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Unveiling the spatial and temporal distribution of urban ecological resilience and analyzing the configuration paths for enhancing its levels are crucial for promoting sustainable development in China. Our study integrates the DPSIR and EES models, considering the causal relationships between systems affecting urban ecological resilience while also examining their internal structures. Based on this, we construct an evaluation system for urban ecological resilience indicators. Utilizing the entropy-TOPSIS method, we assess the ecological resilience index (ERI) across 280 Chinese cities from 2011 to 2021, and the kernel density estimation and Markov chain are used to study the evolution process while the magnitude and source of spatial–regional differences are examined by the Dagum Gini coefficient decomposition method. Additionally, we empirically investigate the driving mechanisms toward high ERI with the focused stepwise quantitative case analysis (fsQCA) method based on the technology–organization–environment (TOE) framework. The results find that the ERI in China shows a tendency of moderate growth in variability, with an obvious gradient distribution: higher levels in the eastern and southern and lower levels in the western and northern regions. Also, ERI exhibits evolutionary features of increasing polarization and inter-regional differentiation. Spatial disparities gradually increase with fluctuations, driven primarily by transvariation density and intra-regional differences, contributing to a dual non-equilibrium state of east–west and north–south directions. Achieving a high ERI is influenced by various antecedent variables interacting with each other, and there are three predominant driving paths among these variables, with the level of informatization playing a central role in each pathway. [ABSTRACT FROM AUTHOR]

The surface glycoprotein (S protein) of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) was used to develop coronavirus disease 2019 (COVID‐19) vaccines. However, SARS‐CoV‐2, especially the S protein, has undergone rapid evolution and mutation, which has remained to be determined. Here, we analyzed and compared the early (12 237) and the current (more than 10 million) SARS‐CoV‐2 strains to identify the mutation features and geographical distribution of the S gene and S protein. Results showed that in the early strains, most of the loci were with relative low mutation frequency except S: 23403 (4486 strains), while in the current strains, there was a surge in the mutation strains and frequency, with S: 23403 constantly being the highest one, but tremendously increased to approximately 1050 times. Furthermore, D614 (S: 23403) was one of the most highly frequent mutations in the S protein of Omicron as of March 2022, and most of the mutant strains were still from the United States, and the United Kingdom. Further analysis demonstrated that in the receptor‐binding domain, most of the loci with low mutation frequency in the early strains, while S: 22995 was nowadays the most prevalent loci with 3 122 491 strains in the current strains. Overall, we compare the mutation features of the S region in SARS‐CoV‐2 strains between the early and the current stains, providing insight into further studies in concert with emerging SARS‐CoV‐2 variants for COVID‐19 vaccines. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surface (RIS) is regarded as a promising technology with great potential to boost wireless networks. Affected by the “double fading” effect, however, conventional passive RIS cannot bring considerable performance improvement when users are not close enough to RIS. Recently, active RIS is introduced to combat the double fading effect by actively amplifying incident signals with the aid of integrated reflection-type amplifiers. In order to reduce the hardware cost and energy consumption due to massive active components in the conventional fully-connected active RIS, a novel hardware-and-energy efficient sub-connected active RIS architecture has been proposed recently, in which multiple reconfigurable electromagnetic elements are driven by only one amplifier. In this paper, we first develop an improved and accurate signal model for the sub-connected active RIS architecture. Then, we investigate the joint transmit precoding and RIS reflection beamforming (i.e., the reflection phase-shift and amplification coefficients) designs in multiuser multiple-input single-output (MU-MISO) communication systems. Both sum-rate maximization and power minimization problems are solved by leveraging fractional programming (FP), block coordinate descent (BCD), second-order cone programming (SOCP), alternating direction method of multipliers (ADMM), and majorization-minimization (MM) methods. Extensive simulation results verify that compared with the conventional fully-connected structure, the proposed sub-connected active RIS can significantly reduce the hardware cost and power consumption, and achieve great performance improvement when power budget at RIS is limited. [ABSTRACT FROM AUTHOR]

Cell-free millimeter-wave (mmWave) multiple-input multiple-output (MIMO) communications have been proposed as promising enablers for the next generation wireless networks. In this paper, we study the user association and hybrid beamforming in cell-free mmWave systems without full channel state information (CSI) acquisition. We consider a cloud radio access network (C-RAN), where multiple remote radio heads (RRHs) are distributed to communicate with users via analog beamforming, and connected to a centralized baseband unit (BBU) through fronthaul links which executes digital beamforming. We aim to jointly design user association, hybrid beamforming, and fronthaul compression with the aid of uplink training. A train-and-design framework is developed to achieve this goal. In particular, we first propose a two-stage uplink training approach to assist RRH-level design, during which the analog beamforming and user association are obtained. After that, digital beamforming and fronthaul compression are optimized at BBU based on the training results. Two performance metrics are considered in this paper, i.e. weighted sum-rate maximization and max-min fairness. Simulation results demonstrate the effectiveness of the proposed train-and-design framework for both sum-rate maximization and max-min fairness performance metrics. It is shown that the proposed algorithms can achieve comparable performance to the full-digital beamformer. [ABSTRACT FROM AUTHOR]

Optimally extracting the advantages available from reconfigurable intelligent surfaces (RISs) in wireless communications systems requires estimation of the channels to and from the RIS. The process of determining these channels is complicated when the RIS is composed of passive elements without any sensing or data processing capabilities, and thus, the channels must be estimated indirectly by a noncolocated device, typically a controlling base station (BS). In this article, we examine channel estimation for passive RIS-based systems from a fundamental viewpoint. We study various possible channel models and the identifiability of the models as a function of the available pilot data and behavior of the RIS during training. In particular, we will consider situations with and without line-of-sight propagation, single-antenna and multi-antenna configurations for the users and BS, correlated and sparse channel models, single-carrier and wideband orthogonal frequency-division multiplexing (OFDM) scenarios, availability of direct links between the users and BS, exploitation of prior information, as well as a number of other special cases. We further conduct simulations of representative algorithms and comparisons of their performance for various channel models using the relevant Cramér-Rao bounds. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surface (RIS) is a promising technology for 6 G networks owing to its superior ability to enhance the capacity and coverage of wireless communications by smartly creating a favorable propagation environment. In this paper, we investigate the potential of employing RIS in dual-functional radar-communication (DFRC) systems for improving both radar sensing and communication functionalities. In particular, we consider a RIS-assisted DFRC system in which the multi-antenna base station (BS) simultaneously performs both multi-input multi-output (MIMO) radar sensing and multi-user multi-input single-output (MU-MISO) communications using the same hardware platform. We aim to jointly design the dual-functional transmit waveform and the passive beamforming of RIS to maximize the radar output signal-to-interference-plus-noise ratio (SINR) achieved by space-time adaptive processing (STAP), while satisfying the communication quality-of-service (QoS) requirement under one of three metrics, the constant-modulus constraint on the transmit waveform, and the unit-modulus constraint of RIS reflecting coefficients. An efficient algorithm framework based on the alternative direction method of multipliers (ADMM) and majorization-minimization (MM) methods is developed to solve the complicated non-convex optimization problem. Simulation results verify the advancement of the proposed RIS-assisted DRFC scheme and the effectiveness of the developed ADMM-MM-based joint transmit waveform and passive beamforming design algorithm. [ABSTRACT FROM AUTHOR]

Introduction: We explored the association between clinical outcomes and the cleavage rate of day-3 cleavage slow-growing embryos after overnight culture. Methods: The data collected from 303 frozen embryo transfer (FET) cycles with 606 4-cell or 5-cell embryos cultured overnight (18–22 h) after thawing were analyzed. Based on the growth rate after the overnight culture, the embryos were divided into three groups: no embryo reaching eight cells (Group I), either one of the two embryos reaching eight cells (Group II), and both two embryos reaching eight cells or more (Group III). A statistical analysis of the different clinical outcomes from the three groups was performed. Results: Biochemical pregnancy rate (OR 3.22; p = 0.001), implantation rate (OR 2.44; p = 0.002), clinical pregnancy rate (OR 3.04; p = 0.001), ongoing pregnancy rate (OR 3.14; p = 0.001), and live birth rate (OR 2.78; p = 0.004) were significantly higher in Group III as compared to Group I. Group II had a significantly higher biochemical pregnancy rate (OR 2.02; p = 0.013) and implantation rate (OR 1.77; p = 0.019) than Group I. Conclusions: The capability of day-3 cleavage slow-growing embryos to reach eight cells, especially that of two embryos reaching eight cells by overnight culture, appear to result in a better pregnancy outcome. [ABSTRACT FROM AUTHOR]