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In the past few decades, network real-time kinematic (NRTK) positioning technology has developed rapidly. Generally, in the continuously operating reference stations (CORS) network, within a moderate baseline length, e.g., 80–100 km, atmospheric delay can be effectively processed through regional modeling and, thus, can support almost instantaneous centimeter-level NRTK positioning. However, in long-baseline CORS networks, especially during the active period of the ionosphere, ionospheric delays cannot be fully eliminated through modeling, leading to decreased NRTK positioning accuracy. To address this issue, this study proposes a long-baseline NRTK positioning method considering ionospheric residual interpolation uncertainty (IRIU). The method utilizes the ionospheric residual interpolation standard deviation (IRISTD) calculated during atmospheric delay modeling, then fits an IRISTD-related stochastic model through the fitting of the absolute values of the ionospheric delay modeling residuals and IRISTD. Finally, based on the ionosphere-weighted model, the IRISTD processed by the stochastic model is used to constrain the ionospheric pseudo-observations. This method achieves good comprehensive performance in handling ionospheric delay and model strength, and the advantage is validated through experiments using CORS data with baseline lengths ranging from 54 km to 106 km in western China and from 84 km to 180 km in AUSCORS data. Quantitative results demonstrate that, across the three sets of experiments, the proposed ionosphere-weighted model achieves an average increase in the fixed rate of 16.9% compared to the ionosphere-fixed model and 25.6% compared to the ionosphere-float model. In terms of positioning accuracy, the proposed model yields average improvements of 67.4%, 76.4%, and 66.0% in the N/E/U directions, respectively, compared to the ionosphere-fixed model, and average improvements of 21.0%, 32.0%, and 24.4%, respectively, compared to the ionosphere-float model. Overall, the proposed method can achieve better NRTK positioning performance in situations where ionospheric delay modeling is inaccurate, such as long baselines and ionospheric activity.

Abstract In order to eliminate the influence of moving targets in visual positioning, a dynamic object filtering approach based on object detection and inter‐frame geometric constraints is proposed to filter the dynamic objects in monocular images. The object detection algorithm is firstly used to identify and locate objects in the single‐frame image, and the object matching between frames is performed. Then, the depth estimation network and pose recovery network are trained jointly to output estimated depth along with transformation matrix of object centroids between frames respectively. Finally, the mapping centroid is obtained from the estimated depth and inter‐frame transformation matrix. The joint constraint function is performed to complete the detection and filtering of dynamic objects. The experimental results show that the proposed dynamic object filtering approach not only can filter moving objects in sequence images accurately but also allows to reserve the dynamic objects that are temporarily in the stop state. The generalization ability of this approach is also verified in a real urban road scene and meets the requirements of follow‐up research in visual positioning.

Abstract The coupling effect of one-dimensional (1D) materials is of great significance for the practical application of 1D materials in high-density memory devices and ultra-micro nanometer array lasers. However, the determinants of the coupling effect remain debated. Here, using first principles methods, we investigate the effects of chirality, size and stacking mode on the stability and electronic properties of few-chain Te nanowires. We find that the stacking mode and size play a dominant role in the stability of the nanowires, while the chirality and size have a key effect on the electronic structures. These phenomena are mainly due to the quantum size effect and the special helical structure of the Te chain. Our findings provide the means for adjusting the band gap and the candidates for constructing n-type spin devices, which serve as a basis for the research and manufacture of new nano electronic devices.

The diterpene synthase AfAS was identified from Aspergillus fumigatiaffinis. Its amino acid sequence and—according to a structural model—active site architecture are highly similar to those of the fusicocca‐2,10(14)‐diene synthase PaFS, but AfAS produces a structurally much more complex diterpene with a novel 6–5–5–5 tetracyclic skeleton called asperfumene. The cyclisation mechanism of AfAS was elucidated through isotopic labelling experiments and DFT calculations. The reaction cascade proceeds in its initial steps through similar intermediates as for the PaFS cascade, but then diverges through an unusual vicinal deprotonation‐reprotonation process that triggers a skeletal rearrangement at the entrance to the steps leading to the unique asperfumene skeleton. The structural model revealed only one major difference between the active sites: The PaFS residue F65 is substituted by I65 in AfAS. Intriguingly, site‐directed mutagenesis experiments with both diterpene synthases revealed that position 65 serves as a bidirectional functional switch for the biosynthesis of tetracyclic asperfumene versus structurally less complex diterpenes. [ABSTRACT FROM AUTHOR]

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Infiltration of stormwater through green surfaces is an important means of groundwater recharge. However, the increase in constructed impervious area caused by intensive urbanization has led to a reduction in rainwater infiltration over the past decade. The constructed rapid infiltration system (CRIS) with an ample open space plays an important role in groundwater recharge. This study aims to explore the influence of stormwater (roof runoff) concentration infiltration on the groundwater table and quality in the CRIS. Groundwater table monitoring is conducted for more than 2 years (October 2017–December 2019) by continuous online monitoring combined with manual sampling. Results show that the addition of zeolite to the CRIS has a good removal effect on rainfall runoff pollutants, and the influence of stormwater concentration infiltration on groundwater quality is small when the CRIS enters the stable running stage. The increased proportion of chemical oxygen demand, N, and P in J1 are all less than 10% from 2018 to 2019, and they are less than 20% for heavy metals. The stormwater concentration infiltration can recharge groundwater and increase the groundwater depth, and the groundwater depth varies from 0.5 m to 1.5 m during the monitoring period. The influence scope of the concentrated infiltration on the groundwater table and quality is between 25 and 45 m. The response of the groundwater table and quality to the stormwater concentration infiltration of J1, 25 m away from the CRIS, exhibits hysteresis, and the lag time is about 3–4 months. Conclusion from relevant research can provide important theoretical support for the further study of groundwater recharge by the CRIS.

The impact of inherited genetic variation on gene expression in humans is well-established. The majority of known expression quantitative trait loci (eQTLs) impact expression of local genes (cis-eQTLs). More research is needed to identify effects of genetic variation on distant genes (trans-eQTLs) and understand their biological mechanisms. One common trans-eQTLs mechanism is "mediation" by a local (cis) transcript. Thus, mediation analysis can be applied to genome-wide SNP and expression data in order to identify transcripts that are "cis-mediators" of trans-eQTLs, including those "cis-hubs" involved in regulation of many trans-genes. Identifying such mediators helps us understand regulatory networks and suggests biological mechanisms underlying trans-eQTLs, both of which are relevant for understanding susceptibility to complex diseases. The multitissue expression data from the Genotype-Tissue Expression (GTEx) program provides a unique opportunity to study cis-mediation across human tissue types. However, the presence of complex hidden confounding effects in biological systems can make mediation analyses challenging and prone to confounding bias, particularly when conducted among diverse samples. To address this problem, we propose a new method: Genomic Mediation analysis with Adaptive Confounding adjustment (GMAC). It enables the search of a very large pool of variables, and adaptively selects potential confounding variables for each mediation test. Analyses of simulated data and GTEx data demonstrate that the adaptive selection of confounders by GMAC improves the power and precision of mediation analysis. Application of GMAC to GTEx data provides new insights into the observed patterns of cis-hubs and trans-eQTL regulation across tissue types.