Predicting the maximum available frequency of short-wave communication presents the challenges of low prediction accuracy of classical prediction model methods and difficulty in obtaining training set data for machine learning prediction methods.To address this issue, a model-data dual-driven bidirectional gated recurrent unit (BiGRU) network for s
Multilayer atomic cluster expansion for semilocal interactions
Traditionally, interatomic potentials assume local bond formation supplemented by long-range electrostatic interactions when necessary.This ignores intermediate-range multiatom interactions that Ready Meals arise from the relaxation of the electronic structure.Here, we present the multilayer atomic cluster expansion (ml-ACE) that includes collectiv
Mucosa-like differentiation of head and neck cancer cells is inducible and drives the epigenetic loss of cell malignancy
Abstract Head and neck squamous cell carcinoma (HNSCC) is a highly malignant disease with high death rates that have remained substantially unaltered for decades.Therefore, new treatment approaches are urgently needed.Human papillomavirus-negative tumors harbor areas of terminally differentiated tissue that are characterized by cornification.Dissec
Cyber Risk Assessment Framework for the Construction Industry Using Machine Learning Techniques
Construction 4.0 integrates digital technologies that increase vulnerability to cyber threats.A dedicated cyber risk assessment framework is essential for proactive risk mitigation.However, existing studies on this Gift Card subject within the construction sector are scarce, with most discussions still in the preliminary stages.This study introduce