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Pneumonia refers to a death‐causing infection. Astragali Radix (AR) and Atractylodis Macrocephalae Rhizoma (AMR) are widely used as traditional tonic and promising edible immunomodulatory herbal medicine, but the systemic mechanism is not well understood. Therefore, a strategy based on network pharmacology and molecular docking was designed to explore the systemic mechanism of AR‐AMR acting on pneumonia. After a series of bioinformatics assays, seven kernel targets were obtained, including TNF, IL6, IFNG, IL1B, IL10, IL4, and TLR9. And seven key compounds were identified as the synergy components of AR‐AMR acting on pneumonia, the four key compounds belonging to AR were (3R)‐3‐(2‐hydroxy‐3,4‐dimethoxyphenyl)‐7‐chromanol, formononetin, quercetin, and kaempferol, the three key compounds belonging to AMR were atractylone, 14‐acetyl‐12‐senecioyl‐2E, 8E, 10E‐atractylentriol, and α‐Amyrin. The crucial pathways were mainly related to three modules, including immune diseases, infectious disease, and organismal systems. Collectively, these observations strongly suggest that the molecular mechanisms of AR‐AMR regulating pneumonia were closely related to the correlation between inflammation and immune response. Practical applications: Astragali radix and Atractylodis macrocephalae rhizoma can be used as "medicine‐food homology" for dietary supplement. AR and AMR are widely used as a traditional tonic and promising edible immunomodulatory herbal medicine. The AR‐AMR herb pairs are used for compatibility many times in the recommended prescriptions in COVID‐19 develop pneumonia in China. However, the ingredients and mechanisms of AR‐AMR acting on Pneumonia via immunomodulation are unclear. In this paper, bioinformatics and network biology were used to systematically explore the mechanisms of the AR‐AMR herb pairs in treatment of pneumonia, and further analyze the correlation mechanism between it and COVID‐19 develop pneumonia. To sum up, our study reveals the interrelationships between components, targets, and corresponding biological processes of AR‐AMR acting on pneumonia. Understanding these relationships may provide guidance and theoretical basis for the further application of AR‐AMR herb pairs. [ABSTRACT FROM AUTHOR]

In this paper, we study the uplink in a single-cell massive multiple-input–multiple-output system. The base station (BS) is equipped with three antenna arrays, each covering one third of the cell area. Each antenna array comprises a large yet finite number of antennas. The single-antenna users are randomly and uniformly distributed in the cell, transmitting to the BS utilizing full channel inversion power control. All users experience Rician fading. Receiver maximum-ratio-combining is performed at the BS. Under such a setting, we focus on one cell sector and analyze the intrasector interference in a realistic situation where the number of BS antennas is not extremely large compared with the user number. In particular, we show that, due to the line-of-sight (LoS) component of the channel, the interference is partially determined by the angles of arrival of the signals. We approximate the LoS component interference by a Beta mixture. The interference in Rician fading is then modeled as a noncentral chi-square distribution with a random noncentrality parameter, corresponding to the LoS component. The approximate interference distribution can be used to compute signal-to-interference-ratio-dependent metrics such as outage probability and average throughput. [ABSTRACT FROM AUTHOR]