This paper demonstrates the weakness of GNSS/INS-RTK (GIR) systems in mapping challenging environments because of obstruction and deflection of satellite signals. Thus, it emphasizes that the ...strategy of mapping companies to commercially provide maps using expensive GIR systems does not always work robustly. This limits the scalability of autonomous vehicle deployment in many road structures and modern cities. Accordingly, different critical environments in Tokyo have been analyzed and investigated to demonstrate the effects of the road structure complexity on the GIR map quality with highlighting the relevant reasons. Therefore, this paper is intended to be a reference to prove that the data of GIR systems cannot always be considered as ground truth and the integration of SLAM technologies into the mapping modules is very necessary to enable the levels four and five of autonomous driving.
Hepatocyte growth factor (HGF) receptor is a member of the receptor tyrosine kinases (RTKs) and has been reported to perform diverse functions in various cell types during both the developmental and ...adult stages. Among different roles, HGF is best known for its angiogenic effects of inducing the migration of endothelial cells. Because angiogenesis is one of the prerequisite steps for tumor metastasis, HGF-dependent cell migration has to be tightly controlled. However, the underlying mechanisms regulating the optimum level of HGF/c-met signaling have been poorly understood. In this study, we tested whether the migration of endothelial cells is regulated by a negative feedback mechanism under disproportionately large amounts of HGF. Data from endothelial cell migration assays showed that HGF activity increased as its concentration increased, but declined beyond a certain point. Under limiting conditions, amounts of phosphorylated Erk and Akt surged, reaching a plateau in which the enhanced level was more or less maintained. The c-met receptor was degraded when unnecessarily large amounts of HGF were present. Under these conditions, HGF could no longer activate downstream signaling pathways even if cells were re-treated with optimal amounts of HGF. Excessive doses of HGF increased the phosphorylation of tyrosine residue 1003 involved in the ubiquitination of c-met, and phosphorylated c-met was diverted toward the proteasomal degradation pathway. Taken together, HGF/c-met signaling is tightly regulated by a negative feedback loop through an ubiquitin-proteasomal degradation pathway.
•HGF-mediated cell migration increased as concentration of HGF increased, but declined beyond a certain point.•The c-met receptor was degraded when unnecessarily large amounts of HGF were present.•Excessive amounts of HGF attenuated downstream signaling even if cells were re-treated with optimal amounts of HGF.•Excessive amounts of HGF diverted c-met toward the proteasomal degradation pathway through phosphorylation of Tyr 1003.
The quality of weather radar affects the reliability and effectiveness of monitoring severe convective weather. Therefore, rigorous calibration and validation are the foundation for the quantitative ...application of weather radar. Among the available methods, radial velocity validation is of great significance for reducing the false alarm rate in the identification of tornadoes and thunderstorms. Based on the traditional method that utilizes internal and external instrument radar velocity measurements, we propose a weather radar radial velocity validation method that uses RTK UAV to simulate external targets. In addition, according to the characteristics of the UAV application scenarios, we introduce the evaluation parameter of optimal absolute accuracy to supplement the original parametric system. The experimental results show that the evaluation parameter of optimal absolute accuracy can effectively reduce the interference caused by the systematic deviation of the UAV due to the internal and external environment, which can affect the validation results. When the UAV velocity is not greater than 10 m/s, the optimal absolute accuracy of the radial velocity validation is less than 0.05 m/s, which is essentially consistent with the external instruments’ measurement results. This method can be effectively applied to the procedural handling of weather radar radial velocity validation. It is significant for ensuring the accuracy and quality of weather radar radial velocity measurements and improving the effectiveness of radar velocity data applications.
The time difference RTK (TDRTK) of GNSS can obtain high-precision baseline constraints to control the cumulative error of dead reckoning technology. However, the availability of traditional TDRTK ...decreases sharply with the increase of time interval. A geometry-free TDRTK method with quality control using multi-frequency observations is proposed to solve this problem. Experimental shows that in the dynamic condition of a stand-alone GNSS receiver, the average and maximum relative position accuracy (10 min and 10 kilometres tests) of the proposed method are improved by 42.2% and 44.2% compared with the existing methods.
In uncombined long-range real-time kinematic positioning, the ionospheric delays are usually parameterized as a random-walk process, and its power spectral density (PSD) is a decisive parameter ...affecting the positioning performance. Since the spatiotemporal ionospheric variation is complex, using empirical PSD values is insufficient, especially for strong ionospheric variation. The ionospheric observations extracted from the original observations contain the actual ionospheric variation and can be used for estimating PSD. However, they are contaminated by the observation noise, which is amplified because of the high-rate data. In this study, we propose a simple method to separate the PSD of ionospheric delays and the observation noise based on their different stochastic characteristics, i.e., random-walk process and white noise for the ionospheric delay and observation noise, respectively. We evaluate the effect of ionospheric PSD from the proposed method and two typical empirical values based on three long-range baselines up to 105 km (static case) and two baselines with 22 and 41 km lengths (kinematic case). The positioning performance is verified from two aspects: ambiguity fixing time (AFT) and positioning accuracy. The results show that compared to the solutions using the empirical values, using PSD from the proposed method can greatly shorten the AFT and improve the positioning accuracy for both the long-range baselines and the kinematic baselines, the AFT is improved by 65% for kinematic baselines, and the average positioning accuracy in long-range baselines is improved by 12%, 15%, and 19% in the E, N, and U directions compared to that using empirical values.
PPP–RTK, a synthesis of precise point positioning (PPP) and real-time kinematic (RTK) techniques, achieves fast integer ambiguity resolution-enabled positioning using, among others, satellite clocks, ...biases, and ionospheric corrections generated in a reference network. When formulating a network model to estimate these products, one usually considers a receiver as the pivot and selects its receiver-related parameters as the datum to address the rank deficiency problem. This work demonstrates that the precision of ambiguity-float combined PPP–RTK products relates to the pivot receiver selection. The combined product encompasses the summation of satellite clocks, satellite phase biases, and ionospheric delays at a certain station. Specifically, we find that the precision of ambiguity-float combined products at the pivot receiver surpasses that at non-pivot receivers by a significant margin. Consequently, user positioning becomes inhomogeneous in the network, as users far away from the pivot receiver perform worse than those close to the pivot receiver. To relieve this pivot receiver dependency, we emphasize the necessity of network integer ambiguity resolution, which improves the precision of products and ensures the homogeneity of user positioning. For verification purposes, we performed a one-week experiment involving 12 global positioning system (GPS) receivers to generate network products and 23 receivers to perform user positioning. The results showed that the precision of ambiguity-float combined products at the pivot receiver was better than 2 cm, whereas that at non-pivot receivers reached several decimeters. With these ambiguity-float products employed on the user side, the time-to-first-fix (TTFF) of the positioning near the pivot receiver was less than 5 epochs, but that away from the pivot receiver exceeded 15 epochs. Network integer ambiguity resolution improved the quality of PPP–RTK products, as the precision of combined products at an arbitrary receiver reached several millimeters. User positioning with ambiguity-fixed products became homogeneous with an average three-dimensional root-mean-square (3D RMS) of 1.5 cm, and the mean TTFF decreased to 4 epochs.
The enormous biologic complexity of human cancer has stimulated the development of more appropriate experimental models that could resemble in a natural and spontaneous manner the physiopathologic ...aspects of cancer biology. Companion animals have many desired characteristics that fill the gap between in vitro and in vivo studies, and these characteristics have proven to be important in understanding many complex molecular aspects of human cancer. Spontaneous tumors in dogs share a wide variety of epidemiologic, biologic, and clinical features with human cancer, which makes this animal model both attractive and underused in oncology research. In this review, we summarize the importance of naturally occurring canine tumors as valuable tools for studying numerous aspects of human cancer as well as the potential use of this animal model for the development of new cancer treatments. We address specifically the use of canine mammary tumors as an increasingly powerful model to study human breast cancer.
High-precision positioning methods have drawn great attention in recent years due to the rapid development of smart vehicles as well as automatics driving technology. The Real-Time Kinematic (RTK) ...technique is a mature tool to achieve centimeter-level positioning accuracy in open-sky areas. However, the users who drive under dense urban conditions are always confronted with harsh global navigation satellite system (GNSS) environments. Skyscrapers and overpasses block the signals and reduce the number of visible satellites, making it difficult to achieve continuous and precise positioning. Considering that the road is relatively smooth in most urban areas, vehicles are expected to travel on the same plane when they are close to each other. The road plane information is a promising candidate to enhance the performance of the RTK method in constrained environments. In this paper, we propose a plane-constrained RTK (PCRTK) method using the positioning information from cooperative vehicles. In a vehicle-to-vehicle (V2V) network, the positions of cooperative vehicles are used to fit a road plane for the target vehicle. The parameters of the plane fitting are treated as new measurements to enhance the performance of the float estimator. The relationship between the plane parameters and the state of the estimator is derived in our study. To validate the performance of the proposed method, several experiments with a four-vehicle fleet were carried out in open-sky areas and dense urban areas in Beijing, China. Simulations and experimental results show that the proposed method can take advantage of the plane constraint and obtain more accurate positioning results compared to the traditional RTK method.
Autonomous vehicles require a real-time positioning system with in-lane accuracy. They also require an autonomous onboard integrity monitoring (IM) technique to verify the estimated positions at a ...pre-defined probability. This can be computationally demanding. PPP-RTK is a promising positioning technique that can serve this purpose. Since PPP-RTK is developed to process undifferenced and uncombined (UDUC) observations for both network and user sides, it provides the residuals of the individual measurements. This can be exploited to reduce the computational load consumed in the fault detection and exclusion (FDE) process, included in the IM task, without compromising the positioning availability. This research proposes filtering the faulty satellites by the network, then the hardware and location-dependent faults at the user end can be identified. This is achieved by calculating the ratio between the matching UDUC residuals of the user receiver and the nearest reference station observations. This ratio is used to rank the individual observations where the observation with the largest ratio is most likely to be the faulty one. Therefore, it is more likely to identify the faulty observation without generating and testing numerous subsets. In addition, the exclusion can be attempted per observation, which preserves observation availability, unlike the grouping techniques that perform the exclusion per satellite. The method was examined in two test cases where geodetic and commercial receivers were used. Results show that the computational load has been reduced significantly by about 85–99% compared to the solution separation and Chi-squared test methods that are commonly used for FDE.
The use of the GLONASS legacy signals for real-time kinematic positioning is considered. Due to the FDMA multiplexing scheme, the conventional CDMA observation model has to be modified to restore the ...integer estimability of the ambiguities. This modification has a strong impact on positioning capabilities. In particular, the ambiguity resolution performance of this model is clearly weaker than for CDMA systems, so that fast and reliable full ambiguity resolution is usually not feasible for standalone GLONASS, and adding GLONASS data in a multi-GNSS approach can reduce the ambiguity resolution performance of the combined model. Partial ambiguity resolution was demonstrated to be a suitable tool to overcome this weakness (Teunissen in GPS Solut 23(4):100, 2019). We provide an exhaustive formal analysis of the positioning precision and ambiguity resolution capabilities for short, medium, and long baselines in a multi-GNSS environment with GPS, Galileo, BeiDou, QZSS, and GLONASS. Simulations are used to show that with a difference test-based partial ambiguity resolution method, adding GLONASS data improves the positioning performance in all considered cases. Real data from different baselines are used to verify these findings. When using all five available systems, instantaneous centimeter-level positioning is possible on an 88.5 km baseline with the ionosphere weighted model, and on average, only 3.27 epochs are required for a long baseline with the ionosphere float model, thereby enabling near instantaneous solutions.
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