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The rational allocation of industrial factors in resource-based cities is a necessary condition for promoting high-quality economic development. To systematically measure the mismatch of industrial factors, this study integrates the production function model and accounting framework of Aoki (2012). The capital, labor, and energy factors are integrated into the overall measurement framework, and the factor mismatch calculation model is innovatively constructed at the city level. To effectively reflect the factor mismatch of different cities, the relative distortion coefficient of factor price is introduced to establish the relationship between the distortion of factor-use cost and effectiveness of resource allocation. The degree and direction of factor mismatch are effectively measured. This study takes China's resource-based cities as the research object. To avoid the impact of the COVID-19 pandemic, data on 114 resource-based cities in China from 2003 to 2018 are selected, and 164 non-resource-based cities are used as the control group to evaluate the factors affecting the transformation of such cities. Regarding the diversity of resource-based cities in China, this study compares the characteristics of factor misallocation in these cities for different growth stages, geographical regions, and dominant resources. Finally, this study finds that on average, the cities' degree of energy misallocation is the most serious, and the degree of labor misallocation ranks second. The degree of capital misallocation ranks the lowest, but the misallocation of various factors is very different in different situations. Therefore, different types of cities should make detailed policy adjustments in various transformation directions according to the calculation results., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Runqun Yu reports financial support was provided by Liaoning Social Science Planning Fund Office., (© 2024 The Authors.)

Weak magnetic detection technology is an effective method to identify stress-induced damage to ferromagnetic materials, and it especially possesses great application potential in long-distance oil and gas pipeline weld crack detection. In the process of pipeline operation, due to internal pressure and external loads, local stress concentration may be generated, and partial stress concentration may lead to local cracks and expansion of the pipe. In order to improve the accuracy of magnetic signal analysis for ferromagnetic materials under internal pressure, the causes of magnetic signal generation at pipeline welds were analyzed from a microscopic perspective. The distributions of magnetic signals at pipeline welds, weld cracks, and base metal cracks under different internal pressures were numerically analyzed. The variation trends of magnetic signal characteristics, such as peak values of axial and radial components, gradient K , maximum gradient Kmax , and gradient energy factor S ( K ), were analyzed. In addition, experiments were carried out to verify the numerical data. It was revealed that with the elevation of internal pressure, the peak values of the axial and radial components, gradient K , maximum gradient Kmax , and gradient energy factor S ( K ) linearly increased. However, the magnitude and average change of S ( K ) were larger, which can more directly indicate variations of magnetic signals. The radial growth rate ν y of S ( K ) was 3.24% higher than the axial growth rate ν x , demonstrating that the radial component of the magnetic signal was more sensitive to variations of stress. This study provided a theoretical and experimental basis for detection of stress-induced damage to long-distance oil and gas pipelines.

Experiments on hippocampal slices have recorded that a novel pattern of epileptic seizures with alternating excitatory and inhibitory activities in the CA1 region can be induced by an elevated potassium ion (K(+)) concentration in the extracellular space between neurons and astrocytes (ECS-NA). To explore the intrinsic effects of the factors (such as glial K(+) uptake, Na(+)-K(+)-ATPase, the K(+) concentration of the bath solution, and K(+) lateral diffusion) influencing K(+) concentration in the ECS-NA on the epileptic seizures recorded in previous experiments, we present a coupled model composed of excitatory and inhibitory neurons and glia in the CA1 region. Bifurcation diagrams showing the glial K(+) uptake strength with either the Na(+)-K(+)-ATPase pump strength or the bath solution K(+) concentration are obtained for neural epileptic seizures. The K(+) lateral diffusion leads to epileptic seizure in neurons only when the synaptic conductance values of the excitatory and inhibitory neurons are within an appropriate range. Finally, we propose an energy factor to measure the metabolic demand during neuron firing, and the results show that different energy demands for the normal discharges and the pathological epileptic seizures of the coupled neurons.