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 publications. Six main topics emerged: Reconfiguring Authorship and Creativity in AI-Generated Literature; Disentangling Human and AI Authorship in informative and Creative Writing; Cultural Stereotyping, Stylistic Homogenization and Creative Constraints in AI-Generated Literary Content; Audience Perception, Misidentification and Heuristics in Informative Discourse; Educational Applications and Authorship Detection in AI-Generated vs. Human Texts; and Integration of AI into Special Research Fields such as Law, Criminology, Literature Reviews and Social Media. In particular, it was determined that though AI may have the ability to mirror humans on the basis of grammar, structure and at times a degree of creative literacy, it does not possess the capacity to address matters of deep emotional resonance and cultural context. However, at times humans cannot easily discern between texts written by AI and those authored by humans themselves, calling confidence and authority into question. Future studies could focus on how cultural background impacts the responses of people to AI-generated content, particularly in educational environments of colleges and universities.
Some species, such as the Eurasian Collared-Dove (S. decaocto) are fast expanding around the planet, while others, such as the European Turtle-Dove (S. turtur), are experiencing precipitous population declines. Climate change, habitat loss, greater cultivated areas, and hunting pressure are the major threats to the diversity of Streptopelia. A few species require urgent conservation action. Priority for subsequent research should be to redress outstanding taxonomic uncertainties, ascertain the effect of climate change on distributions, and put in place conservation measures for declining taxa. We provide here a detailed review on how it is possible to understand the diversity of Streptopelia and how such an understanding can con
... Show MoreIn the article we consider features of official style, its functions and factors which influence the definition of the style. The topicality of the issue can be explained by rapid development of market economy which affects in its turn business correspondence. In this regard, there are a lot of cliché, terms and professionalisms appeared recently. Only correct usage of them can serve as a key to successful communication in Russian as well as other languages. This work highlights documents that are part of the diplomatic style such as declarations, credentials, notes, resolutions and other documents. The administrative style can include orders and instructions.
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... Show MoreThis study aims to conduct an exhaustive comparison between the performance of human translators and artificial intelligence-powered machine translation systems, specifically examining the top three systems: Spider-AI, Metacate, and DeepL. A variety of texts from distinct categories were evaluated to gain a profound understanding of the qualitative differences, as well as the strengths and weaknesses, between human and machine translations. The results demonstrated that human translation significantly outperforms machine translation, with larger gaps in literary texts and texts characterized by high linguistic complexity. However, the performance of machine translation systems, particularly DeepL, has improved and in some contexts
... Show MoreThe Arab realized that proverbs and their stories had a great literary and linguistic significance, accordingly, they collected them from their sources and wrote them down. Thus, researchers went in studying them in different directions. The aim of the present research is thus to study the stories of proverbs in the Holy Qur’an, Prophet’s hadiths, and in the sayings of Arabs. Such a study helps to show the extent of the relevance of their stories to the proverbs, their literary values, the points of convergence between them and what they highlight, and the extent of their proximity to reality. It further helps to determine the factors that contributed to the transformation of Quranic verses, Prophet’s hadiths, and some phrases of s
... Show MoreThis systematic review aimed to analyse available evidence to answer two focused questions about the efficacy of erythritol powder air‐polishing (EPAP) (i) as an adjunctive during active periodontal therapy (APT) and (ii) as an alternative to hand/ultrasonic instrumentation during supportive periodontal therapy (SPT). Additionally, microbiological outcomes and patient's comfort/perceptions were assessed as secondary outcomes.
PubMed, Cochrane and Medline were searched for relevant articles published before February 2021 following PRISMA guidelines. The search was conducted by three indep
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
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