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Spatial variations in atmospheric parameters, including pressure, temperature, and humidity, significantly impact the precision of interferometric synthetic aperture radar (InSAR) measurements. This significantly limits the applicability of InSAR in the fields, such as terrain inversion and deformation monitoring. Fortunately, the evolving numerical weather models (NWMs) could offer a viable tropospheric correction solution. However, given the influence of complex terrain and areas with sparse atmospheric observation, the effectiveness of tropospheric correction with different NWMs’ resolutions remains to be evaluated. This requires the examination of different NWMs tropospheric delay correction in detail with sufficient metrics. A total of 36 Sentinel-1 interferograms of 2023, which cover Berlin, Paris, and Milan, respectively, are used as examples. Tropospheric correction is carried out using ICOsahedral nonhydrostatic D2 (ICON-D2), the fifth-generation European Centre for Medium-Range Weather Forecast atmospheric reanalysis, and modern-era retrospective analysis for research and applications version 2. To assess the correction efficacy of various resolutions, standard deviation, semivariogram function, and phase–elevation correlation coefficient served as the evaluation method. Results show that the ICON-D2 model outperforms the other models in these metrics, especially in regions with significant topographic relief. Among them, the standard deviation of the corrected interferogram decreased by 21.6%–35.8%. NWMs have demonstrated effectiveness in mitigating altitude-related tropospheric delays without needing altitude assimilation. Overall, the present study underscores that despite potential uncalibrated atmospheric effects, high-resolution NWMs are anticipated to provide a more precise solution for InSAR, especially in regions exhibiting intricate and challenging terrain features.

Non terrestrial network (NTN) has been regarded as an important component of beyond 5G communication. The 3rd Generation Partnership Project (3GPP) has officially started studies on NTN for the purpose of integrating satellites with New Radio (NR) terrestrial networks. However, the NR defined orthogonal frequency division multiplexing (OFDM) waveform is susceptible to doubly selective fading and nonlinear distortions in the NTN uplink, thus leading to severe performance loss. In this paper, a type of block scalable OFDM (BS-OFDM) waveform is proposed, which has modified subcarrier and sub-symbol segmentation when compared to the conventional NR defined OFDM. With our proposed framework, block scalable discrete Fourier transform spread OFDM (BS-DFT-s-OFDM) and block scalable orthogonal time frequency space (BS-OTFS) can also be implemented. To obtain a comprehensive understanding of different waveforms, performance metrics concerning peak to average power ratio (PAPR), total degradation (TD), bit error rate (BER), and complexity are presented. The simulation results demonstrate that the proposed block scalable waveforms can obtain better performance and lower complexity than existing NR waveforms in different NTN uplink scenarios, and can therefore be promising candidate waveforms for NR NTN.

High-resolution remote sensing technology is an efficient and low-cost space-to-earth observation strategy, which can carry out simultaneous monitoring of large-scale areas. It has incomparable advantages over ground monitoring solutions. Traditional road extraction methods are mainly based on image processing techniques. These methods usually only use one or a few features of images, which is difficult to fully deal with the real situation of roads. This work proposes a two-steps network for the road extraction. First, we optimize a pix2pix model for image translation to obtain the required map style image. Images output by the optimized model is full of road features and can relief the occlusion issues. It can intuitively reflect information such as the position, shape and size of the road. After that, we propose a new FusionLinkNet model, which has a strong stability in the road information by fusing the DenseNet, ResNet and LinkNet. Experiments show that our accuracy and learning rate have been improved. The MIOU (Mean Intersection Over Union) value of the proposed model in road extraction is over 80% in both DeepGlobe and Massachusetts road dataset. The figures are available from https://github.com/jsit-luwei/training-dataset.

Active reconfigurable intelligent surface (ARIS) has sparked more attention due to its capability to overcome the impact of double fading. This paper introduces using an ARIS to aid non-orthogonal multiple access (NOMA) communications over cascade Rician fading channels, where the direct links between the base station and users are seriously blocked. By applying ARIS, it can amplify the superposed signals to overcome the double pass loss effect caused by passive RIS. Both ARIS and NOMA can have synergistic impacts on sixth-generation communication systems. New approximated and asymptotic expressions in terms of outage probability and ergodic data rate of the k-th user are deduced for ARIS-NOMA systems. Based on asymptotic analytical results, we further calculate the diversity order and high signal-to-noise ratio slope of the k-th user. Finally, the system throughput of ARIS-NOMA is discussed in the delay-constrained transmission mode. Monte Carlo numerical results are performed to verify that: (1) the outage behaviors of ARIS-NOMA are better than that of ARIS-assisted orthogonal multiple access (OMA); (2) as the impact of thermal noise caused by ARIS becomes larger, the communication performance from the base station to ARIS, then to users, becomes worse; (3) the ARIS-NOMA systems have the ability to provide the improved ergodic data rate relative to ARIS-OMA.

Yellowfin seabream (Acanthopagrus latus) is a hermaphroditic fish with male prematurity, which is also an economically important mariculture species in coastal areas of China. Although the production yield has been increasing in recent years, artificial breeding of this species remains imperfect due to the lack understanding of its sex differentiation mechanism. In this study, we conducted transcriptomic sequencing to screen for sex-related genes in different stage of the testis, ovotestis, ovary, hypothalamus, and pituitary tissues of yellowfin seabream. During gonad development (from intersex to mature stage), Gnrh3, Kiss2, and Dbh were expressed in the hypothalamus and Lhb and Fshb were expressed in the pituitary. Sex-related genes such as Hsd11b1, Foxl2l, Amh, and Gsdf were among the top 10 downregulated genes in the intersex testis compared with the mature testis. The expression of Hsd11b, Wnt, and Sox families genes differed significantly in the sex change process among functional mature gonads. In addition, treatment with estradiol resulted in feminizing of the ovotestis. Inhibition of androgens or estrogens promoted ovarian or testicular steps of ovotestis development. In summary, we systematically evaluated gene expression profiles during yellowfin seabream gonad development from intersex to functional male or female. Our results confirmed that regulation by the hypothalamus-pituitary-gonad (HPG) axis and the promotion of sex steroid hormones acted on this process, and they provide a reference for further studies of the involvement of the HPG axis in sex change and of sex induction methods in yellowfin seabream.