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Epizoochorous dispersal of grassland plants by large herbivores is an important way by which grassland plants achieve population expansion over long distances. However, little is known about the maximum distance that seeds can be dispersed by domestic animals under seasonal grazing, which is the most common type of grassland management worldwide, especially in alpine regions. To this end, we estimated the distance over which epizoochory dispersal occurs via yaks ( ) for seven common plant species seeds in an alpine meadow under seasonal grazing using a simulated yak-fur seed adhesion test combined with observations of grazing behavior. The results showed that, as yak primary (e.g., walking time) and secondary (e.g., foraging rate) behavioral patterns differed significantly across seasons ( < 0.05), the epizoochory dispersal distances of plant seeds also had clear seasonal dynamics, manifesting as spring > summer > autumn > winter, and that the length of seed adhesive structures correlated positively with the retention rate as well as retention time on yak fur. The relatively slow loss of diaspores observed in this study mainly shows that moving yak from one seasonal pasture to the following allows the dispersal of diaspores between two successive pastures. The dispersal scale was even wider (maximum dispersal distance of ~35 km) for seeds with special appendages (i.e., mucilage, sticking to the fur due to mucilage presence). Our results highlight that yaks are substantial seed dispersal vectors for alpine meadow plants and that seasonal grazing is a suitable management method for coping with habitat fragmentation as well as plant diversity conservation in alpine areas from the perspective of seed dispersal.

Grazing on cultivated grassland is a green agricultural model. However, in China's Loess Plateau, the type of cultivated grassland suitable for grazing and the amount of nitrogen application is still unclear, which has led to the failure of this model to be widely implemented. In this context, we set up an experiment using three grass planting types, including monoculture of alfalfa (Medicago sativa L.), monoculture of brome (Bromus inermis L.), and mixed planting of the two forages. Under each planting type, there were six management measures: grazing and no nitrogen application (GN1), grazing and 80 kg ha -1 nitrogen application (GN2), grazing and 160 kg ha -1 nitrogen application (GN3), cutting and no nitrogen application (MN1), cutting and 80 kg ha -1 nitrogen application (MN2), and cutting and 160 kg ha -1 nitrogen application (MN3). To explore the impacts of these treatments on pastures, we studied the effects on the yield, quality, and water use efficiency of the three cultivated grasslands. Results showed that alfalfa monoculture and alfalfa-brome mixed sowing grassland resulted in significantly higher hay yield, crude protein yield, water use efficiency (WUE), precipitation use efficiency (PUE), nitrogen use efficiency (NUE), and agronomic efficiency of nitrogen (AEN) as compared to brome monoculture grassland. In addition, the crude protein, ether extract, and crude ash content of alfalfa monoculture and alfalfa-brome mixture were increased significantly while the contents of neutral detergent fiber (NDF) were reduced, thereby increasing the relative feed value (RFV) during the two years. The forage hay yield, crude protein yield, ether extract, crude ash content, RFV, PUE, and WUE were significantly higher with GN1, GN2, and GN3 treatments than that with MN1 treatment. In contrast, the NDF and acid detergent fiber (ADF) content was significantly lower than the MN1 treatment. Furthermore, the fresh forage yield, crude protein yield, PUE, and WUE of GN3 treatment were significantly higher than that of GN1 and GN2 treatments in both years, while the NUE and AEN were significantly higher in GN2 and GN3 treatments than that of MN3 treatment. Based on these results, alfalfa-brome mixed cropping with the application of 160 kg ha -1 nitrogen under grazing conditions is an appropriate management practice for improving the forage yield, quality, and water- and nitrogen utilization efficiency of cultivated grassland in the Loess Plateau of China. This integrated management model is applicable to the cultivation and utilization of mixed grassland on nutrient-poor land in the Loess Plateau.

Multiple microorganisms directly or treated with NaOH were immobilized by using Ca-alginate embedding to form biosorbents Ⅰ and Ⅱ, successively. The biosorption behaviors of biosorbents Ⅰ and Ⅱ for Pb(Ⅱ) from aqueous solution were investigated in a batch system. Effects of solution pH, initial metal concentration, biosorbent dosage, contact time, temperature, and ionic strength on the adsorption process were considered to study the biosorption equilibrium, kinetics, thermodynamics, and mechanism of Pb(Ⅱ) ion adsorption on the 2 types of biosorbents. The results showed that the adsorption capacity of biosorbent Ⅱ for Pb(Ⅱ) was higher than that of biosorbent Ⅰ, and biosorbent Ⅱ had a faster adsorption rate for Pb(II) ions. According to FTIR spectra, the carboxyl, amine, and hydroxyl groups on the biomass surface were involved in the biosorption of Pb(Ⅱ). EDX analysis showed that ion exchange may be involved in the biosorption process, and the morphology observed by SEM micrograph of biosorbent Ⅰ was completely different from that of biosorbent Ⅱ. Desorption and regeneration experiments showed that the 2 types of biosorbents could be reused for 3 biosorption-desorption cycles without significant loss of their initial biosorption capacities.

Taking the slope reinforced by frame anchors as the research object, it is assumed that the potential sliding surface of the slope is an arc. Based on the limit equilibrium theory, the seismic stability analysis model of frame anchor reinforced slope considering anchor prestress is established. This study considers prestress as uniformly distributed forces acting on the slope surface and calculates the additional stress induced by prestressing within the slope to investigate its reinforcement effect on slopes. Thus, the stability of the slope is analyzed and calculated. On this basis, the functional relationship between the center position coordinates of the potential sliding surface and the safety factor is established. Using the optimization algorithm toolbox in Matlab, the possible center position area is dynamically searched, and the minimum safety factor and its corresponding center position coordinates are obtained. Taking slope engineering as an example, the calculated results are compared with the finite element calculation results. The results show that the calculation result regarding the anchor prestress as the uniformly distributed force is reliable, and the anchor prestress can significantly enhance slope stability. This calculation method applies to slope engineering in homogeneous soil with circular sliding surfaces.

Based on the action mechanism of the frame prestressed anchor slope supporting structure, combined with the pseudo-dynamic method, the acceleration distribution on the half plane is solved by the seismic wave theory, assuming that the seismic waves are simple harmonics. In the case of prestress, the potential sliding surface of slope is determined by derivation of the ratio of anti-sliding force and sliding force under dynamic action. Combined with horizontal layer analysis method, the active earth pressure of prestressed anchor slope supporting structure under simple harmonic earthquake is solved. Finally, the soil pressure variation of the frame bolting structure under the harmonic seismic action is compared with the engineering case. The results show that the higher prestress can restrain the variation range of seismic earth pressure.

Under dry friction conditions, wear of the C-ring mating surface and excessive contact pressure of the Stirling engine piston rod cap seal can reduce its sealing performance and service life. Based on the modified Archard wear model, its thermal coupling-wear mathematical model was established and performance analysis was carried out. Based on the established simulation model, the model’s predictions were first made using a BP neural network (BPNN) optimized by a particle swarm optimization (PSO). On this basis, the grey relational method was used to optimize the design of the working condition parameters with the minimum average wear rate Wr and the maximum contact pressure P cmax as the optimization objectives, and the best optimization combination scheme was derived. Finally, the optimized design method presented in this paper was verified to exhibit superior performance using the seal test bench. The results show that the BPNN optimized by PSO the coefficient of determination R 2 of Wr and P cmax higher than 90 %, the root mean square error (RMSE) lower than 0.5, the model prediction accuracy high and the combination of regression design verifies that the BPNN prediction is real and effective. Through the grey relational method, it is found that the work pressure A 1 is the most significant for the multi-objective response, and the significance of the relative operating speed B 1 , ambient temperature D 1 , and friction factor C 1 decreases in the order of significance: when A 1 = 7 MPa, B 1 = 2.5 m/s, C 1 = 0.11, and D 1 = 120 °C, the W r is 5.07e −6 (mm 3 /s), and the P cmax is 22.406 MPa, which is higher than that of orthogonal experimental method and the original data, W r decreases by 8.75 % and 18.33 %, and P cmax increases by 15.50 % and 35.88 %, respectively, indicating that the grey relational method is superior in terms of comprehensive performance, and the sealing performance and service life of the optimized design method in this paper are verified by the experiment.

In Arabidopsis, Arabidillo-1 and Arabidillo-2 have great sequence homology to Dictyostelium and metazoan β-catenin/Armadillo, which are important to animal and Dictyostelium development. Arabidillo-1 and Arabidillo-2 promote lateral root formation redundantly in Arabidopsis. Here, we showed that gibberellins (GA₃) has a greater inhibitory effect on lateral root growth from the null mutant arabidillo-1 than from the wild type, suggesting that the mechanism for Arabidillo-1-regulated modulation of lateral root proliferation is associated with GA₃-metabolic or signaling pathways. Our yeast two-hybrid analysis demonstrated that Arabidillo-1 interacts with ASK2 and ASK11, and that ASK2 can bind with the F-box domain of Arabidillo-1. Therefore, Arabidillo-1 is involved in the ubiquitin/26S proteasome-mediated proteolytic pathway. Based on these results, we conclude that Arabidillo-1 can degrade some positive regulator of the GA₃ signaling pathway through selective protein degradation of ubiquitin/26S. Moreover, that process is believed to be the mechanism for Arabidillo-1 promotion of lateral root development in Arabidopsis.

A comprehensive understanding of host-virus interactions during persistent foot-and-mouth disease virus (FMDV) infection is essential for elucidating the mechanisms that underpin disease causation by this highly contagious pathogen. This understanding necessitates the development of stable in vitro models. In this study, we established a model of persistent FMDV serotype O infection in Madin-Darby bovine kidney epithelial cells followed by integrated multiomics analyses. These analyses revealed that host cells adapt to persistent viral infection by reprogramming mitochondrial metabolism. This reprogramming is accompanied by alterations in mitochondrial structure and function, as well as the suppression of the apoptotic response in host cells. In particular, bystander cells, which are devoid of active viral replication, display enhanced proliferative capacity and possess a distinct microenvironmental signature that potentially increases viral susceptibility, facilitating sustained virus persistence within the cell population. Moreover, persistent viruses have evolved enhanced replicative fitness. Our findings elucidate the biological characteristics of FMDV-infected cell populations that persistently harbour the virus, reveal host-virus coadaptation, and highlight the critical role of bystander cells in sustaining persistent FMDV infection. These discoveries establish the foundation for further mechanistic studies of FMDV persistence maintenance.

Rolling bearings are essential in rotating machinery, but their operation under diverse conditions like load, speed, and temperature can lead to complex faults. While efforts have addressed multiple component faults, identifying and classifying multipoint faults in rolling bearings remains challenging. In this paper, a hybrid deep learning network (HDLNet) for multipoint fault diagnosis in rolling bearings is proposed under variable operating conditions. Firstly, in the time domain, a two-layer bidirectional long short-term memory (Bi-LSTM) network is utilized to extract the temporal features of vibration signals. Secondly, in the spatial domain, a multi-scale dynamic snake convolution with fast spatial pyramid pooling attention (MDSC-FSPPA) network is proposed to capture the spatial characteristics of vibration signals. Following this, fault features extracted from both time and spatial dimensions are combined, and improved residual network (ResNet) is leveraged to further enhance the feature representation and suppress noise. Furthermore, visualization techniques are employed to intuitively show the relationships and clustering structures among them. Experimental dataset of rolling bearing with multipoint faults are used to evaluate the proposed HDLNet. The findings indicate that the proposed HDLNet has good noise resistance generalization performance and superior diagnostic performance under different rotational speeds compared to other established intelligent fault diagnosis approaches.