The cultivation of vegetables serves as a vital pillar in horticulture, offering an alternative avenue towards achieving economic sustainability. Unfortunately, farmers often lack adequate knowledge on optimizing resource utilization, which subsequently results in low productivity. Furthermore, there has been insufficient research conducted on the comparative profitability and efficient use of resources for pea cultivation. So, the present study was conducted to examine the profitability and resource use efficiency of conventional and organic pea production in Northwestern Himalayan state. Using the technique of purposive sampling, the districts and villages were selected based on the highest area. By using simple random sampling, a sample of 100 farmers was selected, out of which 50 were organic growers and 50 were inorganic growers, who were further categorized as marginal and small. The cost incurred was higher for the cultivation of inorganic vegetable crops, whereas returns and output-input ratio was higher in organic cultivation. The cultivation of peas revealed that the majority of inputs were being underutilized, and there was a need for proper reallocation of the resources, which would result in enhanced production. Further, major problems in the cultivation of vegetable crops were a high wage rate, a lack of organic certification, a shortage of skilled labour and a lack of technical knowledge.

In the current context of China’s vigorous development of its high-speed rail (HSR) network to accelerate the realization of connectivity, which is the aim of the “Belt and Road” initiative, it is crucial to study how the specific opening of HSR enhances enterprise human capital investment efficiency. Using a multiple-time-point difference-in-differences (DID) regression model, we empirically study data from listed Chinese companies. An HSR opening can promote the efficiency of an enterprise’s human capital investment. We further explore the relationship between HSR and a company’s human capital investment, by considering the moderating effects of firm property rights and foreign shareholding. Our findings indicate that these factors can enhance the impact of HSR on the efficiency of firms’ investments in human capital. Finally, to ensure the reliability of our experimental findings, we employed a combination of propensity score matching and the DID methodology. The findings of this study offer empirical evidence that can inform enterprise management strategies and provide valuable insights for policymakers seeking to promote economic growth.

The Organic Rankine Cycle (ORC) is an electricity generation system that uses organic fluid instead of water in the low temperature range. The Organic Rankine cycle using zeotropic working fluids has wide application potential. In this study, data mining (DM) model is used for performance analysis of organic Rankine cycle (ORC) using zeotropik working fluids R417A and R422D. Various DM models, including Linear Regression (LR), Multi-Layer Perceptron (MLP), M5 Rules, M5 Model Tree, Random Committee (RC), and Decision Tree (DT) models are used. The MLP model emerged as the most effective approach for predicting the thermal efficiency of both R417A and R422D. The MLP’s predicted results closely matched the actual results obtained from the thermodynamic model using Genetron software. The Root Mean Square Error (RMSE) for the thermal efficiency was exceptionally low, at 0.0002 for R417A and 0.0003 for R422D. Additionally, the R-squared (R²) values for thermal efficiency were very high, reaching 0.9999 for R417A and R422D. The findings demonstrate the effectiveness of the DM model for complex tasks like estimating ORC thermal efficiency. This approach empowers engineers with the ability to predict thermal efficiency in organic Rankine systems with high accuracy, speed, and ease.

In this paper, a solar tracking device that can continuously track the sun by adjusting the direction and angle of the solar panel in real time is designed and fabricated to improve the power generation efficiency of the solar cell panel. The mechanical parts as well as the automatic control part of the passive sun-tracking system are described, and the efficiency enhancement with the sun-tracking solar panel is characterized in comparison with the fixed panel system. The test results show that in the spring season in Qingdao city of eastern China, the sun-tracking system can improve the solar cell power generation efficiency by 28.5%–42.9% when comparing to the direction and elevation angle fixed system in sunny days. Even in partly cloudy days, the PV power output can increased by 37% with using the passive sun-tracking system. Economic analysis results show the cost-benefit period is about 10 years, which indicates that the passive sun tracking device can substantially contribute to the solar energy harvest practices.