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After the occurrence of mine water inrush, choosing the appropriate emergency evacuation path is very important to reduce the casualty and the mine accident level. The traditional Dijkstra algorithm can not be effectively applied to the dynamic environment of mine water inrush. It can only statically plan a single optimal escape path. In view of the limitations of this algorithm, the time equivalent length is introduced to optimize the traditional Dijkstra algorithm to realize the dynamic change of the optimal escape path with time and water level height. Moreover, the optimized Dijkstra algorithm is combined with the K optimal path algorithm to realize the dynamic planning of multiple optimal escape paths. Field application shows that the optimized dynamic D-K algorithm can be effectively applied to mine water inrush with characteristics of randomness, dynamics and complex, which can provide important decision support for affected personnel to choose emergency escape path.

Abstract Background To use an automated system exploiting the advantages of both a neural network and radiomics for analysis of non‐calcified predominant plaque (NCPP). Methods This study retrospectively included 234 patients. Using the workflow of the previous study, the coronary artery was first segmented, images containing plaques were then extracted, and a classifier was built to identify non‐calcified predominant plaques. Radiomics feature analysis and a visualization tool were used to better distinguish NCPP from other plaques. Results Twenty‐six representative radiomics features were selected. DenseNet achieved an area under the curve of 0.889, which was significantly larger (p = 0.001) than that obtained using a gradient‐boosted decision tree (0.859). The feature variances and energy features in calcified predominant plaque were both different from those in NCPP. Conclusions Our automated system provided high‐accuracy analysis of vulnerable plaques using a deep learning approach and predicted useful features of NCPP using a radiomics‐based approach.

Abstract The structural diversity of biological macromolecules in different environments contributes complexity to enzymological processes vital for cellular functions. Fluorescence resonance energy transfer and electron microscopy are used to investigate the enzymatic reaction of T4 DNA ligase catalyzing the ligation of nicked DNA. The data show that both the ligase–AMP complex and the ligase–AMP–DNA complex can have four conformations. This finding suggests the parallel occurrence of four ligation reaction pathways, each characterized by specific conformations of the ligase–AMP complex that persist in the ligase–AMP–DNA complex. Notably, these complexes have DNA bending angles of ≈0°, 20°, 60°, or 100°. The mechanism of parallel reactions challenges the conventional notion of simple sequential reaction steps occurring among multiple conformations. The results provide insights into the dynamic conformational changes and the versatile attributes of T4 DNA ligase and suggest that the parallel multiple reaction pathways may correspond to diverse T4 DNA ligase functions. This mechanism may potentially have evolved as an adaptive strategy across evolutionary history to navigate complex environments.

Abstract Background Kernel dehydration is an important factor for the mechanized harvest in maize. Kernel moisture content (KMC) and kernel dehydration rate (KDR) are important indicators for kernel dehydration. Although quantitative trait loci and genes related to KMC have been identified, where most of them only focus on the KMC at harvest, these are still far from sufficient to explain all genetic variations, and the relevant regulatory mechanisms are still unclear. In this study, we tried to reveal the key proteins and metabolites related to kernel dehydration in proteome and metabolome levels. Moreover, we preliminarily explored the relevant metabolic pathways that affect kernel dehydration combined proteome and metabolome. These results could accelerate the development of further mechanized maize technologies. Results In this study, three maize inbred lines (KB182, KB207, and KB020) with different KMC and KDR were subjected to proteomic analysis 35, 42, and 49 days after pollination (DAP). In total, 8,358 proteins were quantified, and 2,779 of them were differentially expressed proteins in different inbred lines or at different stages. By comparative analysis, K-means cluster, and weighted gene co-expression network analysis based on the proteome data, some important proteins were identified, which are involved in carbohydrate metabolism, stress and defense response, lipid metabolism, and seed development. Through metabolomics analysis of KB182 and KB020 kernels at 42 DAP, 18 significantly different metabolites, including glucose, fructose, proline, and glycerol, were identified. Conclusions In sum, we inferred that kernel dehydration could be regulated through carbohydrate metabolism, antioxidant systems, and late embryogenesis abundant protein and heat shock protein expression, all of which were considered as important regulatory factors during kernel dehydration process. These results shed light on kernel dehydration and provide new insights into developing cultivars with low moisture content.

The clustered regularly interspaced short palindromic repeat (CRISPR)-Cas12a system is a powerful tool in gene editing; however, crRNA-DNA mismatches might induce unwanted cleavage events, especially at the distal end of the PAM. To minimize this limitation, we engineered a hyper fidelity AsCas12a variant carrying the mutations S186A/R301A/T315A/Q1014A/K414A (termed HyperFi-As) by modifying amino acid residues interacting with the target DNA and crRNA strand. HyperFi-As retains on-target activities comparable to wild-type AsCas12a (AsCas12aWT) in human cells. We demonstrated that HyperFi-As has dramatically reduced off-target effects in human cells, and HyperFi-As possessed notably a lower tolerance to mismatch at the position of the PAM-distal region compared with the wild type. Further, a modified single-molecule DNA unzipping assay at proper constant force was applied to evaluate the stability and transient stages of the CRISPR/Cas ribonucleoprotein (RNP) complex. Multiple states were sensitively detected during the disassembly of the DNA-Cas12a-crRNA complexes. On off-target DNA substrates, the HyperFi-As-crRNA was harder to maintain the R-loop complex state compared to the AsCas12aWT, which could explain exactly why the HyperFi-As has low off-targeting effects in human cells. Our findings provide a novel version of AsCas12a variant with low off-target effects, especially capable of dealing with the high off-targeting in the distal region from the PAM. An insight into how the AsCas12a variant behaves at off-target sites was also revealed at the single-molecule level and the unzipping assay to evaluate multiple states of CRISPR/Cas RNP complexes might be greatly helpful for a deep understanding of how CRISPR/Cas behaves and how to engineer it in future.

The heavy reliance on fossil-based industries for basic chemicals not only contributes to severe global environmental problems but also hampers the sustainable development of the whole society. In addressing this issue, electrocatalysis utilizing biomass-derived platform chemicals provides a promising solution for the directed preparation of high-value chemicals. Among the various electrocatalysts, the remarkable appeal of COFs-based electrocatalysts has engendered great enthusiasm among researchers over the past decade due to the well-defined structure and large surface area of COFs. In this focused review, we highlight vital perspectives on the design, synthesis, and progress of COFs-based electrocatalysts in the electrocatalytic upgrading of biomass-derived platform chemicals. We provide a rational design of COFs-based electrocatalysts by incorporating metal species into the COFs frameworks and then regulate the local coordination environment and microstructure to facilitate efficient access to active centers, mass transportation, and electron transfer. This review offers a comprehensive understanding of the design principles underlying COFs-based electrocatalysts for platform molecules and its derivatives. Specifically, we thoroughly investigate the relationship between structure and performance, as well as synergistic effects within COFs-based electrocatalysts, aiming to shed light on the future design of next-generation electrocatalysts.

Abiotic stresses pose a major increasing problem for the cultivation of maize. Autophagy plays a vital role in recycling and re-utilizing nutrients and adapting to stress. However, the role of autophagy in the response to abiotic stress in maize has not yet been investigated. Here, ZmATG3, which is essential for ATG8-PE conjugation, was isolated from the maize inbred line B73. The ATG3 sequence was conserved, including the C-terminal domains with HPC and FLKF motifs and the catalytic domain in different species. The promoter of the ZmATG3 gene contained a number of elements involved in responses to environmental stresses or hormones. Heterologous expression of ZmATG3 in yeast promoted the growth of strain under salt, mannitol, and low-nitrogen stress. The expression of ZmATG3 could be altered by various types of abiotic stress (200 mM NaCl, 200 mM mannitol, low N) and exogenous hormones (500 µM ABA). GUS staining analysis of ZmATG3-GUS transgenic Arabidopsis revealed that GUS gene activity increased after abiotic treatment. ZmATG3-overexpressing Arabidopsis plants had higher osmotic and salinity stress tolerance than wild-type plants. Overexpression of ZmATG3 up-regulated the expression of other AtATGs (AtATG3, AtATG5, and AtATG8b) under NaCl, mannitol and LN stress. These findings demonstrate that overexpression of ZmATG3 can improve tolerance to multiple abiotic stresses.

Abstract Accurate quantification of the absorption properties of brown carbon (BrC) aerosols is crucial to assess the Earth‐atmosphere radiative impacts of BrC. However, the BrC absorption properties were often misestimated in field observations, due to neglecting the contribution of dust absorption. This study solved this problem by coupling a method for calculating the dust concentration into the traditional model for quantifying BrC absorption. The results show that dust absorption was up to 16.8% of the sum of BrC and dust absorption in northwestern China. The potential contribution of dust to the sum of BrC and dust absorption was significantly higher in the Asia‐located studies (0.4%–16.8%) than in the Americas‐located (

Acid soils occupy approximately 50% of potentially arable lands. Improving crop productivity in acid soils, therefore, will be crucial for ensuring food security and agricultural sustainability. High soil acidity often coexists with phosphorus (P) deficiency and aluminum (Al) toxicity, a combination that severely impedes crop growth and yield across wide areas. As roots explore soil for the nutrients and water required for plant growth and development, they also sense and respond to below-ground stresses. Within the terrestrial context of widespread P deficiency and Al toxicity pressures, plants, particularly roots, have evolved a variety of mechanisms for adapting to these stresses. As legumes, soybean (Glycine max) plants may acquire nitrogen (N) through symbiotic nitrogen fixation (SNF), an adaptation that can be useful for mitigating excessive N fertilizer use, either directly as leguminous crop participants in rotation and intercropping systems, or secondarily as green manure cover crops. In this review, we investigate legumes, especially soybean, for recent advances in our understanding of root-based mechanisms linked with root architecture modification, exudation and symbiosis, together with associated genetic and molecular strategies in adaptation to individual and/or interacting P and Al conditions in acid soils. We propose that breeding legume cultivars with superior nutrient efficiency and/or Al tolerance traits through genetic selection might become a potentially powerful strategy for producing crop varieties capable of maintaining or improving yields in more stressful soil conditions subjected to increasingly challenging environmental conditions.

Abstract The experimental study on the variation law of coal fracture and stress was carried out in the laboratory and engineering fields, respectively. A multiparameter monitoring system including electromagnetic radiation and a high‐speed camera was built, and three stress paths, uniaxial compression, cyclic loading, and graded loading, were used to monitor the dynamic expansion process of surface cracks during uniaxial compression failure of coal specimens. Through the quantitative analysis of the electromagnetic radiation signal in the crack propagation process, it is found that the electromagnetic radiation and the stress change trend are consistent, and the electromagnetic radiation signal is ahead of the failure of coal‐generating rock mass 1–2 s. The surface crack changes after the peak value of electromagnetic radiation and presents a stepwise growth trend, crack length changes on the millisecond time scale, and the crack propagation speed is about 2000 mm/s. The surface cracks appear when the stress reaches a certain degree, and the propagation of the principal cracks is consistent with the failure of the specimen. The electromagnetic radiation value of the coal mass from static period to dynamic is analyzed by using electromagnetic radiation at the engineering site, and it was found that the electromagnetic radiation is consistent with the stress distribution of the mining face. Through normalization, the variation rule of electromagnetic radiation in laboratory and engineering sites is similar, but the peak value of electromagnetic radiation in engineering sites is more significant. Therefore, electromagnetic radiation has a good monitoring effect on the stress distribution and cracks propagation of underground coal mining working faces, which could guide the layout of underground drilling.

Monitoring the temperature of the coal gangue mountains is fundamental to preventing their spontaneous combustion. However, the existing temperature monitoring systems fail to achieve stable, pollution-free temperature monitoring without affecting vegetation growth in these mountains. To address this issue, this work proposes a flexible thermoelectric device (FTD) based on a protrusion-structured liquid metal elastomer (LME). Utilizing a high-thermal-conductivity LME, the FTD adheres closely to the surface of the gravity heat pipe (GHP), ensuring compatibility between FTD and the curved surface of the GHP. Simultaneously, employing a low-thermal-conductivity elastomer helps concentrate heat onto FTD, thereby enhancing thermoelectric power generation efficiency. Additionally, the impact of the shape, size, and height of the protrusion structure at the cold end of the GHP on its efficiency was also investigated. The practical application of FTD on GHP was demonstrated.

Tricyclene, a tricyclic monoterpene naturally occurring in plant essential oils, holds potential for the development of medicinal and fuel applications. In this study, we successfully synthesized tricyclene in E. coli by introducing the heterologous mevalonate (MVA) pathway along with Abies grandis geranyl diphosphate synthase (GPPS) and Nicotiana sylvestris tricyclene synthase (TS) XP_009791411. Initially, the shake-flask fermentation at 30 ◦C yielded a tricyclene titer of 0.060 mg/L. By increasing the copy number of the TS-coding gene, we achieved a titer of 0.103 mg/L. To further enhance tricyclene production, optimal truncation in the N-terminal region of TS XP_009791411 resulted in an impressive highest titer of 47.671 mg/L, approximately a 794.5-fold improvement compared to its wild-type counterpart. To the best of our knowledge, this is the highest titer of the heterologous synthesis of tricyclene in E. coli. The SDS-PAGE analysis revealed that lowering induction temperature and truncating the random coil N-terminal region effectively improved TS solubility, which was closely associated with tricyclene production levels. Furthermore, by truncating other TSs, the titers of tricyclene were improved to different degrees.

Abstract Central to homologous recombination (HR) is the assembly of Rad51 recombinase on single-strand DNA (ssDNA), forming the Rad51-ssDNA filament. How the Rad51 filament is efficiently established and sustained remains partially understood. Here, we find that the yeast ubiquitin ligase Bre1 and its human homolog RNF20, a tumor suppressor, function as recombination mediators, promoting Rad51 filament formation and subsequent reactions via multiple mechanisms independent of their ligase activities. We show that Bre1/RNF20 interacts with Rad51, directs Rad51 to ssDNA, and facilitates Rad51-ssDNA filament assembly and strand exchange in vitro. In parallel, Bre1/RNF20 interacts with the Srs2 or FBH1 helicase to counteract their disrupting effect on the Rad51 filament. We demonstrate that the above functions of Bre1/RNF20 contribute to HR repair in cells in a manner additive to the mediator protein Rad52 in yeast or BRCA2 in human. Thus, Bre1/RNF20 provides an additional layer of mechanism to directly control Rad51 filament dynamics.

Carbon fiber reinforced polyamide-imide (CF/PAI) composites are potential candidates for high temperature applications under high stress conditions. However, the structure–property relationships of CF/PAI are not clear. This work presented an experimental investigation into the influence of interfacial modification and heat treatment on the microstructures and mechanical properties of CF/PAI composites. The CF/PAI interfacial interactions were improved by the combined effect of chemical bonding between the PAI-compatible sizing and CF as well as hydrogen bonding between the sizing and matrix. Meanwhile, heat treatment enhanced the modulus of matrix, which was beneficial to stress transfer in the interfacial region. Therefore, the interlaminar shear strength (ILSS), flexural strength, and flexural modulus of RS0.6-CF/PAI composites (the concentration of PAI-compatible sizing agent was 0.6 wt%) were remarkably improved by 81.3%, 23.7%, and 39.1% compared with the control specimen. Microstructure examinations of modified and unmodified CF/PAI composites showed that both interfacial modification and heat treatment played an important role in the transitions of failure mode under interlaminar shear loading and flexural loading. These findings provide an effective method to tailor the microstructures of CF/PAI composites for achieving the desired properties.

In the research area of the CT digital coal petrography, the selection of gray threshold directly affects the accuracy of spatial structure remodeling. To allow the pores and fissures space remodeling data to more accurately represent the real structure and improve the reliability of research on microscopic seepage of coal rock, the mapping relation between the CT digital coal rock porosity and gray threshold is established. Also, the distribution rule of gray threshold is adopted to conduct a quantitative analysis of the development features of pore, fissure and matrix. The Bi-PTI (Biphasic Pore Threshold Inversion) model is established for the identification of pore and fissure structures. The value inversion of the optimal gray threshold of pore and fissure based on the CT scanning data of metamorphic coal, and the comparison of porosity obtained with the model against the mercury injection test value are conducted. On the basis of the optimal gray threshold inversion results, the spatial structure of pore and fissure is remodeled and compared with the Otsu model through the parameters of spatial structure and topological structure. Research results indicate that the porosity based on the CT digital coal petrography is in asymmetrical S-shaped distribution as the threshold value increases, with the features of exponential increase and logarithmic climb at different sections. The Bi-PTI model can fairly reflect the mapping relation between porosity and gray threshold, and represent the development features of pore, fissure and matrix. The porosity calculated through the Otsu model is as high as over 70%, the porosity calculated by the MP-Otsu model is greatly affected by the mineral content while that calculated with the Bi-PTI model ranges from 0.40% to 16.22%, more close to the mercury injection test data. The Otsu model is most likely to neglect the topological structure with partial pores and fissures. The MP-Otsu model is not effective for constructing the topology of coal samples with low mineral content, while the Bi-PTI model can better identify the topological features in the locations of the defect and faithfully restore the pore throat abundance and connectivity in the pore and fissure topology.

The Unmanned Aerial Vehicle (UAV) swarm cooperative networks across diverse domains present significant challenges in management and control to maximize collaborative efficiency, particularly in applications for large-scale and dynamic environments where real-time coordination is essential. This challenge has led to the development of a UAV swarm cooperative network flow prediction model, facilitating the strategic anticipation of network dynamics. A novel algorithm for distributed, finite-time cooperative control is introduced, grounded in this model. This algorithm optimizes the operational efficiency and control precision of UAV systems, while simultaneously augmenting the collaborative efficiency and stability of the UAV swarms. It marks a significant advancement in distributed computing strategies, offering a viable solution for the real-time coordination challenges in extensive UAV swarm cooperative networks. The proposed approach leverages multi-agent technology, integrating spatial-temporal constraints, location limitations, and path selection in cooperative behavior for dynamic and effective network management. This study not only enhances the understanding of UAV swarm dynamics but also contributes to the practical application of UAV swarms in areas requiring precise coordination and robust network stability.

The electric heating process for lifting heavy oil has been widely applied. However, research on its temperature field laws mostly focuses on onshore heavy oil wells, while research offshore is limited. Therefore, based on the energy conservation equation and heat transfer theory, a transient one-dimensional wellbore temperature model coupled with the temperature and viscosity of heavy oil and considering the effect of time was developed. In order to verify the accuracy of the model, the results of the previous model were used for comparison with the present model, and the results showed that the model has good accuracy. The results show that a reasonable selection of the process parameters of electric heating can increase the production of heavy oil while saving development costs and improving the economic benefits of the oilfield. The conclusions and recommendations of this paper can provide a theoretical basis and guiding suggestions for the optimal design of process parameters for lifting heavy oil using an offshore electric heating process.

With the popularization of better network access and the penetration of personal smartphones in today’s world, the explosion of multi-modal data, particularly opinionated video messages, has created urgent demands and immense opportunities for Multi-Modal Sentiment Analysis (MSA). Deep learning with the attention mechanism has served as the foundation technique for most state-of-the-art MSA models due to its ability to learn complex inter- and intra-relationships among different modalities embedded in video messages, both temporally and spatially. However, modal fusion is still a major challenge due to the vast feature space created by the interactions among different data modalities. To address the modal fusion challenge, we propose an MSA algorithm based on deep learning and the attention mechanism, namely the Mixture of Attention Variants for Modal Fusion (MAVMF). The MAVMF algorithm includes a two-stage process: in stage one, self-attention is applied to effectively extract image and text features, and the dependency relationships in the context of video discourse are captured by a bidirectional gated recurrent neural module; in stage two, four multi-modal attention variants are leveraged to learn the emotional contributions of important features from different modalities. Our proposed approach is end-to-end and has been shown to achieve a superior performance to the state-of-the-art algorithms when tested with two largest public datasets, CMU-MOSI and CMU-MOSEI.

Maize is one of the major crops that has demonstrated success in the utilization of heterosis. Developing high-yield hybrids is a crucial part of plant breeding to secure global food demand. In this study, we conducted a genome-wide association study (GWAS) for 10 agronomic traits using a typical breeder population comprised 442 single-cross hybrids by evaluating additive, dominance, and epistatic effects. A total of 49 significant single nucleotide polymorphisms (SNPs) and 69 significant pairs of epistasis were identified, explaining 26.2% to 64.3% of the phenotypic variation across the 10 traits. The enrichment of favorable genotypes is significantly correlated to the corresponding phenotype. In the confident region of the associated site, 532 protein-coding genes were discovered. Among these genes, the Zm00001d044211 candidate gene was found to negatively regulate starch synthesis and potentially impact yield. This typical breeding population provided a valuable resource for dissecting the genetic architecture of yield-related traits. We proposed a novel mating strategy to increase the GWAS efficiency without utilizing more resources. Finally, we analyzed the enrichment of favorable alleles in the Shaan A and Shaan B groups, as well as in each inbred line. Our breeding practice led to consistent results. Not only does this study demonstrate the feasibility of GWAS in F1 hybrid populations, it also provides a valuable basis for further molecular biology and breeding research.

In this paper, we prove the existence of a positive ground state solution to the following coupled system involving nonlinear Schrödinger equations: \begin{equation*} \begin{cases} -\Delta u+V_1(x)u =f_1(x,u)+\lambda(x) v,& x\in \mathbb{R}^2, \\ -\Delta v+V_2(x)v=f_2(x,v)+\lambda(x) u,& x\in \mathbb{R}^2, \end{cases} \end{equation*} where $ \lambda, V_1, V_2\in C(\mathbb{R}^2,(0,+\infty))$ and $ f_1, f_2:\mathbb{R}^2\times \mathbb{R} \rightarrow \mathbb{R} $ have critical exponential growth in the sense of Trudinger–Moser inequality. The potentials $ V_1(x) $ and $ V_2(x) $ satisfy a condition involving the coupling term $ \lambda(x) $, namely $ 0

Identifying desirable genotypes with the best performance in diverse environments is a perpetual aim of plant breeding, and the interaction between genotype and environment (G × E) always plays a key role. This study was conducted to elucidate the genetic behaviour of different hybrid combinations at various densities in diverse environments. According to a line × tester design, 32 hybrid combinations were obtained from 16 inbred individuals crossed with two testers and planted at three locations at three density levels (45,000, 67,500 and 90,000 plants ha−1) during 2014−2017. Genotype (G), environment (E) and the interaction of genotype and environment (G × E) significantly affected grain yield at different densities. Increasing planting density enhanced grain yield and improved the efficiency of germplasm screening, where the effect of location on grain yield at different densities was larger than that of year and the GCA was larger than the SCA. Finally, four inbred lines (KB102, KB081, KA105, and KB106) with a high GCA, environmental adaptability, and several combinations using them as parents have been approved in ShannXi Province and National of China. In conclusion, the evaluation of combining ability at multiple densities and locations can effectively screen inbred lines and improve breeding efficiency.

In this work, artificial intelligence (AI) is trained to “study” optical fibers as an AI optical fiber scientist. The dataset is constructed on the structural parameters and confinement loss of hollow-core anti-resonant fibers and is divided into different datasets. An effective approach to overcome the non-uniqueness challenge of inverse designs is the tandem neural network (T-NN), which consists of a forward prediction model and an inverse design model, which are trained by different datasets. The impact of the hyperparameter on the performance of the proposed model is also studied. For the forward prediction model, the mean square error reaches the lowest value of 0.0007 with 6 hidden layers; the nodes of each hidden layer are 800, and the corresponding coefficient of determination R2 is 0.9154. Moreover, the R2CL of the T-NN can reach the maximum value of 0.9881 for the dataset-1-0. The comparison between the target, prediction result, and calculation result proves that the proposed approach is an effective way to design hollow-core anti-resonant fibers intelligently. Compared with current numerical simulation methods, the presented AI model based on the T-NN is more “intelligent”. This study can both accelerate the design of hollow-core anti-resonant fibers and provide guidance on the development of AI scientists in optics.

Selective photocatalysis offers an alternative green and economically competitive approach for valuable fine chemical synthesis. In this research, the Ni@C/TiO2-Z catalyst was prepared for the efficient photocatalytic oxidation of various aromatic alcohols. Interestingly, the selectivity of the reaction products is affected by the absorbance of the solvents used in the reaction. The oxidation ability of the reaction system is stronger when the absorption peaks of the solvents are closer to light source wavelengths. Therefore, the reaction tends to generate aldehyde in acetonitrile and acid in ethyl acetate, which allows for the manipulation of product selectivity by choosing the solvent.

Maize, the most widely planted and highest yielding of the three major crops in the world, requires the development and breeding of new varieties to accommodate the shift towards mechanized harvesting. However, the moisture content of kernels during harvest poses a significant challenge to mechanized harvesting, leading to seed breakage and increased storage costs. Previous studies highlighted the importance of LEA (Late Embryogenesis Abundant) members in regulating kernel dehydration. In this study, we aimed to gain a better understanding of the relationship between the LEA family and grain dehydration in maize. Through expression pattern analysis of maize, we identified 52 LEA genes (ZmLEAs) distributed across 10 chromosomes, organized into seven subgroups based on phylogenetic analysis, gene structure, and conserved motifs. Evolutionary and selective pressure analysis revealed that the amplification of ZmLEA genes primarily resulted from whole-genome or fragment replication events, with strong purifying selection effects during evolution. Furthermore, the transcriptome data of kernels of two maize inbred lines with varying dehydration rates at different developmental stages showed that 14 ZmLEA genes were expressed differentially in the two inbreds. This suggested that the ZmLEA genes might participate in regulating the kernel dehydration rate (KDR) in maize. Overall, this study enhances our understanding of the ZmLEA family and provides a foundation for further research into its role in regulating genes associated with grain dehydration in maize.

Rheumatoid arthritis (RA) is an autoimmune disease characterized by synovial inflammation, pannus formation, and bone and cartilage damage. It has a high disability rate. The hypoxic microenvironment of RA joints can cause reactive oxygen species (ROS) accumulation and mitochondrial damage, which not only affect the metabolic processes of immune cells and pathological changes in fibroblastic synovial cells but also upregulate the expression of several inflammatory pathways, ultimately promoting inflammation. Additionally, ROS and mitochondrial damage are involved in angiogenesis and bone destruction, thereby accelerating RA progression. In this review, we highlighted the effects of ROS accumulation and mitochondrial damage on inflammatory response, angiogenesis, bone and cartilage damage in RA. Additionally, we summarized therapies that target ROS or mitochondria to relieve RA symptoms and discuss the gaps in research and existing controversies, hoping to provide new ideas for research in this area and insights for targeted drug development in RA.

Offshore heavy oil resources are abundant, but they have greater difficulty and higher costs compared to onshore extraction. When crude oil flows through the seawater section, the temperature of the crude oil decreases faster, making it susceptible to solidification in the wellbore and resulting in lower well production. The cooling of crude oil becomes more pronounced in deep-water wellbore. However, the injection of low-temperature gas will have a cooling effect on the formation production fluid, which will have a negative effect. The model analyzes the effects of coiled tubing running depth, gas injection temperature, gas injection volume, coiled tubing diameter, and crude oil production on the temperature distribution of heavy oil in deep-water and shallow water wellbores. We propose recommendations for the selection of each parameter for deep and shallow water environments by analyzing and summarizing the laws.

The catalytic oxidation of lignin into phenolic monomers with aldehydes as the main products is very attractive but the yield of desired monomers is still limited. The aim of this work is to investigate the reaction pathway for the conversion of lignin to aldehydes and aldehydes stabilization in alkaline media. Studies on pure aldehydes stability revealed that over-oxidation to carboxylic acids and condensation are crucial factors of limited yield. A chemical protection method using aniline as the capping agent was applied to the depolymerization of real lignin and achieved the theoretical maximum monomer yield within 30 min at 160 °C.

The low-frequency disturbances transmitted by flexible cables are difficult to be attenuated for a novel disturbance-free payload spacecraft, which decreases the payload’s pointing accuracy and stability. In this research, a new spacecraft configuration with a high-precision inertial reference unit composed of capacitive sensors and a spherical test mass is proposed. The disturbance attenuation and pointing control system is subdivided into four interconnected control loops. The payload can be isolated from disturbances in the all-frequency band by the active vibration isolation control loop and the drag-free control loops, and its high-precision pointing requirement can be satisfied with the attitude pointing control loop and the attitude tracking control loop. An integrated control strategy is proposed, and the control system is decoupled into 12 single-input single-output control loops by pre-compensating, which lays the foundation for feedback design. Through the amplitude-frequency response analysis, the control bandwidth is designed according to the Proportional-Integral-Differentive control algorithm. The numerical simulations show that the disturbance attenuation performance is better than −20 dB in the all-frequency band, and the pointing accuracy and the pointing stability are better than 10−6 deg and 10−7 deg/s, respectively. The new spacecraft configuration and the disturbance attenuation and pointing control system provide a general technical solution for payloads with high-precision and high-stability requirements.

Dielectric breakdown of a vertical Gas insulated transmission line (GIL) caused by demixing of the mixture of SF6/N2 is studied by both theoretical simulation and the experimental measure. The mechanism and the threshhold of the demixing is addressed quantitatively. The potential risk of the segregation of the molecules by forming dimer or trimer under the high voltage is excluded by the quantum mechanics simulation in microscopic scale and the molecular simulation in mesoscopic scale. In macroscopic scale, the distribution of the mixture depending on the length of the tube is computed by the statistical physics quantitatively.

Aiming at the decrease of tracking accuracy caused by nonlinear friction and strong coupling of the flexible upper-limb exoskeleton, an improved super-twisting sliding mode controller (ISTSMC) is proposed. Compared with the conventional super twisted sliding mode controller (STSMC), this method can replace the switching function under the integral term with a nonsmooth term, resulting in a faster response, less vibration when performing trajectory tracking, and reduced steady-state error. The introduction of the nonsmooth term causes the controller to have a stronger anti-interference ability. At the same time, the parameters of the ISTSMC can be adjusted in order to achieve the expected control performance. The effectiveness and feasibility of the proposed control algorithm are verified through experiments.

To solve situation of high-sulfur copper slag utilization, an innovative technology was proposed for oxidation roasting with composite agglomerates. The oxidation-roasting process was studied by factage7.3 software. The thermodynamics were calculated about sulfur removal, sulfur adsorption and decomposition. The adsorption of sulfur oxides and microstructure evolution were analyzed via an oxidation roasting experiment and SEM-EDS. The results show that the matte and AsxSy in the matrix could be effectively removed via oxidation roasting in an oxygen atmosphere; the sulfoxide was adsorbed to produce CaSO4. The Fe2SiO4 decomposition could be realized at suitable roasting temperature and in an oxygen atmosphere. This is helpful for the magnetic separation of iron and silicon. The thermodynamic and experimental results were preliminarily confirmed to be available in the innovative process.

Liquid carbon dioxide phase transition fracturing technology (LCPTF) is an effective method to increase coal seam permeability, but there are many factors that affect the fracturing effect. Blasting pressure, vent diameter, and blasting time are important factors that affect the fracturing effect. However, very limited studies were performed in this regard. Therefore, in this paper, a multifield coupled model for fracturing coal bodies by LCPTF is established; the effect of blasting pressure, vent diameter, and blasting time on blasting effectiveness was studied; a numerical simulation study based on the seepage field and stress field is performed and verified in the field based on the specific geological conditions of Hujiahe mine. Experimental results show that the fracturing radius and the maximum displacement of coal increase with the increase of blasting pressure, and the fracturing radius is 4.875 m when the blasting pressure is 280 MPa, which is 9.6% higher than that of 200 MPa, and the effect is obvious. The fracturing effect improves with the increase of vent diameter but the effect is modest. In general, the fracturing effect increases with the increase of CO2 impact duration, and when there is no gas impact, the fracturing radius basically remains the same. The maximum displacement gradually decreases with time, and its maximum displacement of the coal body decreases by 33.69% at 200 s. After field blasting, the gas flow attenuation coefficient was reduced by up to 85.7% and the effective radius of influence was between 4 and 5 m.

This study is aimed at detecting small faults in coal seams. With coal seams of different buried depths in Luling Coal Mine, Yuenan Coal Mine, and Sihe Coal Mine with obvious difference in hardness and outburst hazards selected as the research objects, the morphological characteristics of a sample particle size such as the Rosin-Rammler distribution function, average particle size, cumulative mass distribution, and mechanical parameters such as particle strength and F value were statistically analyzed through drill cuttings related to sampling points at different positions of faults already known. The results show that the effect of tectonic stress reduces the strength and permeability of the coal after the borehole enters the fault damage zone, resulting in abnormal fluctuations in the morphological characteristics of the drill cuttings. Correspondingly, large-size particles account for a high percentage. The weight analysis discloses that the characteristic particle size of the Rosin-Rammler distribution function has the greatest influence on the determination of fault existence. The analysis of drill cutting characteristics conduces to detecting the distribution of small faults, helps to improve the utilization of mine information, and is of great significance for accident prevention and control.

Regarding the three expansion modes of hydraulic fractures at the interface of a coal measure composite reservoir (arrested, deflection, and penetration), based on the coupling theory of fluid flow and solid elastic deformation, a criterion that considers the influences of the injection parameters (fracturing fluid injection rate and viscosity) is established to predict the propagation path of hydraulic fractures at the interface of a composite reservoir. The criterion judges the propagation behavior of the fractures by comparing the water pressure in the wellbore and the critical seam pressure of the penetration and deflection. The controlled variable method is used to analyze the influences of the various factors on the propagation behavior of hydraulic fractures at the interface between layers. The results show that the differences in in situ stress, the interface cohesion, and the included angle mainly affect the critical seam pressure of the fracture deflection. The differences in elastic modulus, fluid injection rate, and fracturing fluid viscosity directly affect the water pressure in the wellbore. The difference in the fracture toughness mainly affects the crack propagation path by affecting the critical seam pressure of the deflection. The smaller the difference in the in situ stress is, the more likely it is that the hydraulic fractures will penetrate the layer. Larger differences in the fracture toughness between layers, interfacial cohesion, fluid injection rate, and fracturing fluid viscosity are more conducive to the hydraulic fractures penetrating the layer. When the angle between the hydraulic fractures and the interface is 25–55°, the hydraulic fracture is more likely to expand along the interface. This criterion takes into account the influences of the injection parameters and is of great significance to gaining a better understanding of the propagation behavior of hydraulic fractures at an interlayer interface.

For the evaluation of college students’ physical health, the t-test, one-way ANOVA test, fuzzy comprehensive evaluation, and other methods were used to establish the models of back generation test, ANOVA, and fuzzy comprehensive evaluation; and Matlab, Excel, VBA, and other software programming were used to derive the significant influence of body weight on college students’ physical health, no significant difference of students’ physical health in different places of birth and the comprehensive score of college students’ physical health. The results such as the comprehensive score of health evaluation were used to analyze the physical health test results of college students in Zhuzhou city colleges and universities in the context of the promulgation of the new Student Physical Health Standard and several higher school sports policies by using the fuzzy comprehensive evaluation method to comprehensively grasp the physical health condition of students and provide reference for school sports reform and students’ physical exercise. Conclusion. The current situation of physical health of college students in Zhuzhou City is less satisfactory, and most of the students’ physical test results are concentrated in the passing area, with fewer students with excellent and good proportions. The policy changes, system construction, implementation, and students’ attitudes were analyzed, and solution measures were proposed to intervene in time to turn the situation around and improve students’ physical health.

Abstract Long intergenic nonprotein coding RNA p53‐induced transcript (LINC‐PINT) has been reported to participate in various cancers. Here, we investigated the effects of LINC‐PINT on lung cancer progression. Firstly, in our study, we implied that LINC‐PINT was obviously decreased in NSCLC. Thereafter, in A549 and H1299 cells, LINC‐PINT was upregulated via transfecting LV‐LINC‐PINT. As exhibited, LINC‐PINT repressed cell proliferation and cell colony formation of A549 and H1299 cells. Subsequently, flow cytometry evidenced that A549 and H1299 cell apoptosis was obviously triggered and the cell cycle was arrested in G1 phase. Then, migration and transwell invasion experiments were carried out to detect the cell migration and invasion capacity. We found A549 and H1299 cell migration and invasion capacity were restrained by the upregulation of LINC‐PINT. Meanwhile, we predicted that miR‐543 could function as the target of LINC‐PINT and the association was verified. Moreover, we exhibited that miR‐543 was remarkably increased in lung cancer, which could be regulated by LINC‐PINT negatively. Furthermore, PTEN could act as the downstream target of miR‐543 and upregulation of miR‐543 repressed PTEN, which was reversed by LV‐PINT in A549 and H1299 cells. Finally, xenografts were utilized to confirm the function of LINC‐PINT on lung cancer. All these findings concluded that LINC‐PINT exerted crucial biological roles in NSCLC through sponging miR‐543 and inducing PTEN.

Abstract Background AsCas12a and LbCas12a nucleases are reported to be promising tools for genome engineering with protospacer adjacent motif (PAM) TTTV as the optimal. However, the C-containing PAM (CTTV, TCTV, TTCV, etc.) recognition by Cas12a might induce extra off-target edits at these non-canonical PAM sites. Results Here, we identify a novel Cas12a nuclease CeCas12a from Coprococcus eutactus, which is a programmable nuclease with genome-editing efficiencies comparable to AsCas12a and LbCas12a in human cells. Moreover, CeCas12a is revealed to be more stringent for PAM recognition in vitro and in vivo followed by very low off-target editing rates in cells. Notably, CeCas12a renders less off-target edits located at C-containing PAM at multiple sites compared to LbCas12a and AsCas12a, as assessed by targeted sequencing methods. Conclusions Our study shows that CeCas12a nuclease is active in human cells and the stringency of PAM recognition could be an important factor shaping off-target editing in gene editing. Thus, CeCas12a provides a promising candidate with distinctive characteristics for research and therapeutic applications.

For a novel disturbance-free payload (DFP) spacecraft, it is difficult to isolate the low-frequency disturbances owing to the umbilical cables, which decreases the pointing accuracy and stability of the payload. In this research, an improved DFP spacecraft and its integrated control scheme are designed to enhance the pointing accuracy and disturbance attenuation performance. The improved DFP spacecraft consists of a Payload Module (PM), a Support Module (SM), and a Test Mass (TM). The integrated control system is subdivided into three interconnected control loops. An active vibration isolation control loop is used to isolate the PM from disturbances in the high-frequency bands and control the PM to track the attitude of the SM. A drag-free control loop is used to isolate the SM from disturbances in the low-frequency bands and control the SM to track the attitude of the TM. An attitude-pointing control loop is used to control the TM to track the desired attitude. Based on the improved DFP spacecraft and the integrated control system, the payload mounted on the PM can be isolated from disturbances in all of the frequency bands, and its high-level requirements for pointing accuracy and stability can be realized.

Abstract Histone acetylation is a key histone post‐translational modification that shapes chromatin structure, dynamics, and function. Bromodomain (BRD) proteins, the readers of acetyl‐lysines, are located in the center of the histone acetylation‐signaling network. How they regulate DNA repair and genome stability remains poorly understood. Here, a conserved function of the yeast Bromodomain Factor 1 (Bdf1) and its human counterpart TAF1 is reported in promoting DNA double‐stranded break repair by homologous recombination (HR). Depletion of either yeast BDF1 or human TAF1, or disruption of their BRDs impairs DNA end resection, Replication Protein A (RPA) and Rad51 loading, and HR repair, causing genome instability and hypersensitivity to DNA damage. Mechanistically, it is shown that Bdf1 preferentially binds the DNA damage‐induced histone H4 acetylation (H4Ac) via the BRD motifs, leading to its chromatin recruitment. Meanwhile, Bdf1 physically interacts with RPA, and this interaction facilitates RPA loading in the chromatin context and the subsequent HR repair. Similarly, TAF1 also interacts with H4Ac or RPA. Thus, Bdf1 and TAF1 appear to share a conserved mechanism in linking the HR repair to chromatin acetylation in preserving genome integrity.

Manganese oxides are often used as catalysts for oxygen reduction reactions due to their low price and high stability, and they have been extensively studied. However, the poor electrical conductivity and low intrinsic activity of manganese oxides restrict its application in oxygen reduction. In this paper, the manganese oxide octahedral molecular sieve is used as the research object, and the oxygen reduction performance of the material is adjusted by the surface reduction etching treatment of sodium borohydride. After being treated with 8 mmol/L sodium borohydride, the oxygen vacancy content of the manganese oxide octahedral molecular sieve was 26%. The manganese oxide octahedral molecular sieve showed the best performance, and its half-wave potential was 0.821 V. Tests show that the material has excellent electrical conductivity and high oxygen reduction kinetics. The generation of appropriate oxygen vacancies on the surface directly improves the chemical properties of the material surface, regulates the ratio of Mn3+/Mn4+ on the surface of the nanorod, and increases the oxygen reduction adsorption sites on the surface of the material. On the other hand, the electrical conductivity of the material is adjusted to increase the electron transfer rate during the oxygen reduction process, thereby enhancing the oxygen reduction activity.

MgO addition plays an essential role in the blast furnace smelting process, including softening-melting characteristics and metallurgical properties of slag. In the present study, the effect of MgO distribution on the softening-melting characteristics and slag system of vanadium-titanium magnetite burden were explored by simulating BF conditions. The results show that the MgO flux addition significantly affects the crystallization temperature of slag-phase, the precipitated phase components, and slag viscosity. This indicates that appropriate MgO addition can improve the metallurgical properties of blast furnace slag effectively, thereby improving the softening-melting-dripping performance of the mixed burden. The V-Ti pellets with a MgO content higher than 2.40 wt% exhibit optimum metallurgical properties. With a constant MgO content in mixed burden, the softening-melting properties of composite burden could be improved effectively as the MgO partitioning scheme includes 1.90 wt% MgO in sinter and 3.02 wt% MgO in pellet.

Abstract Two novel N‐embedded polycyclic units functionalized phosphorescent iridium(III) complexes (Ir‐1 and Ir‐2) with substituents in different positions have been prepared. Complex Ir‐1 bearing the substituent at the 3‐position shows a distinct blue shift single‐peak emission (524 nm) with a higher luminescence efficiency (ΦPL=42 %) and shorter emission lifetime (τ=282 ns) by comparison with 4‐position substitution based complex Ir‐2 (ΦPL=23 %, τ=562 ns), which exhibits a dual‐peak emission (564 nm and 602 nm), and phosphorescence color can be tuned from green to yellow. In addition, DFT calculations demonstrate that unusual ligand‐to‐metal charge transfer (3LMCT) excited state property can be found in Ir‐2, which is in contrast to metal‐to‐ligand charge transfer (3MLCT) excited state character in Ir‐1. This result can be attribute to strong electron‐donating character and 4‐position substitution effect of the unit.

Considering the effects of disturbances in permanent magnet synchronous motor (PMSM), in this paper, a non-smooth composite control approach, which includes finite time disturbance observer (FTDO) for feedforward compensation and finite time control (FTC) for feedback control, is proposed to improve the anti-disturbance performance of PMSM. First, the FTDO is used to estimate the lumped disturbances, such as friction, parameter perturbation, and load variation. Then, the observed value is added to the speed controller as a feedforward compensation to eliminate the effect of disturbance. Second, FTC is introduced into the feedback control design part. In the end, by utilizing Lyapunov theory, the stability analysis of the overall closed-loop system is demonstrated. In contrast to the conventional asymptotically stable control strategy, the proposed composite scheme can provide not only a faster dynamic response but also a stronger capacity of disturbance rejection. The simulation and experimental tests are presented to demonstrate the superior properties of the proposed control scheme.

Photovoltaic (PV) array fault diagnosis is important because it helps reduce energy and revenue losses to PV system operators. It also reduces fire hazards and electric shocks caused by PV array faults. As a result, many machine-learning-based fault diagnosis techniques have been proposed in recent times. Although the fault diagnosis accuracies associated with these techniques have been impressive, most machine learning algorithms rely on manual feature extraction, which is time consuming, expensive, and diagnostic expertise exacting. To address the problem of manual feature extraction, this paper proposes a new PV array fault diagnosis technique capable of automatically extracting features from raw data for PV array fault classification. The proposed technique utilizes long short-term memory networks, which is a deep learning algorithm, for feature extraction. The extracted features feed into a softmax regression classifier for fault diagnosis. The proposed technique exhibits high fault diagnosis accuracies on both noisy and noiseless data. In addition, the results of the proposed technique compare favorably with those of other techniques. It can, therefore, be inferred from the results that the proposed fault diagnosis technique offers an effective approach to automatically extract useful features from raw data and thus remove the need for the manual feature extraction.

We propose a novel fiber-optic auditory nerve of ground (FANG) in the suburb based on the fiber-optic distributed vibration sensor (DVS). The feasibility and effectiveness of the principle prototype FANG for traffic flow monitoring are proved and investigated by the field experiment. One of the 31.8 km-long redundant optical fiber of the buried optical-fiber cable for data transmission is utilized as the sensing fiber. Then, the phase-sensitive optical time-domain reflectometer (φ-OTDR) based DVS is realized and regarded as the FANG. The vibration events at 9 observation points with different ground conditions along the sensing fiber are detected by a threshold algorithm during 6.5 hours from 8:00 am. Then, the vibration events are analyzed in combination with the ground conditions to recognize the machine working in the factory, rammer working and the vehicles passed through near different areas and roads. The traffic flow is estimated by the vibration-counting with a counting error that is believed to be in an acceptable range. The distribution and the fluctuation trends of the estimated traffic flow are useful and enlightening for the traffic monitoring and pre-warning of special events, such as an accident. The accuracy can be improved by artificial intelligence methods in the future. It seems that our proposed FANG can be a potential and effective tool for the internet of things, smart ground and smart traffic in the suburb where the video and other information collection methods are not available.

Lab-attenuated rabies virus (RABV) is a highly cellular adaptation and less pathogenic than wild-type RABV. However, the molecular mechanisms that regulate the cellular adaptation and pathogenicity remain obscure. In this work, we isolated a wild-type RABV (CNIM1701) from a rabid bovine in northern China. The original CNIM1701 was lethal in adult mice and restricted replication in cell cultures. After 20 serial passages in the brains of suckling mice, the virus was renamed CNIM1701-P20, which was safe in adult mice and replicated well in cell cultures. In addition, sequence comparison analysis of the original CNIM1701 and CNIM1701-P20 identified 2 amino acid substitutions on G protein (Lys83 → Arg83 and Pro367 → Ser 367) related to pathogenesis and cellular adaptation. Using site-directed mutagenesis to exchange Lys83 with Arg83 and Pro367 with Ser 367 in the G protein of the RABV SAD strain, the pathogenicity of rSAD-K83R was significantly decreased. Our data indicate that the decreased pathogenicity of rSAD-K83R is due to increasing the expression of RABV-G, which also induced a higher level of apoptosis in infected cells. Furthermore, the K83 mutation induced high expression of MMP-2 and MMP-9 on DCs and promoted blood–brain barrier (BBB) permeability. These results demonstrate that the pathogenesis of RABV is partially dependent on G expression and BBB permeability, which may help in the design and development of highly safe, live-RABV vaccines.