The research undertaken has provided a comprehensive insight into the practice of cupping therapy, a traditional treatment modality that has seen resurgence in. modern complementary medicine. This exploration, focusing on a spectrum of. Conditions such as migraines, lower back pain, neck pain, knee osteoarthritis, and chronic urticaria, highlights the potential benefits and the necessity for a deeper. Scientific understanding of cupping therapy. Cupping therapy, with its roots deeply embedded in ancient medical practices, offers a unique approach to treatment by promoting healing through increased blood flow and the release of toxins from the body. The application of this therapy in treating migraines has shown promising results, su

The research undertaken has provided a comprehensive insight into the practice of cupping therapy, a traditional treatment modality that has seen resurgence in. modern complementary medicine. This exploration, focusing on a spectrum of. Conditions such as migraines, lower back pain, neck pain, knee osteoarthritis, and chronic urticaria, highlights the potential benefits and the necessity for a deeper. Scientific understanding of cupping therapy. Cupping therapy, with its roots deeply embedded in ancient medical practices, offers a unique approach to treatment by promoting healing through increased blood flow and the release of toxins from the body. The application of this therapy in treating migraines has shown promising results, su

Sensibly highlighting the hidden structures of many real-world networks has attracted growing interest and triggered a vast array of techniques on what is called nowadays community detection (CD) problem. Non-deterministic metaheuristics are proved to competitively transcending the limits of the counterpart deterministic heuristics in solving community detection problem. Despite the increasing interest, most of the existing metaheuristic based community detection (MCD) algorithms reflect one traditional language. Generally, they tend to explicitly project some features of real communities into different definitions of single or multi-objective optimization functions. The design of other operators, however, remains canonical lacking any inte

Artificial intelligence has quickly invaded the realms of both creative and information-based writing, raising new questions about human originality, authorship and style. Despite its ability to produce writings that are coherent and stylistically varied, there are still concerns over the uniqueness and cultural neutrality of AI programs such as ChatGPT. This review covers significant recent advancements with artificial intelligence applications in both the literary and non-literary fields. It analyzes 35 recent studies contrasting authorship and creativity, or stylistic considerations and impressions, between human and AI texts. These studies range from poetic and fictional writing through essay, news article and academic publicati

Face recognition and identity verification are now critical components of current security and verification technology. The main objective of this review is to identify the most important deep learning techniques that have contributed to the improvement in the accuracy and reliability of facial recognition systems, as well as highlighting existing problems and potential future research areas. An extensive literature review was conducted with the assistance of leading scientific databases such as IEEE Xplore, ScienceDirect, and SpringerLink and covered studies from the period 2015 to 2024. The studies of interest were related to the application of deep neural networks, i.e., CNN, Siamese, and Transformer-based models, in face recogni