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To address the problem of pillar instability in residual mining areas under repeated mining disturbances, the prediction of pillar instability time and mining technology is studied by using numerical simulations, theoretical examinations, and practical experimentation techniques utilizing the remaining facade of the Shenghua Coal Industry 3103. On the basis of the findings, employing a fully mechanized mining technique exerts greater pressure on the coal pillar, increasing the likelihood of plastic failure. However, adopting the segmental filling mining approach can effectively disperse this pressure, consequently mitigating potential damage to the coal pillar. Initially, the coal pillar undergoes a progressive yielding or collapsing process at its periphery, leading to instability once the area of the projectile core of the coal pillar decreases beyond a specific threshold. The dimensions of both the affected roadway and the coal pillar play a pivotal role in determining the coal pillar's load‐bearing capacity. A prediction model for pillar instability is established. If the area of the projectile core is less than 34% during remining, the mining method should be changed or pillar reinforcement should be implemented. The accurate prediction and adaptation of the model's mining approach ensure the secure extraction of coal pillars within the remaining mining region, with successful validation of the model's performance. [ABSTRACT FROM AUTHOR]

Virtual antenna array (VAA) formed by unmanned aerial vehicle (UAV) antenna units using collaborative beamforming (CB) technology plays an important role in the air communication system, and can be used in radar, military, disaster rescue and other places. However, there are still some issues with the beam pattern formed by this method, such as high sidelobe level (SLL), high cost and low efficiency. In this article, each UAV carries an omnidirectional antenna unit, and a large number of UAVs form a UAV virtual rectangular antenna array (UVRAA) to communicate with the ground base station (BS). We formulate an overhead minimization and efficient communication multi‐objective optimization problem (OMECMOP) which jointly optimize the excitation current weights of the UVRAA and reduce the number of UAVs in operation to improve the beam pattern, enhance the communication efficiency and decrease the overhead of UVRAA. In addition, we also propose an improved multi‐objective multi‐verse optimization algorithm based on the inverse S$$ S $$ decline curve type (ISDT‐MOMVO) which introduces a strategy optimization initialization solution with quasi‐opposition based learning (QBL) and a hybrid solution updating operators to solve the OMECMOP. The simulation results show that compared with other traditional swarm intelligence (SI) optimization algorithms the ISDT‐MOMVO algorithm produces better beam pattern and the thinning rate can reach 50%. [ABSTRACT FROM AUTHOR]

Summary: Transient and rapid increase in cytosolic Ca2+ plays a crucial role in plant–pathogen‐associated molecular pattern (PAMP)‐triggered immunity (PTI). Cyclic nucleotide‐gated channels (CNGCs) have been implicated in mediating this Ca2+ influx; however, their regulatory mechanisms remain poorly understood.Here, we have found that AVRblb2 requires the calmodulin (CaM) and calmodulin‐like (CML) proteins as co‐factors to interact with the NbCNGCs, resulting in the formation of AVRblb2‐CaM/CML‐NbCNGCs complex. Furthermore, CaM and CML are dissociated from NbCNGC18 during PTI response to increase Ca2+ influx; however, Avrblb2 inhibits calcium channel activation by disrupting the release of CaM and CML from NbCNGC18.Following recognition of PAMP, NbCNGC18 forms active heteromeric channels with other NbCNGCs, which may give selectivity of CNGC complex against diverse signals for fine‐tuning of cytosolic Ca2+ level to mediate appropriate responses. Silencing of multiple NbCNGCs compromised the function of AVRblb2 on the pathogenicity of Phytophthora infestans, confirming that AVRblb2 contributes to pathogen virulence by targeting CNGCs.Our findings provide new insights into the regulation of CNGCs in PTI and the role of pathogen effectors in manipulating host cell physiology to promote infection. [ABSTRACT FROM AUTHOR]

Preparation of lactic acid (LaA) from waste biomass Pueraria cellulose by chemically catalyzed conversion is important for the realization of biomass waste resource utilization. In this study, lignin was used as raw material to prepare lignin-based carbonaceous support (LCSA) by one-step sulfonation and carbonization with chlorosulfonic acid. LCSA–AlxZny, a lignin-based carbon solid acid catalyst, was obtained by modifying the carbonaceous support with inexpensive and readily available Al and Zn chlorides. Through the use of SEM, BET, XRD, FT-IR and NH3–TPD, the catalyst's physical as well as chemical characteristics were identified. In an aqueous solution, these catalysts were evaluated for the generation of LaA from Pueraria cellulose. LCSA–Al was identified as the optimal catalyst, subsequently, experimental conditions such as reaction time, reaction temperature, and catalyst dosage were studied and optimized. The results showed that at 160 °C, with 50 mg Pueraria cellulose, 50 mg catalyst, and 10 mL deionized water, the conversion rate of Pueraria cellulose was 53.7% and the highest LaA yield was 24.7% after 120 min of reaction. This research provides a new pathway for the preparation of chemicals from cellulose via multi-step tandem catalytic reactions. [ABSTRACT FROM AUTHOR]