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This paper aims to obtain fire resistance of semi-rigid joints for concrete-filled steel tubular (CFST) composite frames and temperature filed distribution of composite joints in fire.

The temperature filed model of semi-rigid joints to CFST columns with slabs was made by using ABAQUS finite element (FE) software, in considering temperature heating-up stage of fire modelling. The effects of composite slab, fire type and construction location were discussed, and the model was verified by the test results. The temperature distribution of composite joint under three-side or four-side fire condition was studied by the sequentially coupled thermal analysis method. The temperature versus time curves and temperature distribution of various construction and location were analyzed.

The paper provides FE analysis and numerical simulation on temperature field of semi-rigid joints for CFST composite frames in fire. The effects of composite slab, fire type and construction location were discussed, and the model was verified by the test results. It suggests that the temperature distribution of composite joint in three- or four-side fire condition showed a different development trend.

Because of the chosen FE analysis approach, the research results may lack generalizability. Therefore, researchers are encouraged to test the proposed propositions further.

The research results will become the scientific foundation of mechanical behavior and design method of semi-rigid CFST composite frames in fire.

This paper fulfils an identified need to study the temperature field distribution of the semi-rigid joints to CFST columns and investigate the mechanical behavior of the semi-rigid CFST joints in fire.

Entrepreneurs approach the startup process with a stock of experience and a unique range of accumulated skills and abilities. Their prior experience shapes an “information funnel” through which the entrepreneurs’ attention is filtered. This study aims to investigate the impact of the relatedness of prior knowledge and knowledge acquisition activities on entrepreneurs’ perceived knowledge access.

Survey data were collected from 100 early-stage entrepreneurs in the New York City metropolitan area to empirically test the proposed relationships with the method of conditional process modeling.

Findings from this study demonstrate a negative relationship between entrepreneurs’ prior experience and their perceived ability to access knowledge. However, this negative relationship can be mitigated by seeking tacit knowledge through informal channels. In addition, the relatedness of prior experience plays a positive role in influencing media use and knowledge network engagement. While media use is a positive predictor of perceived knowledge access, engagement within knowledge networks shows no direct influence on perceived knowledge access.

This study sheds light on the dimensions of entrepreneurial knowledge and recognizes perceived knowledge access as an important concept in forming an entrepreneurial intention and adds to the current dialogue on the interpretation of entrepreneurs’ prior experience. For practitioners, this study offers insights into the formation of founding teams and the approaches to obtaining valuable information.

With the rapid development of short videos in China, the public has become accustomed to using short videos to express their opinions. This paper aims to solve problems such as how to represent the features of different modalities and achieve effective cross-modal feature fusion when analyzing the multi-modal sentiment of Chinese short videos (CSVs).

This paper aims to propose a sentiment analysis model MSCNN-CPL-CAFF using multi-scale convolutional neural network and cross attention fusion mechanism to analyze the CSVs. The audio-visual and textual data of CSVs themed on “COVID-19, catering industry” are collected from CSV platform Douyin first, and then a comparative analysis is conducted with advanced baseline models.

The sample number of the weak negative and neutral sentiment is the largest, and the sample number of the positive and weak positive sentiment is relatively small, accounting for only about 11% of the total samples. The MSCNN-CPL-CAFF model has achieved the Acc-2, Acc-3 and F1 score of 85.01%, 74.16 and 84.84%, respectively, which outperforms the highest value of baseline methods in accuracy and achieves competitive computation speed.

This research offers some implications regarding the impact of COVID-19 on catering industry in China by focusing on multi-modal sentiment of CSVs. The methodology can be utilized to analyze the opinions of the general public on social media platform and to categorize them accordingly.

This paper presents a novel deep-learning multimodal sentiment analysis model, which provides a new perspective for public opinion research on the short video platform.

The purpose of this paper is to study the transition process from the crystalline particles appearing before the pump inlet to the stable operation of the pump.

Firstly, a modeling test method was put forward for the high-temperature molten salt pump. Then, according to a modeling test scheme, the experiment of the solid–liquid two-phase flow was carried out by using a model pump similar to the prototype pump. Meanwhile, the numerical method to simulate the transition process of a molten salt pump was studied, and the correctness of the numerical model was verified by the experimental results. Finally, the transition process of the molten salt pump was studied by the verified numerical model in detail.

In the simulation of the transition process, it is more accurate to judge the end of the transition process based on the unchanged particle volume fraction (PVF) at the pump outlet than on the periodic fluctuation of the outlet pressure. The outlet pressure is closely related to the PVF in the pump. The variation of the outlet pressure is slightly prior to that of the PVF at the pump outlet and mainly affected by the PVF in the impeller and volute. After 0.63 s, the PVF at each monitoring point changes periodically, and the time-averaged value does not change with time.

This study is of great significance to further improve the design method of molten salt pump and predict the abrasion characteristic of the pump due to interactions with solid particles.

A numerical method is established to simulate the transition process of a molten salt pump, and a method is proposed to verify the numerical model of two-phase flow by modeling test.

This investigation seeks to elaborate on how proactive market orientation (MO) and responsive MO motivate firms to conduct business model innovation (BMI) through the breadth of market knowledge search (BMKS) and the depth of market knowledge search (DMKS).

Based on the survey data of 259 high-tech firms in the industrial parks of the Yangtze River Delta, this study uses multiple hierarchical regressions to examine the hypotheses and conducts Sobel and bootstrapping methods to further test the mediating effects.

The findings indicate that the positive effects of proactive and responsive MO on BMI are mediated by BMKS and DMKS. It also shows that proactive MO has a greater impact on BMKS than responsive MO, while responsive MO has a stronger impact on DMKS than proactive MO.

Firms with different MOs can choose different types of market knowledge search to promote BMI, which reminds managers to give attention to the importance of bridging MOs with knowledge search strategies in BMI.

This study introduces a constructive theoretical framework by examining the roles of MO and market knowledge search on BMI. The findings reveal that MO as a key initiating factor and market knowledge search as an important conduit play vital roles in the experimental process of BMI and identify the differential effects of proactive and responsive MO on two types of market knowledge search.

An obvious way to improve acquisition performance is to avoid completing value-destroying acquisitions. However, once announced, manager motivations often focus on completing acquisitions. The authors develop how external governance actors can interpret acquisition characteristics and make counter-signals that acquiring firm managers could use to improve acquisition outcomes. The authors specifically develop how managers may react to counter-signals by shareholders, media, analysts, and short sellers. While there is limited research considering these external governance actors, evidence suggests that managers’ reactions to these actors may vary. A more integrated assessment of external governance actors’ influence on acquisition completion offers an opportunity to better understand acquisition processes and performance.

The purpose of this study is to delineate the differences in how contextual factors (i.e. funding, market reach and talent) influence performance of entrepreneurial ecosystems in advanced and emerging economies.

Building upon the biological perspective on entrepreneurial ecosystems, in this study we conduct the fuzzy-set Qualitative Comparative Analysis (fsQCA) on the sample of 100 entrepreneurial ecosystems across 25 advanced economies and 21 emerging economies. The fsQCA allows us to embrace the causal complexity that characterizes the relationship between multiple contextual factors and ecosystem performance in countries with different levels of economic development.

The results elucidate how the level of a country’s economic development influences the interplay of contextual factors and their collective impact on the performance of entrepreneurial ecosystems across advanced and emerging economies.

Our findings provide useful guidance for practitioners and policymakers aiming to cultivate conducive environments for nurturing new ventures within local ecosystems, which will stimulate the economic growth of the regions and narrow the gap between advanced and emerging economies.

This study delineates the complex interactions of key contextual factors and their joint impact on ecosystem performance in emerging economies, in comparison to ecosystems in advanced economies. By looking into differences of antecedents of high and low performance of ecosystems embedded in countries with distinctive level of economic development, this study goes beyond prior research that primarily focused on singular countries or regions.

High-speed turnouts are more complex in structure and thus may cause abnormal vibration of high-speed train car body, affecting driving safety and passenger riding experience. Therefore, it is necessary to analyze the data characteristics of continuous hunting of high-speed trains passing through turnouts and propose a diagnostic method for engineering applications.

First, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) is performed to determine the first characteristic component of the car body’s lateral acceleration. Then, the Short-Time Fourier Transform (STFT) is performed to calculate the marginal spectra. Finally, the presence of a continuous hunting problem is determined based on the results of the comparison calculations and diagnostic thresholds. To improve computational efficiency, permutation entropy (PE) is used as a fast indicator to identify turnouts with potential problems.

Under continuous hunting conditions, the PE is less than 0.90; the ratio of the maximum peak value of the signal component to the original signal peak value exceeded 0.7, and there is an energy band in the STFT time-frequency map, which corresponds to a frequency distribution range of 1–2 Hz.

The research results have revealed the lateral vibration characteristics of the high-speed train’s car body during continuous hunting when passing through turnouts. On this basis, an effective diagnostic method has been proposed. With a focus on practical engineering applications, a rapid screening index for identifying potential issues has been proposed, significantly enhancing the efficiency of diagnostic processes.

The volume of passenger traffic at metro transfer stations serves as a pivotal metric for the orchestration of crowd flow management. Given the intricacies of crowd dynamics within these stations and the recurrent instances of substantial passenger influxes, a methodology predicated on stochastic processes and the principle of user equilibrium is introduced to facilitate real-time traffic flow estimation within transfer station streamlines.

The synthesis of stochastic process theory with streamline analysis engenders a probabilistic model of intra-station pedestrian traffic dynamics. Leveraging real-time passenger flow data procured from monitoring systems within the transfer station, a gradient descent optimization technique is employed to minimize the cost function, thereby deducing the dynamic distribution of categorized passenger flows. Subsequently, adhering to the tenets of user equilibrium, the Frank–Wolfe algorithm is implemented to allocate the intra-station categorized passenger flows across various streamlines, ascertaining the traffic volume for each.

Utilizing the Xiaozhai Station of the Xi’an Metro as a case study, the Anylogic simulation software is engaged to emulate the intra-station crowd dynamics, thereby substantiating the efficacy of the proposed passenger flow estimation model. The derived solutions are instrumental in formulating a crowd control strategy for Xiaozhai Station during the peak interval from 17:30 to 18:00 on a designated day, yielding crowd management interventions that offer insights for the orchestration of passenger flow and operational governance within metro stations.

The construction of an estimation methodology for the real-time streamline traffic flow augments the model’s dataset, supplanting estimated values derived from surveys or historical datasets with real-time computed traffic data, thereby enhancing the precision and immediacy of crowd flow management within metro stations.

The purpose of this paper is to explore the contemporary paradigm of business leadership vis-à-vis China’s reform and transitional context.

The paper employs an evidence-based approach to explore the business leadership issues influenced by economic reform and within the context of societal transition in China. A qualitative research method was adopted based on in-depth interviews with a number of middle managers from a variety of Chinese enterprises, including state-owned, domestic-private and foreign-invested enterprises. Content analysis of several rounds of interviews added depth to the data analysis.

The findings complement existing thoughts and illustrate concepts, issues, and characteristics not yet emphasized in mainstream literature. General patterns and associated characteristics of business leadership in China, as well as specific patterns associated with different forms of enterprise ownerships, are identified.

The study makes a timely and necessary contribution that enriches context-specific understandings of business leadership against the backdrop of surrounding economic, social, and cultural changes.

The study enriches understandings of commonalities and differences in leadership across the globe, facilitating working collaboratively to achieve common goals in a global community.

The study offers new insights into business leadership by linking contextual, personal, and cognitional factors together and demonstrates some unique characteristics of leadership styles in transitional economies like China.