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The shield type temporary support robot is an important component of the intelligent excavation robot system for large section roadways that adapts to the coexistence of dirt and debris. Its main function is to provide a safe and reliable workspace for achieving 'parallel excavation and support' operations. In order to enhance the safe and stable support of the shield type temporary support robot for surrounding rock during its pushing and driving process, based on the structure, working environment, and operational requirements of the shield type temporary support robot, a mathematical model of its pushing amount and support force during pressurized driving, as well as a dynamic model of pressurized driving, are established. A hydraulic control system for the shield type temporary support robot driving under pressure is designed. The system mainly consists of a support hydraulic system and a driving hydraulic system. During static support, the support hydraulic system needs to constantly output a support force greater than the weight of the upper shield body itself, and the driving hydraulic system is in standby mode. When driving under pressure, the support hydraulic system and the driving hydraulic system work simultaneously, ensuring that the temporary support robot 'reducing stress without leaving the roof' while steadily moving forward with the roof under pressure at all times. A precise control method for shield type temporary support robot driving under pressure based on fuzzy PID is proposed. The pressure and displacement signals of the temporary support robot are collected in real time by displacement sensors integrated on the displacement cylinder and pressure sensors in the hydraulic circuit. The signals are used to reflect the changes in support force and driving displacement during the temporary support robot's driving under pressure. Based on the error and error rate of the support force and displacement, the fuzzy PID algorithm is used to modify the control parameters of the support force and displacement, achieving reliable control of driving under pressure based on the fuzzy PID algorithm. Both simulation and experimental results show that the effect of fuzzy PID control is superior to traditional PID control. Under fuzzy PID control, the relative error of support force during the pushing and driving process of the shield type temporary support robot is less than 1%, and the driving displacement error is less than 2 mm. Moreover, the response speed of support force and pushing amount control is fast, ensuring the safe and stable support of the surrounding rock during the pushing and driving process.

Climate change is creating a new era of infectious disease crises, further exacerbated by extreme weather. However, the relationship between extreme weather and infectious disease remain unclear. Here, we provide a new quantitative study on the impact of cold wave on COVID‐19 as an example. We found that during cold waves, extreme cold temperatures coupled with rapid aerosol transport accelerated COVID‐19 outbreaks. It directly increased the number of COVID‐19 cases in Beijing by 28.1% in the winter of year 2022. More urgently, cold temperatures led to a higher risk of death during infectious disease outbreaks, with a 7.07% increase in confirmed deaths and a 16.61% increase in excess mortality. Our findings emphasize the urgent need to promote a synergistic policy for responding to infectious diseases during cold wave disasters in order to minimize the risk of death among the elderly and those with underlying diseases. Plain Language Summary: The sudden drop in temperature and rapid spread of aerosols during cold waves resulted in a higher prevalence of infectious diseases. At the same time, low temperatures resulted in a higher risk of death due to infectious diseases and a variety of other factors during the epidemic. Key Points: The rapid dispersion of aerosols during cold waves hastens the transmission of infectious diseasesLow temperatures contribute to higher risk of death during infectious disease outbreaks [ABSTRACT FROM AUTHOR]

Special attention was drawn to the heavy metals contained in coal, due to it will cause harm to the environment during coal processing and utilization. The sequential chemical extraction of Shanxi coal (SX coal) and Wulanchabu coal (WLCB coal) was carried out to investigate the distribution of arsenic (As) in coals. Two raw coals were pyrolyzed at 300–900 °C in horizontal tubular furnace to investigate release behavior of As during pyrolysis process. The results showed that As in SX coal mainly existed in aluminosilicate-bound state (40.25%) and disulfide-bound state (32.51%), followed by carbonate-bound state and organic-bound state. The As in WLCB coal mainly existed in aluminosilicate-bound state (62.50%), followed by disulfide-bound state (19.10%). The As contents of water-soluble, ion-exchange and residue states in the two coals were less than others. The modes of occurrence of As had great influence on its volatilization behavior. As in organic part was easy to volatilize at low temperature. Sulfide-bound state would escape with the decomposition of pyrite. Because SX coal contained higher organic state and sulfide-bound state, the volatilization rate of As was higher than WLCB coal at any temperature, and the difference was more obvious at low temperature. In addition, FactSage simulation value was basically consistent with the experimental value. [ABSTRACT FROM AUTHOR]

Plant height is regarded as a key indicator that is crucial for assessing the crop growth status and predicting yield. In this study, an advanced method based on solid-state LiDAR technology is proposed, which is specifically designed to accurately capture the phenotypic characteristics of plant height during the maize growth cycle. By segmenting the scanned point cloud of maize, detailed point cloud data of a single maize plant were successfully extracted, from which stem information was accurately measured to obtain accurate plant height information. In this study, we will concentrate on the analysis of individual maize plants. Leveraging the advantages of solid-state LiDAR technology in precisely capturing phenotypic information, the data processing approach for individual maize plants, as compared to an entire maize community, will better restore the maize's original growth patterns. This will enable the acquisition of more accurate maize plant height information and more clearly demonstrate the potential of solid-state LiDAR in capturing detailed phenotypic information. To enhance the universality of the research findings, this study meticulously selected key growth stages of maize for data validation and comparison, encompassing the tasseling, silking, and maturity phases. At these crucial stages, 20 maize plants at the tasseling stage, 40 at the flowering stage, and 40 at the maturity stage were randomly selected, totaling 100 samples for analysis. Each sample not only included actual measurement values but also included plant height information extracted using point cloud technology. The observation period was set from 20 June to 20 September 2021. This period encompasses the three key growth stages of maize described above, and each growth stage included one round of data collection, with three rounds of data collection each, each spaced about a week apart, for a total of nine data collections. To ensure the accuracy and reliability of the data, all collections were performed at noon when the natural wind speed was controlled within the range of 0 to 1.5 m/s and the weather was clear. The findings demonstrate that the root mean square error (RMSE) of the maize plant height data, procured through LiDAR technology, stands at 1.27 cm, the mean absolute percentage error (MAPE) hovers around 0.77%, and the peak R2 value attained is 0.99. These metrics collectively attest to the method's ongoing high efficiency and precision in capturing the plant height information. In the comparative study of different stem growth stages, especially at the maturity stage, the MAPE of the plant height was reduced to 0.57%, which is a significant improvement compared to the performance at the nodulation and sprouting stage. These results effectively demonstrate that the maize phenotypic information extraction method based on solid-state LiDAR technology is not only highly accurate and effective but is also effective on individual plants, which provides a reliable reference for applying the technique to a wider range of plant populations and extending it to the whole farmland. [ABSTRACT FROM AUTHOR]

Glycosylation, a dynamic modification prevalent in viruses and higher eukaryotes, is principally regulated by uridine diphosphate (UDP)-glycosyltransferases (UGTs) in plants. Although UGTs are involved in plant defense responses, their responses to most pathogens, especially plant viruses, remain unclear. Here, we aimed to identify UGTs in the whole genome of Nicotiana benthamiana (N. benthamiana) and to analyze their function in Chinese wheat mosaic virus (CWMV) infection. A total of 147 NbUGTs were identified in N. benthamiana. To conduct a phylogenetic analysis, the UGT protein sequences of N. benthamiana and Arabidopsis thaliana were aligned. The gene structure and conserved motifs of the UGTs were also analyzed. Additionally, the physicochemical properties and predictable subcellular localization were examined in detail. Analysis of cis-acting elements in the putative promoter revealed that NbUGTs were involved in temperature, defense, and hormone responses. The expression levels of 20 NbUGTs containing defense-related cis-acting elements were assessed in CWMV-infected N. benthamiana, revealing a significant upregulation of 8 NbUGTs. Subcellular localization analysis of three NbUGTs (NbUGT12, NbUGT16 and NbUGT17) revealed their predominant localization in the cytoplasm of N. benthamiana leaves, and NbUGT12 was also distributed in the chloroplasts. CWMV infection did not alter the subcellular localization of NbUGT12, NbUGT16, and NbUGT17. Transient overexpression of NbUGT12, NbUGT16, and NbUGT17 enhanced CWMV infection, whereas the knockdown of NbUGT12, NbUGT16 and NbUGT17 inhibited CWMV infection in N. benthamiana. These NbUGTs could serve as potential susceptibility genes to facilitate CWMV infection. Overall, the findings throw light on the evolution and function of NbUGTs. [ABSTRACT FROM AUTHOR]

Hydrogen‐bonded organic frameworks (HOFs) are porous crystalline materials. The pores in HOFs are usually non‐covalent extrinsic pores constructed through the formation of the framework. Supramolecular macrocycles with intrinsic pores in their structures are good candidates for constructing HOFs with intrinsic pores from the macrocycles themselves, thus leading to hierarchically porous structures. Combining the macrocycle and HOFs will endow these hierarchically porous materials with enhanced properties and special functionalities. This review summarizes recent advances in macrocycle‐based HOFs, including the macrocycles used for constructing HOFs, the hierarchically porous structures of the HOFs, and the applications induced by the hierarchically HOFs porous structures. This review provides insights for future research on macrocycle‐based hierarchically porous HOFs and the appropriate applications of the unique structures. [ABSTRACT FROM AUTHOR]

A nitrogen-rich graphdiyne (HATN-GDY) material containing electrochemical active hexaazatrinaphthylene units was successfully prepared. HATN-GDY exhibits a superior specific capacity of 2139 mA h g−1 and firm long-term stability due to the unique 2D π-conjugated structure and the large in-plane N-cavities. [ABSTRACT FROM AUTHOR]