that GDNF has a good therapeutic effect on drug addiction, but its clinical application is limited due to its poor blood-brain barrier (BBB) permeability. Low-frequency focused ultrasound, combined with microbubbles, is a non-invasive and reversible technique for locally-targeted BBB opening. In the present study, magnetic resonance imaging-guided low-frequency focused ultrasound, combined with GDNF microbubbles, was used to target BBB opening in the ventral tegmental area (VTA) region. The effects of GDNF on morphine-induced conditioned place preference (CPP) and acute withdrawal symptoms in rats after a partially opened BBB were evaluated by behavioral observation. Western blot was used to detect changes in tyrosine hydroxylase (TH) expression levels in the VTA region after different treatments, and high performance liquid chromatography was used to detect the changes in monoamine neurotransmitter content. The results showed that ultrasound combined with GDNF microbubbles targeted and opened the BBB in the VTA region, and significantly increased GDNF content, destroyed morphine-induced CPP, and reduced the withdrawal symptoms of morphine addiction in rats. Furthermore, the up-regulation of TH expression and the increase of norepinephrine and dopamine content induced by morphine were significantly reversed, and the increase of 5-hydroxytryptamine content was partially reversed. Therefore, ultrasound combined with GDNF microbubbles to target and open the BBB can effectively increase the content of central GDNF, thus playing a therapeutic role in morphine addiction. Our study provides a new approach to locally open the BBB and target delivery of neurotrophic factors, such as GDNF, to treat brain diseases like addiction.

In recent years, studies have shown a close relationship between cardiomyocyte death and ferroptosis. Clioquinol (CQ) can inhibit ferroptosis. Porous lipid-poly (lactic-co-glycolic acid) (PLGA) microbubbles (MBs) were prepared by double emulsification (W1/O/W2) using 1,2-dioctadecanoyl-sn-glycero-3-phophocholine and PLGA as raw materials. Porous lipid-PLGA MBs were used as carriers to prepare CQ/PLGA MBs containing CQ. CQ/PLGA had the advantages of high drug loading, good biocompatibility, and sustained release. Our results showed that CQ/PLGA improved the effect of CQ and reduced its cytotoxicity. Under low-frequency ultrasound with certain parameters, CQ/PLGA showed steady-state cavitation, which increased the membrane permeability of mouse cardiomyocyte HL-1 to a certain extent and further prevented the process of ferroptosis in mouse cardiomyocyte HL-1.

Background & Aims: Hepatic encephalopathy (HE) is a major complication after transjugular intrahepatic portosystemic shunt (TIPS) and is primarily influenced by the gut microbiota. We aimed to evaluate alterations in the microbiota after TIPS and the association between such alterations and HE. Methods: We conducted a prospective longitudinal study of 106 patients with cirrhosis receiving TIPS. Faecal samples were collected before and after TIPS, and the gut microbiota was analysed by 16S ribosomal RNA sequencing. Results: Among all patients, 33 developed HE (HE+ group) within 6 months after TIPS and 73 did not (HE- group), and 18 died during follow-up. After TIPS, the autochthonous taxa increased, whereas the potential pathogenic taxa decreased in the HE- group, and the autochthonous taxon Lachnospiraceae decreased in the HE+ group. Furthermore, synergism among harmful bacteria was observed in all patients, which was weakened in the HE- group (p

Downstream fining of riverbed gravels is generally linked with the processes of hydraulic sorting and abrasion. Hydraulic sorting is when larger gravel clasts stop moving in response to decreasing flow energy, whereas, finer grains will continue to be carried downstream. Furthermore, transportation of gravel clasts causes abrasion, bringing about a gradual decrease in grain size. Hydraulic sorting and abrasion have different dominant effects on the downstream fining of clasts in rivers with different climatic and tectonic backgrounds. At present, most studies focus on humid areas, and relatively few studies have explored this issue for the northeastern margin of the Tibetan Plateau in arid and semi-arid areas. Detailed investigations of the grain size, lithology, and roundness of riverbed gravels have been performed here along the Taolai, Hongshuiba, and Fengle Rivers, which flow across the northeastern margin of the Tibetan Plateau and debouch into the arid inland of North China. The obtained data were subsequently employed in a hydraulic pattern of grain-size distribution of riverbed gravels in this area, which is characterized by the combined influences of tectonic activity and climatic aridity. Analysis reveals that there is no new rock type appearing in the lithological compositions of riverbed gravels along these rivers, only showing fluctuations in proportions of lithology even though they are adjacent to uplifting mountains. Fresh gravel material from these mountains does indeed mix into the fluvial bedload, inducing a notable decrease in roundness in the Taolai and Hongshuiba bedloads downstream from here. The downstream fining of gravel along the three rivers, with median grain sizes above 128 mm and falling into the range from 20 to 128 mm, can probably be attributed to hydraulic sorting and abrasion. Further analysis suggests that the former presents a high correlation with channel gradient, which may be sustained by fault activity at the northeastern margin of the Tibetan Plateau. The grain-size distribution in these riverbed gravels thus provides insights into the evaluation of fluvial responses to active tectonic uplift.

Summary: Organic–inorganic hybrid perovskite nanoplatelets (NPLs) have emerged as promising materials for solar energy. However, the structural instability under electron beam hinders further probing and understanding of its crystalline structures and defects at the atomic scale. Taking methylammonium bromide perovskite methylammonium lead bromide (CH3NH3PbBr3 (MAPbBr3)) perovskite NPLs as model material, we performed atomic-scale characterization of the native state of the hybrid perovskite solar cell material in different states using ultra-low-dose cryo-TEM imaging. With a series of observation at different growth time, we revealed the growth pattern of such MAPbBr3 material from an initially stacked slices with rotational moiré fringes to a perfect single-crystalline structure of NPLs. Our high-resolution cryo-TEM further enabled the atomic-scale investigations of solid electrolyte interphase (SEI) and sodium (Na) dendrite materials, which can largely impact the safety and life of batteries. This study offers insights on the atomic scale characterization of a wide variety of beam-sensitive materials, inspiring us to probe more materials with cryo-transmission electron microscopes (TEM).

In this paper, a new distributed fiber optic sensor system based on dual sensing directions by polarization optical time-domain reflectometer (POTDR) is proposed. Using a single POTDR scheme, the system is able to detect signals in the forward direction and backward direction simultaneously. It can detect more perturbations applied on the fiber simultaneously than a traditional POTDR. It can also improve the positioning accuracy of POTDR by judging the perturbations from both directions. The proposed method is cost effective and has good potential in the application of intrusion monitoring.

The ultra-rapid satellite clock product based on the satellite clock batch estimation is commonly used for high-precision and reliable precise point positioning (PPP) services. In order to clarify the effect of different ranging errors on the satellite clock batch estimation accuracy, the source of the satellite clock bias induced by the batch observation model is classified into the initial clock bias (ICB) and time-dependent bias (TDB). In addition to the effect of the ICB and TDB, the analytic relationship between the observation redundancy and the satellite clock batch estimation accuracy are derived and verified. The suitable number of stations is suggested to be 40 for the satellite clock batch estimation to achieve the counterbalance between the efficiency and saturable accuracy. For the PPP based on the batch-estimated satellite clock, the impacts of the ICB and TDB on PPP are clarified. The satellite clock batch estimation and PPP experiments are carried out to investigate the impacts of the ICB and TDB on the satellite clock batch estimation accuracy and the PPP performance. The ICB causes a significant bias for the batch-estimated satellite clock. The TDB is impacted by the assimilation ability of the batch-estimated satellite clock to the satellite orbit error. The convergence time and the positioning accuracy after the convergence of PPP are primarily affected by the ICB and TDB, respectively.

Self-alignment of strapdown inertial navigation systems incorporating micro-electro-mechanical systems (MSINS) is a great challenge for marine applications. In this paper, a self-alignment method for a rotating MEMS strapdown compass is proposed with the aim of solving this problem. First, based on an analysis of biaxial rotation modulation and initial alignment of the strapdown compass, a self-alignment method is presented and verified. Second, by analyzing the effects of biaxial rotation modulation, the proposed method is improved by speeding up the rotation and reducing the stop time of the biaxial rotation mechanism to shorten the initial alignment time, which effectively suppresses the influence of MEMS noise on the initial alignment error angle. The influence of ship swinging on the initial alignment error angle is also analyzed. The efficiency of the method is verified by experiments on a swinging base. Finally, a parameter adjustment approach is presented that allows the proposed method to be used with different types of MEMS. This approach is validated by experiments. All the experimental results demonstrate the efficiency and precision of the proposed method.

The construction of underwater geodetic networks (UGN) is crucial in marine geodesy. To provide high-precision kinematic positioning for underwater submersibles, an underwater acoustic geodetic network configuration of three seafloor base stations, one subsurface buoy, and one sea surface buoy is proposed. The simulation results show that, for a 3 km-deep sea, based on the proposed UGN, the submersible positioning range and positioning accuracy are primarily affected by the size of the seafloor base station array, while the height of the subsurface buoy has a greater impact on the submersible positioning accuracy than the positioning range. Considering current acoustic ranging technology, the kinematic positioning performance of the UGN is optimal when the seafloor base stations are 9~13 km apart and the subsurface buoy is less than 2.5 km above the seafloor, which can achieve a submersible positioning accuracy of less than 30 m within an underwater space of 25 km × 25 km × 3 km. The proposed cost-effective UGN configuration can provide high-precision submersible kinematic positioning performance for seafloor surveying and ocean precision engineering. The impact of the underwater environment on the acoustic transmission characteristics should be further investigated.

The periodic noise exists in BeiDou navigation satellite system (BDS) clock offsets. As a commonly used satellite clock prediction model, the spectral analysis model (SAM) typically detects and identifies the periodic terms by the Fast Fourier transform (FFT) according to long-term clock offset series. The FFT makes an aggregate assessment in frequency domain but cannot characterize the periodic noise in a time domain. Due to space environment changes, temperature variations, and various disturbances, the periodic noise is time-varying, and the spectral peaks vary over time, which will affect the prediction accuracy of the SAM. In this paper, we investigate the periodic noise and its variations present in BDS clock offsets, and improve the clock prediction model by considering the periodic variations. The periodic noise and its variations over time are analyzed and quantified by short time Fourier transform (STFT). The results show that both the amplitude and frequency of the main periodic term in BDS clock offsets vary with time. To minimize the impact of periodic variations on clock prediction, a time frequency analysis model (TFAM) based on STFT is constructed, in which the periodic term can be quantified and compensated accurately. The experiment results show that both the fitting and prediction accuracy of TFAM are better than SAM. Compared with SAM, the average improvement of the prediction accuracy using TFAM of the 6 h, 12 h, 18 h and 24 h is in the range of 6.4% to 10% for the GNSS Research Center of Wuhan University (WHU) clock offsets, and 11.1% to 14.4% for the Geo Forschungs Zentrum (GFZ) clock offsets. For the satellites C06, C14, and C32 with marked periodic variations, the prediction accuracy is improved by 26.7%, 16.2%, and 16.3% for WHU clock offsets, and 29.8%, 16.0%, 21.0%, and 9.0% of C06, C14, C28, and C32 for GFZ clock offsets.

Global Navigation Satellite System—Acoustic (GNSS-A) positioning is the main technique for seafloor geodetic positioning. A transceiver lever arm offset and sound velocity bias in seawater are the main systematic errors of the GNSS-A positioning technique. Based on data from a sea trial in shallow water, this paper studies the functional model of GNSS-A positioning. The impact of the two systematic errors on seafloor positioning is analysed and corresponding processing methods are proposed. The results show that the offset in the lever arm measurement should be parameterised in the observation equation. Given the high correlation between the vertical lever arm offset and the vertical coordinate of the seafloor station, a sample search method was introduced to fix the vertical offset correction. If the calibration of the sound velocity profiler cannot be ensured, the correction parameter of the sound velocity bias should be solved. According to the refined functional model and corrections, the position of a seafloor station in shallow water can be determined with a precision of better than 1 cm.

Restenosis after percutaneous coronary intervention (PCI) is a remained clinical problem which limits long-term success of PCI. Although there was recognition that probucol in treating restenosis after percutaneous transluminal coronary angioplasty, the efficacy of probucol on restenosis after stent-implantation is controversial. So this meta-analysis was conducted to investigate the association between probucol and late restenosis.Articles were assessed by four trained investigators, with divergences resolved by consensus. PubMed, EMBASE, ScienceDirect and the Cochrane Central Register of clinical trials were searched for pertinent studies. Inclusion criteria were random allocated to treatment and a comparison of probucol-treated patients and control patients (not treated with lipid-lowering drug) undergoing PCI.Fifteen studies with 859 subjects were analyzed. Major outcome, binary angiographic restenosis defined as >50% stenosis upon follow-up angiography, was significantly decreased with probucol treatment (RR = 0.59 [0.43, 0.80] among vessels, P = 0.0007; and RR = 0.52 [0.40, 0.68] among patients, P