AISI H11 (X38CrMoV5‐1) hot‐work tool steel is widely used for making extrusion tools because of its good mechanical properties at high temperature and moderate cost. To predict its lifetime, an energy conservation‐based model was proposed in this paper by introducing the damage rate, which is expressed as the product of damage force and plastic strain rate. The strain‐controlled low‐cycle fatigue tests were conducted to obtain the parameters of the proposed model, while the stress‐controlled low‐cycle fatigue tests were used to validate the proposed model. The results demonstrate that the proposed model is accurate and reliable. Furthermore, the local misorientation was investigated by electron backscatter diffraction to analyse the correlation between the microstructure evolution and the cyclic behaviour, and crack propagation behaviour was identified.

66Bumblebees are a diverse group of globally important pollinators in natural 67 ecosystems and for agricultural food production. With both eusocial and solitary life-68 cycle phases, and some social parasite species, they are especially interesting models 69to understand social evolution, behavior, and ecology. Reports of many species in 70 decline point to pathogen transmission, habitat loss, pesticide usage, and global 71 climate change, as interconnected causes. These threats to bumblebee diversity make 72 our reliance on a handful of well-studied species for agricultural pollination 73 particularly precarious. To broadly sample bumblebee genomic and phenotypic 74 diversity, we de novo sequenced and assembled the genomes of 17 species, 75representing all 15 subgenera, producing the first genus-wide quantification of genetic 76and genomic variation potentially underlying key ecological and behavioral traits. The 77 species phylogeny resolves subgenera relationships while incomplete lineage sorting 78 likely drives high levels of gene tree discordance. Five chromosome-level assemblies 79show a stable 18-chromosome karyotype, with major rearrangements creating 25 80 chromosomes in social parasites. Differential transposable element activity drives 81 changes in genome sizes, with putative domestications of repetitive sequences 82influencing gene coding and regulatory potential. Dynamically evolving gene families 83and signatures of positive selection point to genus-wide variation in processes linked 84to foraging, diet and metabolism, immunity and detoxification, as well as adaptations 85for life at high altitudes. These high-quality genomic resources capture natural genetic 86and phenotypic variation across bumblebees, offering new opportunities to advance 87 our understanding of their remarkable ecological success and to identify and manage 88 current and future threats. 89 90 91 92

Under the assumption that the emergence and expansion of the new energy vehicles market is due to consumer groups entering market sequentially, and the size and characteristics of each consumer group are different, this paper proposes the R&D investment model of a new energy vehicles firm based on product subsidy. The firm’s optimal R&D investment and pricing strategies are given through theoretic analysis. It is found that when the initial value of the firm’s marginal profits is positive, the optimal R&D investment strategy is to make its marginal profits equal zero if its R&D funds is sufficient enough, otherwise, the optimal R&D investment strategy is its whole R&D funds. And when the initial value of the firm’s marginal profits is non-positive, its optimal R&D investment strategy is zero. It is also found that there is a crowding-in effect of product subsidy on the firm’s R&D investment under two conditions: only if the unit product subsidy is large enough when the firm doesn’t conduct R&D without subsidy, and if only the firm has surplus R&D funds when the firm has conducted R&D without subsidy.

Triethylene glycol (TEG) dehydration unit is a piece of essential device for removing moisture from raw natural gas during natural gas production. However, the existing station equipment management systems are mostly collection-oriented with little analysis, lack the effective methods of parameter prediction and fault warning, and the strong coupling between the monitoring parameters is a problem should be study. To solve these problems, this paper analyzes the time dependence and spatial correlation of these parameters. Also, a spatio-temporal graph convolutional networks prediction model driven by data-physical fusion (SG-STGCN) is proposed for constructing the graph structure. Firstly, the signed directed graph (SDG) model is established based on the physical process, and the weight of each edge is obtained by using the grey relational analysis (GRA). Secondly, by stacking spatio-temporal convolutional modules, the temporal and spatial dependencies over a long range of time are captured to realize multivariate parameter prediction. Then, the real-time monitoring data of a dehydration station are used for analysis. The experimental results showed that the proposed method can achieves the best predict result compared with other methods, and can be used in the fault early warning to maintain high reliability of equipment. Finally, the SG-STGCN has been integrated and tested successfully on the real-time monitoring platform of a dehydration unit.