Utah authorities have released CCTV footage showing the Charlie Kirk shooting suspect fleeing the scene at Utah Valley University. The video shows a figure dressed in black running across a roof before dropping down to the ground and fleeing towards a wooded area. Authorities say the suspect was wearing Converse shoes, sunglasses and a distinctive black T-shirt with an American flag and an eagle. Watch: Key moments from RFK Jr's heated Senate hearing The US health secretary faced questions on Covid deaths and vaccines a week after firing the head of the Centers for Disease Control and Prevention. The group said they are making their own list of Jeffrey Epstein's associates and called for the release of all files related to the investigation.

This research explores the use of Natural Language Processing (NLP) techniques to locate geological resources, with a specific focus on industrial minerals. By using word embeddings trained with the GloVe model, we extract semantic relationships between target keywords and a corpus of geological texts. The text is filtered to retain only words with geographical significance, such as city names, which are then ranked by their cosine similarity to the target keyword. Dimensional reduction techniques, including Principal Component Analysis (PCA), Autoencoder, Variational Autoencoder (VAE), and VAE with Long Short-Term Memory (VAE-LSTM), are applied to enhance feature extraction and improve the accuracy of semantic relations. For benchmarking, we calculate the proximity between the ten cities most semantically related to the target keyword and identified mine locations using the haversine equation. The results demonstrate that combining NLP with dimensional reduction techniques provides meaningful insights into the spatial distribution of natural resources. Although the result shows to be in the same region as the supposed location, the accuracy has room for improvement.