Gumashvili Megi^1,2, Yiping Mu¹, Kulbo Nora Bakabbey³, Addo Prince Clement^2,3,4,*, Kiti Kanokon¹, Menezes Dalila Batista de Sousa de¹, Baidoo Bernard Ekow¹

Journal of Psychology in Africa, Vol.35, No.3, pp. 287-298, 2025, DOI:10.32604/jpa.2025.067165 - 31 July 2025

Abstract This study investigated the influence of human capital development and technological, strategic, cognitive, and environmental factors on Industry 4.0 readiness, as well as cultural factors acting as a mediator. Respondents were 478 employees from across eight regions in Russia. Survey data were collected on employee technological readiness, human capital development, strategic planning, cognitive perceptions, and environmental and cultural factors influencing the adoption of Industry 4.0 technologies, with cultural factors mediating. These findings from the structure equation analysis show that technological factors and human capital development are the strongest predictors of readiness, suggesting that robust digital More >

Erdong Shen¹, Ting Pan¹, Pan Guo¹, Ke Chen¹, Rui Xu¹, Mei Yang¹, Dahe Zhan¹, Fang Fang¹, Qinghui Wu^1,*, Jianbing Hu^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.4, pp. 1-3, 2024, DOI:10.32604/icces.2024.012772

Abstract Objective
This study investigates the synergistic effects of a novel multifunctional nanoparticle on gastric cancer treatment through photothermal therapy, chemotherapy, and immunotherapy.

Method
Synthesize hollow mesoporous Prussian blue nanoparticles and load them with luteolin. Use exosomes to encapsulate the nanoparticles and modify the surface of the targeted peptide GX1. Detect the morphology of nanoparticles using a nanoparticle size analyzer and transmission electron microscopy. Use Coomassie Brilliant Blue to detect the effect of extracellular vesicle encapsulation. Detect the thermal conversion efficiency of nanoparticles under specific laser irradiation through infrared and ultraviolet spectroscopy, as well as the release rate… More >

Galimkair Mutanov, Vladislav Karyukin^*, Zhanl Mamykova

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 913-930, 2021, DOI:10.32604/cmc.2021.017827 - 04 June 2021

Abstract The volume of social media data on the Internet is constantly growing. This has created a substantial research field for data analysts. The diversity of articles, posts, and comments on news websites and social networks astonishes imagination. Nevertheless, most researchers focus on posts on Twitter that have a specific format and length restriction. The majority of them are written in the English language. As relatively few works have paid attention to sentiment analysis in the Russian and Kazakh languages, this article thoroughly analyzes news posts in the Kazakhstan media space. The amassed datasets include texts… More >