There is strong interest in develo** a more efficient mental health care system. Digital
interventions and predictive models of treatment prognosis will likely play an important role …

It has been evidenced by numerous studies that irrational investor sentiment is one of the
critical factors leading to dramatic volatility in financial market prices. Therefore, how to …

Machine learning (ML) and deep learning (DL) are a subset of artificial intelligence (AI) that
can automatically learn from data and can perform tasks such as predictions and decision …

Landslides are a common geological hazard causing impairment of public works and loss of
lives worldwide and in India, especially in the Himalayan region. The present study aims to …

Planted forests are critical to climate change mitigation and constitute a major supplier of
timber/non-timber products and other ecosystem services. Globally, approximately 36% of …

Background: The long-term risk of recurrent ischemic stroke, estimated to be between 17%
and 30%, cannot be reliably assessed at an individual level. Our goal was to study whether …

Drought is a costly natural disaster that impacts economies and ecosystems worldwide, so
monitoring drought and communicating its impacts to individuals, communities, industry, and …

Soil water and salt contents are key soil physical parameters that play a crucial role in soil-
related hydrological, ecological, environmental, and agricultural processes. Time domain …

Abstract Machine-learning methods exploit fund characteristics to select tradable long-only
portfolios of mutual funds that earn significant out-of-sample annual alphas of 2.4% net of all …

The sports market has grown rapidly over the last several decades. Sports outcomes
prediction is an attractive sports analytic challenge as it provides useful information for …