Recent works identified ClpXP, mitochondrial caseinolytic protease, as the only target of imipridones - new class of antitumor agents. Our study of the mechanism of imipridone derivative TR-57 action in SUM159 human breast cancer cells demonstrated mitochondrial fragmentation, degradation of mitochondrial mtDNA and mitochondrial dysfunction, due to inhibition of Complex I and Complex II activity. Complete inhibition of oxidative phosphorylation accom-panied with 90, 94, 88 and 87% decrease in the content of Complex I, II, III and IV proteins, respectively. The content of the FOF1-ATPase subunits decreased sharply by approximately 35% after 24 hours and remained unchanged up to 72 hours of incubation with TR-57. At the same time, a disappearance of the ATPIF1, natural inhibitor of mitochondrial FOF1-ATPase observed after 24 h exposure to TR-57. ATPase inhibitor oligomycin had no effect on the mitochondrial membrane potential in intact SUM159, whereas it caused a 65% decrease in TR-57-treated cells. SUM159 cells incubated with TR57 up to 72 hours retained the level of proteins facilitating the ATP transfer across the mitochondrial membranes: VDAC1 expression was not affected, while expression of ANT-1/2 and APC2 increased by 20% and 40%, respectively. Thus, our results suggest that alt-hough TR-57 treatment lead to complete inhibition of respiratory chain activity of SUM159 cells, hydrolysis of cytoplasmic ATP by reversal activity of FOF1-ATPase supports mitochondrial polarization.

Principle of memristor presented by Leon Chua and time reversal based non-linear elastic wave spectroscopy (TR-NEWS) which can be applied to acoustic tomography are reviewed. Correlation of acoustic or electromagnetic nonlinear waves and its time reversed wave can produce strong signal. Materials like transducer or biological skin can be assumed to be composed of a large number of small elastic unit: hysteretic elementary unit (HEU), and one can take a HEU as a memristor whose operation depends on time. Relation between TR-NEWS and solitonic wave in fluid, and relation between decomposition of time reversal operator (DORT) and chaotic oscillation are discussed.

Changing climate conditions and rapidly increasing carbon dioxide emissions have severely affected the global ecosystem and world economy. Governments around the world have paid attention to these resulting challenges and enacted many policies to reduce environmental pollution and carbon dioxide (CO2) emissions. This study aimed to determine and understand the relationship between innovation, foreign direct investment, economic growth, renewable consumption and CO2 emission in Vietnam. Information was collected annually based on the annual data of the General Statistics Office of Vietnam and World Bank from 2000 to 2022. Data processing was conducted using the STATA 17.0 software. The innovation affects Vietnam’s environmental pollution. Innovation positively affect environmental pollution in Vietnam; if Vietnam’s innovation were to increase by 1%, CO2 emissions would increase by 0.68%. The empirical research results of this study also show that renewable energy consumption has a negative effect on environmental pollution in Vietnam; if renewable energy were consumed at a 1% increase, CO2 emission would decrease by 0.51%. In addition, FDI inflows and economic growth have strongly positive affecting to environmental pollution; if Vietnam’s FDI inflows were to increase 1%, CO2 emissions would increase 1.39%; if Vietnam’s GDP increase 1% then CO2 emission would increase 1.26%. This paper also provides some recommendations that can assist Vietnam in developing a green and sustainable economy in the technology revolution 4.0 to achieve the United Nations Sustainable Development Goals (SDGs) over a long-term period.

Cultural Tourism (CT), which enhances the economic development of a region, aids a country in reinforcing its identities, enhancing cross-cultural understanding, and preserving the heritage culture of an area. Designing a proper tourism model assists the tourists in understanding the point of interest without the help of a local guide. However, owing to the need for the analysis of different factors, designing such a model is a complex process. Therefore, this article proposes a CT model for Riyadh for peak visitor time. Primarily, the map data and cultural event dataset are processed for location, such as grouping with Kriging Interpolation-based Chameleon (KIC), tree forming, and feature extraction. After that, the event dataset’s attributes are processed with word embedding. Meanwhile, the Social Network Sites (SNS) data like reviews and news are extracted with an external Application Programming Interface (API). The review data is processed with keyword extraction and word embedding, whereas the news data is processed with score value estimation. Lastly, the data are fused corresponding to a historical site and given to the Multi-Quadratic-Long Short Term Memory (MQ-LSTM) Recommendation System (RS); also, the recommended result with the map is stored in a database. Lastly, the database security is maintained with Locality Sensitive Hashing (LSH); moreover, by attaining higher performance values, the proposed model is experimentally verified.