As of fall 2013, the university has two campuses, a combined student body of 10,000 students, 600 faculty members.The university consists of 10 departments, with 6 specialties for undergraduates. The university covers a total area of 1,100 mu, with more than 10,178 square meters of floor space. As of 2021, the Best Chinese Universities Ranking, also known as the "Shanghai Ranking", placed the university 554th in China.
Low-alloy wear-resistant steel is critical for mechanical transmission components serving under reciprocating friction and corrosive environments. To meet the service requirements of core transmission components of archery training robots, two Sn-microalloyed low-alloy wear-resistant steels (0.04 wt.% and 0.20 wt.% Sn) were designed based on commercial NM450 steel in this work. The effects of Sn on the continuous cooling transformation, microstructure evolution, mechanical properties, and corrosion-wear performance of the steels were systematically investigated, and the optimal heat treatment process was determined. The results show that both steels have a critical cooling rate of 20 °C/s for full martensitic structure with excellent hardenability. The optimized heat treatment enables a well-balanced strength, hardness and toughness of the steels. The 0.20 wt.% Sn steel exhibits significantly improved corrosion resistance and corrosion-wear performance, which is attributed to Sn-induced formation of dense and stable rust layer that inhibits corrosion-wear synergy. This study provides theoretical and data support for composition design and heat treatment optimization of low-alloy wear-resistant steel for archery training robots.
This paper investigates the null controllability of a class of two-dimensional linear parabolic equations with a boundary degeneracy on the domain Ω=T×(0,1), where the internal control acts on a space-time measurable subset of positive measure. Unlike conventional open control supports, a measurable control domain poses significant analytical challenges due to its lack of geometric and topological structures. To overcome this, we combine the method of separation of variables with sharp one-dimensional Carleman estimates that explicitly incorporate high-frequency parameters. This framework allows us to derive a refined Lebeau-Robbiano spectral inequality, which effectively bridges the gap from observability on open sets to general measurable subsets. Consequently, the exact null controllability with an L∞-bounded control is established. This approach provides a unified analytical tool for proving controllability results for higher-dimensional degenerate parabolic equations on structured domains.
PurposeThe present study integrates self-determination theory and affective events theory to develop a dual-path model and a chain mediation model illustrating how humble leadership influences employee counterproductive work behavior.Design/methodology/approachThis study employs a three-wave longitudinal survey design to collect matched data from 350 employees and 92 direct supervisors. Hierarchical regression analysis, along with bootstrapping methods, was employed for empirical testing.FindingsThe results reveal that a significant negative correlation exists between humble leadership and employee counterproductive work behavior. Thriving at work and frustration at work respectively mediate the negative relationship between humble leadership and employee counterproductive work behavior. Additionally, employee empathic concern weakens the indirect negative effects of humble leadership on employee counterproductive work behavior.Originality/valueCurrent research on humble leadership predominantly emphasizes its role in promoting positive employee behaviors, while relatively neglecting its potential efficacy in inhibiting negative employee behaviors. The findings of this study elucidate the mechanisms and boundary conditions through which humble leadership inhibits employee counterproductive work behavior, enriching theoretical research on humble leadership and counterproductive work behavior, while providing managerial implications for organizations to control and reduce such detrimental employee behaviors.
Aerobic oxidation of 5-hydroxymethylfurfural (HMF) can yield numerous furan-based chemicals, and enhancing the selectivity for specific products poses a significant challenge. In this study, a novel non-noble bimetallic catalyst supported on N-doped carbon (Co-Mn/N-C) was designed and synthesized, and various characterization techniques, including XRD, BET analysis, TEM, XPS and VSM studies, were employed to investigate the catalyst's structure and properties. Catalytic testing studies demonstrated that Co-Mn/N-C exhibits superior catalytic performance in the selective oxidation of HMF to 2,5-furandicarboxylic acid (FDCA) in aqueous media, outperforming both Co/N-C and Mn/N-C catalysts. Nearly 100% HMF conversion and 98.3% selectivity towards FDCA were achieved using the Co-Mn/N-C catalyst at 150 degrees C with Na2CO3 (0.5 mmol) as a base. Furthermore, the Co-Mn/N-C catalyst exhibited good stability, maintaining its catalytic activity throughout the recycling experiments. This stable performance is attributed to the robust interaction between the metal and nitrogen-carbon materials.
The occurrence of multiple coupled extreme weather disasters leads to complex operational mechanisms and resilience characteristics in ADN. Considering the fault evolution mechanism under multiple extreme weather disasters, a comprehensive resilience evaluation method of ADN is proposed. First, the spatiotemporal evolution patterns of typical extreme weather events such as typhoon, rainstorms and lightning are analyzed. Based on the material properties of components and the structural characteristics of distribution lines, a mathematical model is developed to quantify the fault probability of ADN under compound extreme weather conditions. Second, the post-fault dynamic response characteristics of ADN are investigated. A unified fault modeling approach is established using Monte Carlo sampling combined with Shannon entropy theory to extract the operational and load features of ADN at different stages. Then, a full-stage resilience evaluation metric system is constructed, covering pre-disaster prevention, in-disaster adaptation and post-disaster recovery. Load performance curves are analyzed from both temporal and power dimensions, and Metric weights for each stage are determined using a hybrid subjective-objective weighting method. The overall system resilience score is calculated using the Euclidean weighted distance method.Finally, a feasible ADN model was constructed for simulation experiments.The simulation results indicate that, the proposed approach can precisely evaluate the overall performance loss of the system subjected to extreme weather events while successfully detecting its resilience-critical segments. With demonstrated accuracy, this framework provides a reliable reference for disaster resilience planning and weak link identification in ADN.
