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This study used surveys, interviews, and XGBoost analysis to examine how experienced and novice entrepreneurs differ in their thinking and decision-making.

This study developed an effective method for extracting valuable information from social media data and employed computer-assisted human coding alongside the AI-powered tool to analyze social media posts. The findings provide a deep understanding of the major challenges that home health care workers are experiencing and offer important implications regarding how to improve home healthcare workers' well-being, and provide suggestions on optimizing the home health care service experience.

Paper found that heat waves in India are linked to lower household income, agricultural income, and consumption, with agriculture being affected the most. It also suggests farm workers may adapt to extreme heat over time by increasing labor inputs despite rising temperatures.

The authors studied optimized delivery routes to reduce travel times using different traveling salesman algorithms.

The authors used a particle-in-cell simulation to determine the effects on extensive and intensive metrics. They found that preliminary simulations could be run quickly with much lower particle counts before more technically demanding and comprehensive simulations are performed.

The authors looked at variables and their patterns and how those contribute to the properties of X-ray binaries.

The authors looked at student perception on various situations involving third-party tracking to personalize recommendations.

Investigation of the largest rigid shape that can be moved through a circular hallway of unit width with an arbitrary turn angle

The authors used Monte Carlo simulations to assess the impacts of various factors on neonatal seizure risk.

The authors looked at the ability of different deep learning models to predict the presence of lung cancer from chest CT scans. They found that a pre-trained CNN model performed better than an autoencoder model.