Protest event analysis is a key method to study social movements, allowing systematically analyze protest events over time and space. However, the manual coding of time-consuming resource intensive. Recently, advances in automated approaches offer opportunities code multiple sources create large data sets that span many countries years. too often procedures used are not discussed details and, t...

Preprocessing text data sets for use in Natural Language Processing tasks is usually a time-consuming and expensive effort. Text data, normally obtained from sources such as, but not limited to, web scraping, scanned documents or PDF files, typically unstructured prone to artifacts other types of noise. The goal the TextCL package simplify this process by providing multiple methods suited prepr...

In recent years, natural language processing (NLP) has transformed numerous domains, becoming a vital area of research. However, the focus NLP studies predomi-nantly centered on major languages like English, inadvertently neglecting low-resource Pashto. Pashto, spoken by population over 50 million worldwide, remains largely unexplored in research, lacking off-the-shelf resources and tools even ...

Computer-based knowledge and computation systems are becoming major sources of leverage for multiple industry segments. Hence, educational learning processes across the world on cusp a digital transformation. This paper seeks to explore concept an artificial intelligence natural language processing (NLP) based intelligent tutoring system (ITS) in context computer education primary secondary sch...

Nesfatin-1 is an 82 amino acid anorexigen encoded in a secreted precursor nucleobindin-2 (NUCB2). NUCB2 was named so due to its high sequence similarity with nucleobindin-1 (NUCB1). It was recently reported that NUCB1 encodes an insulinotropic nesfatin-1-like peptide (NLP) in mice. Here, we aimed to characterize NLP in fish. RT- qPCR showed NUCB1 expression in both central and peripheral tissue...

Accurate and timely detection of medical adverse events (AEs) from free-text narratives can be challenging. Natural language processing (NLP) with deep learning has already shown great potential for analyzing data, but its application AE been limited. In this study, we developed based NLP (DL-NLP) models efficient accurate hip dislocation following primary total replacement standard (radiology ...