The paper presents the results of a study focused on technological parameters that ensure the effectiveness of using concrete powders obtained from crushed concrete waste as an active mineral additive in construction mixtures used for 3D printing. The efficiency of using a complex polyfunctional additive to cement pastes and mortars based on it is experimentally demonstrated. This additive includes a naphthalene-formaldehyde-based superplasticizer and a water-retaining additive, hydroxyethyl methylcellulose. Using the mathematical experiment planning methodology, polynomial models of the cement pastes and mortars' mechanical properties were obtained. The models showed a positive effect of the complex additive on the cement pastes' normal consistency and viscosity. Additionally, the results of the study demonstrate the possibility of regulating the cement pastes' setting time and the plastic strength of mortars based on them using a complex additive. Analysis of the experimental-statistical models shows that using the complex additive allows regulation of water separation as well as the compressive and flexural strength of cement-sand mortars based on the investigated cement pastes within the required limits. Improving the key properties of building mixtures containing crushed concrete waste for 3D printing using complex polyfunctional modifier additives opens up new opportunities for increasing their economic and environmental efficiency.
This study examines the temporal dynamics of petroleum hydrocarbon contamination and natural attenuation processes in riverine surface waters affected by military-related accidental pollution. Time-series monitoring data from six rivers located in eastern and western regions were analysed to quantify concentration exceedances, rates of decline, and differences in self-purification capacity among river systems. Petroleum hydrocarbon concentrations were determined using a standardised fluorimetric method, and their temporal behaviour was evaluated through descriptive statistics and first-order kinetic modelling. Extremely high peak concentrations were recorded following accidental releases, exceeding regulatory thresholds for fisheries and domestic water use by one to two orders of magnitude. Although a consistent decreasing trend was observed in all rivers, median and mean concentrations in several cases remained above regulatory limits for extended periods. Estimated half-times of concentration reduction varied markedly among rivers, reflecting differences in hydrological conditions, channel morphology, urbanisation, and dilution capacity. The results demonstrate that natural attenuation plays a significant role in reducing petroleum hydrocarbon levels, but is insufficient to fully offset the impacts of large-scale and repeated pollution events under conflict conditions. These findings highlight the need for integrated monitoring, targeted mitigation measures, and long-term restoration strategies to support sustainable water management during post-conflict recovery.
Water is extensively used for cooling in power plants, accumulating major ions (HCO3-, CO32-, SO42-, Cl-, Ca-2(+), Mg-2(+), Na+, and K+) in the cooling water system. This study quantitatively examines the factors influencing the composition of these ions in the cooling water cycle and assesses their environmental impact upon discharge into the Styr River (Ukraine). Over a 5-year monitoring period (2018-2022), ion concentrations were measured in process water and receiving surface water using certified laboratory methods. The findings reveal that sulphate concentrations ranged from 17.3 to 375 mg/L, chloride from 9.3 to 90.0 mg/L, and total dissolved solids from 230 to 1035 mg/L, with seasonal fluctuations observed. Statistical regression models were developed to predict post-discharge ion concentrations based on intake water quality and cooling system operational parameters, demonstrating a strong correlation (coefficients of determination R-sq = 82.4%-98.8%). The study uniquely integrates the grey water footprint (GWF) methodology to quantify the required dilution volumes for maintaining regulatory water quality. The results indicate that while ion concentrations increase in return water, they remain within permissible limits, ensuring no significant ecological disturbance.
This article presents a comprehensive interdisciplinary analysis of the legal and economic challenges associated with the use of artificial intelligence in journalism. It does this within the framework of developing a model of responsible media governance. The relevance of the study is driven by several factors. Firstly, there has been rapid diffusion of generative artificial intelligence technologies in editorial practice. Secondly, there has been transformation of media business models. Thirdly, there has been emergence of new challenges relating to copyright protection, professional journalistic ethics, and information security. Finally, there is a need to harmonise Ukrainian legislation with the European regulatory framework governing artificial intelligence. The study aims to examine the legal and economic implications of artificial intelligence in journalism, evaluate current approaches to its regulation and demonstrate that responsible media governance is a viable model for balancing technological innovation, economic efficiency and public interest protection. The findings demonstrate that, although artificial intelligence can substantially enhance the efficiency of editorial workflows by automating routine tasks, it can also generate new legal, economic and ethical challenges. These challenges are associated with using journalistic content to train generative AI models, allocating liability for AI-generated content, developing the market for licensing journalistic data, spreading disinformation and the growing use of digital avatars and synthetic media. The study concludes that the risk-based regulatory approach set out in the European Union's Artificial Intelligence Act (AI Act) offers a modern conceptual basis for managing the use of artificial intelligence in the media sector. However, effective implementation requires economic mechanisms to complement content licensing, transparent allocation of responsibilities among digital ecosystem participants, and further development of editorial self-regulation. The research's scientific novelty lies in substantiating the interdisciplinary concept of responsible media governance, integrating legal, economic and organisational self-regulatory mechanisms for the use of artificial intelligence in journalism. The practical significance of the findings is their potential to improve Ukrainian legislation on media and artificial intelligence, develop editorial AI governance policies, establish licensing mechanisms for journalistic content and align the national regulatory framework with European Union legislation.
Дослідження становища соціально вразливих категорій дітей має стратегічне значення для формування якісного людського капіталу та забезпечення суспільної стабільності. Ефективним методом аналізу цієї проблематики є картографічне моделювання. На основі статистичних даних Служби у справах дітей Житомирської ОДА за допомогою програмного забезпечення QGIS було розроблено тематичні карти. Вони наочно відображають показники первинного обліку дітей-сиріт і дітей, позбавлених батьківського піклування, а також структуру їх влаштування: під опіку, до прийомних сімей та дитячих будинків сімейного типу, у державних закладах. Основним способом картографічного зображення обрано картограми. Розроблені карти деталізують територіальний розподіл даних на рівні адміністративних районів та громад. Така візуалізація дозволяє органам влади об’єктивно оцінити ситуацію в регіоні та приймати обґрунтовані управлінські рішення. Зокрема, це стосується оптимізації соціальної інфраструктури та впровадження дієвих заходів для захисту інтересів дітей-сиріт і дітей, позбавлених батьківського піклування
