Trough mapping the knowledge structure of livelihood vulnerability research, the current landscape was clarified, key research areas was highlighted, evolving trends was traced, and future research directions was proposed, offering valuable insights for advancing this field. Using CiteSpace visualization software, studies on livelihood vulnerability published from 2008 to 2024 in the Web of Science (WoS) and CNKI (China National Knowledge Network) databases were compared, their progression, core themes, and emerging trends were analyzed. The findings reveal the volume of research in this field has grown steadily, with France and the UK forming the core of an collaboration network, supported by strong partnerships among scholars and institutions. Early studies focused on climate change, natural disasters, and household livelihood dynamics, while recent research emphasizes regional and empirical analyses, livelihood capital, poverty-alleviated households, visualization techniques, rural revitalization, risk of poverty recurrence, and livelihood resilience. Future research on livelihood vulnerability should deepen efforts in collaboration, topics, and methodologies, while continuing to extract and refine China’s rural anti-poverty experiences to support the comprehensive advancement of the rural revitalization strategy.

In the process of the formation of new quality productive forces, four technologies play crucial roles. Information technology is the innovation-leading technology. New industrialization technology is the foundation-building technology.Financial technology is the efficiency-enhancing technology. Green technology is the quality-oriented technology. At present, the information revolution has developed to the stage of qualitative change, where data has become a new factor of production, and the production of knowledge and information has entered the stage of mechanized large-scale industry from manual workshops. The proposal of new quality productive forces is a scientific observation and summary of the progress of the information revolution to the stage of qualitative change. Through the analysis of the key technologies of new quality productive forces, the implication of “new” and “quality” in the phrase of new quality productive forces can be understood more clearly.

A modern industrial system is the material and technological foundation of a modern country, and building a modern industrial system is a necessary condition for promoting high-quality development and the key to winning international competitive advantages. On the basis of constructing the index system, the provincial panel data of in China from 2011 to 2022 were used for empirical analysis. The results show that the digital economy has significantly promoted the construction of a modern industrial system.The efficiency of factor allocation plays an intermediary role in the impact of the digital economy on the modern industrial system. The impact of the digital economy on the modern industrial system has a significant spatial spillover effect.

Aiming at the airport clear water vehicle scheduling problem, considering the situation that clear water vehicles with multi-specification load capacity provide guarantee services for flights of different aircraft types, an optimal airport clear water vehicle scheduling model was constructed to minimize the number of vehicles in use and the waiting service time for flights. By introducing time window span and service waiting time as the key factors of the state transfer rule, and adopting stage pheromone evaporation and intra-path 2-opt and inter-path 2-opt^* optimization strategies, the traditional ant colony algorithm is improved in terms of applicability and used for model solving. Finally, the operational data of a hub airport in Southwest China was used as an example for validation. Compared with the traditional first-come-first-served scheduling, the number of vehicles in use and the flight waiting service time are reduced by 27.3% and 22.9%, respectively, for the scheduling scheme obtained by solving the improved ant colony algorithm. The results show that the constructed model and algorithm demonstrate high optimization efficiency and practicality in the airport clear water vehicle scheduling problem.

Under the technical support of geographic information system(GIS), the country park in Yannan Mountain Area of Urumqi was taken as the research object. Based on the field investigation, 10 key ecological sensitivity evaluation indexes were selected. By applying analytic hierarchy process (AHP) to determine the weight of each factor, the evaluation index system of ecological sensitivity of country parks was constructed. The results show that the ecological sensitivity of country parksis mainly highly sensitive, with an area of 173.30 hm², accounting for 31.64%. The remaining sensitive areas are 91.07 hm², 93.01 hm², 126.07 hm², and 64.30 hm², accounting for 16.63%, 16.98%, 23.02%, and 11.74%, respectively.

Addressing the difficulties in collecting key data during battery operation and the limited amount of electrochemical impedance spectroscopy (EIS) data, is able to optimize battery performance evaluation and health monitoring, as well as optimize battery usage and charging strategies. The research method involves using data augmentation techniques to increase the sample size while ensuring data quality. The denoising diffusion probability model (DDPM), as an emerging generative model, is applied to enhance battery data. For low dimensional battery data such as current, voltage, temperature, and capacity, the DDPM model is directly applied for data augmentation. For high-dimensional EIS data, the autoencoder (AE) model is first used for dimensionality reduction, followed by data augmentation in low dimensional space, and the enhanced data is restored to the original space. The research results confirm that the proposed data augmentation method can generate high-quality data on NASA(National Aeronautics and Space Administration) and EIS public datasets and effectively reduce computational complexity. The conclusion indicates that this study provides an effective data augmentation strategy for battery performance evaluation and health management, and has certain reference and application value.

As an important means of energy storage project, salt cavern storage will cause the cavern to contract due to the fluctuation of injection and extraction pressures, which in turn can lead to surface subsidence. Numerical simulation analysis has been conducted on the main influencing factors of surface subsidence of double cavity under different injection and extraction cycles, and it has been found that reducing the injection and extraction cycle can slow down the trend of surface subsidence. An analysis of the probability of cavern failure in the operation of a salt cavern storage with a 60 d injection and extraction cycle has been carried out. When the pressure fluctuation of the storage exceeds 1 MPa, the probability of cavern failure will exceed 20% after 30 a. Therefore, when designing the operating conditions of salt cavern, it is necessary to consider the impact of pressure fluctuations on surface subsidence and control the fluctuation range of pressure according to the design life of the storage.

It is of great significance for promoting the transformation of scientific and technological achievements(TSTA) to make the technicians in the core position. Based on the multi-case study, the technology transfer patterns in which the technicians as the core factor formed in the construction of “Qinchuangyuan” in Shaanxi province were analyzed and summarized. It is found that by the implementation of “Three reforms” policy during the construction of “Qinchuangyuan”, which greatly arouses the initiative of technicians to promote the TSTA, and produces four patterns of TSTA innovation and entrepreneurship, embedded scientific research personnel, market transaction, internal self-transform by technicians of enterprises. The transformation of achievements centered on scientific and technological personnel provides useful reference for the whole country.

Affected by the complex situation at home and abroad, the financing cost of Chinese enterprises is high. The VAT policy is one of the key measures to reduce taxes and fees, which has a significant effect on reducing the burden on enterprises. A differentially differential model was used to explore the impact of this policy on corporate debt financing costs based on pilot data from some industries in 2018. The results show that after the implementation of the policy, the debt financing cost of enterprises has decreased significantly, especially in the non-state-owned, small and competitive industries of enterprises, while the impact on state-owned and large enterprises is small. This result can provide a basis for further deepening the tax rebate policy and helps promote the healthy and sustainable development of enterprises.

In the context of the digital economy and VUCA(volatility, uncertainty, complexity, ambiguity) era, digitally empowering operations management has become an important strategy for manufacturing enterprises to operate steadily and develop efficiently, but there is still insufficient research in academia on whether and how digital capabilities (DC) can improve enterprise operational performance (OP). Based on the theory of dynamic capabilities, questionnaire survey data from manufacturing enterprises in China was used to empirically analyze the influence mechanism and boundary conditions of DC on OP. The results indicate that DC (intelligence capability, connectivity capability and analysis capability) have a positive impact on OP, supply chain resilience (SCR) partially mediates the relationship between DC and OP. Strategic matching positively moderates the impact of connectivity capability and analytical capability on SCR, but has no significant moderating effect on the relationship between intelligence capability and SCR. These results can provide important practical implications for effectively promoting enterprise OP under the digital context.