The dynamic impact of renewable energy consumption, trade, and financial development on carbon emissions in low-, middle-, and high-income countries.

The present study confronts potential theoretical argument of dynamic and non-linear relationship between [Formula: see text] emissions, renewable energy consumption, trade, and financial development by using quantile regression that accounts for the role of development in explaining the stated nexus. The results show that renewable energy consumption reduces [Formula: see text] emissions in the short run in low-, middle-, and high-income countries. [Formula: see text] emissions plumet as country open up for trade and expand financial services for their people.

Automated Lung Nodule Detection and Classification Using Deep Learning Combined with Multiple Strategies.

Lung cancer is one of the major causes of cancer-related deaths due to its aggressive nature and delayed detections at advanced stages. Early detection of lung cancer is very important for the survival of an individual, and is a significant challenging problem. Generally, chest radiographs (X-ray) and computed tomography (CT) scans are used initially for the diagnosis of the malignant nodules; however, the possible existence of benign nodules leads to erroneous decisions.