Standards

The evaluation of bioavailable forms of heavy metals in zones of anthropogenic pollution is the basis of ecological risk assessment. The characterization of the consequences of the operation of the Pechenganikel smelting plant was carried out using AAS and two methods of soil bioavailable forms of heavy metal extraction (3% nitric acid and ammonium acetate buffer with pH 4.8) along three directions from the plant, corresponding to the wind prevalence. Buffer extraction provided more significant correlations between Ni, Co, Cu, Pb, and Zn, compared to nitric acid application, indicating a negative correlation between soil Cu, Co, and the distance from the plant, while no significant correlations were recorded for nitric acid extracts. A higher significant correlation number arose between soil elements in buffer extracts along the N-E direction than the S-W one. In the former direction, the number of the mentioned correlations decreased according to the following sequence: Zn (6) > Cu (5) > Se and Co (4) > Ni and Fe (3); in nitric acid extract, only significant correlations of Cu, Zn, and Se with Co and Ni were recorded. Biocrust formation was revealed only along the N-E direction, characterized by unexpected high Se concentrations and intensive correlation between Zn and all the elements extracted by the buffer. Biocrust accumulated high levels of all the elements tested and showed antioxidant activity and polyphenol content significantly correlated with soil organic matter. The biocrust mineral content demonstrated a complex relationship with soil Fe, Cu (buffer extract), and Se, as well as Co and Zn (nitric acid extract). Application of linear mixed-effects modelling and transfer factor analysis indicate that biocrusts may serve as effective bioindicators of both absolute metal contamination and its bioavailable fractions. The results indicate the expediency of using both methods of soil extraction for assessing the ecological risk and soil–biocrust relationships.

This article examines the global efforts to govern and regulate Artificial Intelligence (AI) in response to its rapid development and growing influence across many parts of society. It explores how governance takes place at multiple levels, including international bodies, national governments, industries, companies, and communities. The study draws on a wide range of official documents, policy reports, and international agreements to build a timeline of key regulatory and standardization milestones. It also analyzes the challenges of coordinating across different legal systems, economic priorities, and cultural views. The findings show that while some progress has been made through soft-law frameworks and regional partnerships, deep divisions remain. These include unclear responsibilities, uneven enforcement, and risks of regulatory gaps. The article argues that effective AI governance requires stronger international cooperation, fair and inclusive participation, and awareness of power imbalances that shape policy decisions. Competing global and commercial interests can create obstacles to building systems that prioritize the public good. The conclusion highlights that future governance models must be flexible enough to adapt to fast-changing technologies, yet consistent enough to protect rights and promote trust. Addressing these tensions is critical for building a more just and accountable future of AI.

Driver fatigue and drowsiness are the causes of many road accidents. In this work, a low-cost hybrid system is proposed for determining driver fatigue level based on four metrics: last sleep quality, blinking rate, heart rate variation, and yawning. The values of these metrics were experimentally determined for two age groups (20–25 and 55–60 years) and three time intervals of a day (9:00–10:00, 12:00–14:00, and 21:00–24:00). It should be mentioned that it is not always necessary to calculate the values of the four metrics, depending on the state of the driver and the state of the vehicle. In comparison to other proposed systems, our proposed system uses the four metrics in a single system, with their measurement being interdependent. Experimental results as well as future research directions are presented in this paper.