This paper proposes a robot designed for automated routine or emergency disinfection in closed premises. The robot is related to the combined type robots. The robot consists of two functional parts: a universal mobile platform (lower part) and a disinfector (upper part), which, if necessary, can be freely moved by personnel on 4 wheels. In the initial position, the upper part of the disinfection robot is at the charging station. The mobile robot drives up to the disinfector, «hooks» it (puts it on itself) and moves along the planned route. The upper part of the disinfector will have its own independent intelligent system, separate from the mobile robot, which, when a person is recognized, stops liquid disinfection: in this case, the UV lamps turn through 180°, the cylindrical body closes and ventilation of the disinfected air from the enclosed space is turned on. In addition, liquid disinfection is only enabled when detecting beds, tables and chairs. With the spray nozzles located at a height of 400 mm, the disinfector can carry out a simultaneous combined treatment of rooms with equipment and furniture, including high-quality processing of the lower surfaces of tables, chairs and beds. To improve the functional characteristics of robotic disinfectors and to simplify their design, a multifunctional robotic disinfector has been proposed. It was found that the result is achieved by the fact that in a multifunctional disinfection robot containing a mobile cart with an autonomous positioning and navigation system, a disinfection platform with a disinfection liquid spraying system and UV lamps with reflectors installed on it, the disinfection platform will have its own autonomous control and power systems © 2022, Eastern-European Journal of Enterprise Technologies. All rights reserved.

Dye wastewater pollution has become a significant environmental issue threatening aquatic ecosystems and human health. To achieve green and efficient removal of organic dye (e.g., methylene blue (MB)), bio-based magnetic composite beads (Fe3O4/SiO2@SA) were prepared through HCl-assisted SiO2 extraction, co-precipitation and ion-crosslinking under mild conditions, without high pressure, high reaction temperature or toxic chemicals. Batch adsorption studies of MB were used to explore the adsorption performance and mechanism of Fe3O4/SiO2@SA. The experimental results demonstrate that the MB removal rate of Fe3O4/SiO2@SA composite beads reaches 91.75% under optimised adsorption conditions (25 ℃, pH 9, 100 mg/L initial MB concentration, 20 mL solution volume, and 10 mg adsorbent dosage). Compared to Fe3O4 and Fe3O4/SiO2 powders, the adsorption capacity is much higher at 183.77 mg/g. Physisorption and monolayer adsorption were demonstrated. The optimal adsorption capacity of Fe3O4/SiO2@SA on MB is 925.77 mg/g. In addition, Fe3O4/SiO2@SA enabled rapid and efficient solid-liquid separation through an external magnetic field and exhibits excellent reusability. The removal efficiency stayed at 80.1% after six cycles of adsorption and desorption, and reached 81.1% in river water. The Fe3O4/SiO2@SA composite beads possess excellent adsorption capability, rapid magnetic separability and good reusability, providing a sustainable solution for dye water treatment. This research provides novel viewpoints and experimental supports for the evolution of low-cost, recyclable, environmentally friendly adsorbents.

The purpose of the present work was to determine the thermal performance of borehole heat exchangers, considering the influences of their geometric configurations and the thermophysical properties of the soil, grout and pipe wall material. A three-dimensional model was developed for the heat and mass transfer in soil (a porous medium) and grout, together with one-dimensional conductive heat transfer through the pipe walls and one-dimensional convective heat transfer of the heat transfer fluid circulating in the pipes. An algorithm was developed to solve the mathematical equations of the model. The COMSOL Multiphysics software was used to implement the algorithm and perform the numerical simulations. An apparatus was designed, installed and tested to implement the thermal response test (TRT) method. Two wells of depth 50 m were drilled in the Almaty region in Kazakhstan. Gravel and till/loam were mainly found, which are in accordance with the stratigraphic map of the local geological data. In each well, two borehole heat exchangers were installed, which were an integral part of the ground source heat pump. The TRT measurements were conducted using one borehole heat exchanger in one well and the data were obtained. The present TRT data were found to be in good agreement with those available in literature. The numerical results of the model agreed well with the present TRT data, with the root-mean-square-deviation within 0.184 °C. The TRT data, together with the predictions of the line-source analytical model, were utilized to determine the soil thermal conductivity ((Formula presented.) = 2.35 W/m K) and the thermal resistance of the borehole heat exchanger from the heat transfer fluid to the soil ((Formula presented.) = 0.20 m K/W). The model was then used to predict the efficiencies of the borehole heat exchangers with various geometric configurations and dimensions. The simulation results show that the spiral borehole heat exchanger extracts the highest amount of heat, followed by the multi-tube, double U-type parallel, double U-type cross and single U-type. It is also found that the spiral configuration can save 34.6% drilling depth compared with the conventional single U-type one, suggesting that the spiral configuration is the best one in terms of the depth and the maximum heat extracted. The simulation results showed that (i) more heat was extracted with a higher thermal conductivity of grout material, in the range of 0.5–3.3 W/m K; (ii) the extracted heat remained unchanged for a thermal conductivity of pipe material higher than 2.0 W/m K (experiments in the range of 0.24–0.42 W/m K); (iii) the extracted heat remained unchanged for a volumetric flow rate of water higher than 1.0 m3/h (experimental flow rate 0.6 m3/h); and (iv) the heat extracted by the borehole heat exchanger increased with an increase in the thermal conductivity of the soil (experiments in the range of 0.4–6.0 W/m K). The numerical tool developed, the TRT data and simulation results obtained from the present work are of great value for design and optimization of borehole heat exchangers as well as studying other important factors such as the heat transfer performance during charging/discharging, freezing factor and thermal interference. © 2022 by the authors.

Typical leg exoskeletons employ open-loop kinematic chains with motors placed directly on movable joints; while this design offers flexibility, it leads to increased costs and heightened control complexity due to the high number of degrees of freedom. The use of heavy servo-motors to handle torque in active joints results in complex and bulky designs, as highlighted in the existing literature. In this analytical study, we introduced a novel synthesis method with analytical solutions provided for synthesizing the lower-limb exoskeleton. Furthermore, we proposed a mathematical model of multicriteria optimization; as a result, we obtained several lower-limb exoskeleton mechanisms comprising only six links, well-suited to the human anatomical structure, exhibit superior trajectory accuracy, efficient force transmission, satisfactory step height, and having internal transfer segment of the foot. © 2023 by the authors.

The article presents the results of experimental studies of the effect of the stabilizing MgO dopant using the electron spin resonance (ESP) method on enhancement of the stability of Li2ZrO3 ceramics to defect formation processes and accumulation of radiolysis products in the near-surface layer in the case of high-dose irradiation with protons simulating the hydrogenation effects characteristic of processes associated with tritium production. During the conducted studies, it was established that the addition of the stabilizing MgO dopant results in formation of inclusions in the form of the tetragonal MgLi2ZrO4 phase, which leads to an increase in the resistance of the near-surface layers to destructive damage due to the accumulation of structural damage (oxygen vacancies and point defects), as well as products of the physicochemical processes of radiolysis, characteristic of high irradiation fluence values. It was found that in the case of unmodified Li2ZrO3 ceramics, the formation of HC2 – centers is observed at a fluence of 1016 proton/cm2, while for two-phase ceramics, the formation of HC2 – centers is observed at higher fluences, while the intensity of the bands is significantly less than in the case of single-phase unmodified ceramics. The difference in the nature of changes in the intensities of singlet bands responsible for the presence of vacancy defects in the damaged layer, as well as HC2 – centers for single-phase and two-phase ceramics is a direct confirmation of the inhibition of structural degradation mechanisms in two-phase ceramics.

During the conducted studies, it was established that the use of ion modification by irradiation with O+ and Ar+ ions makes it possible to elevate the degradation resistance of anode materials due to the effect of vacancy defect creation, the density of which varies with the irradiation fluence. At the same time, the analysis of changes in the band gap and the optical density value, expressing changes in structural distortions, revealed that ion irradiation leads to a rise in the stability of the preservation of electronic properties during long-term resource tests, which are inextricably linked with the degradation of ZnO/CoZn nanostructures due to oxidation processes as a result of lithiation. During assessment of changes in the parameters of the band gap and optical density of the samples after resource tests, it was found that the observed growth in these indicators is due to oxidation processes and partial amorphization due to the formation of oxide inclusions in the structure of nanowires, the presence of which is due to the interaction of nanostructures with the electrolyte over a long period of time during charging/discharging, which results in near-surface layer degradation due to the introduction of oxygen, and in the case of a long service life, to the formation of oxide inclusions that elevate the density of defects and vacancies in the structure. According to tests of synthesized ZnO/CoZn nanostructures as anode materials, it was found that the use of O+ and Ar+ ions not only leads to a growth in the degradation resistance of capacitive characteristics during long-term tests, but also to the stability maintenance of indicators with a reversible decrease in the charging rate at charging rate variation.

This study evaluates the applicability of optical spectroscopy and X-ray diffraction techniques for determining the lower detection limit of latent track density in polymer nuclear-track detectors exposed to α-particles from simulated radon decay products using Americium-241 sources. The results demonstrate that both UV optical spectroscopy and X-ray diffraction can detect latent track densities as low as 10⁴ tracks/cm². The research further reveals that increasing track density leads to significant structural and optical changes in the polymer, including anisotropic variations in electron density, deformation-induced stresses, and molecular structure distortions. A strong correlation was found between optical and structural characteristics across different irradiation levels.

Typical leg exoskeletons employ open-loop kinematic chains with motors placed directly on movable joints; while this design offers flexibility, it leads to increased costs and heightened control complexity due to the high number of degrees of freedom. The use of heavy servo-motors to handle torque in active joints results in complex and bulky designs, as highlighted in the existing literature. In this analytical study, we introduced a novel synthesis method with analytical solutions provided for synthesizing the lower-limb exoskeleton. Furthermore, we proposed a mathematical model of multicriteria optimization; as a result, we obtained several lower-limb exoskeleton mechanisms comprising only six links, well-suited to the human anatomical structure, exhibit superior trajectory accuracy, efficient force transmission, satisfactory step height, and having internal transfer segment of the foot. © 2023 by the authors.

This study was conducted to assess the applicability of artificial neural networks (ANN) for forecasting the dynamics of uranium extraction over exploitation time during the process of In Situ Leaching (ISL). Currently, ISL process simulation involves multiple steps, starting with geostatistical interpolation, followed by computational fluid dynamics (CFD) and reactive transport simulation. While extensive research exists detailing each of these steps, machine learning techniques may offer the potential to directly obtain extraction curves (i.e., the concentration of the mineral produced over the exploitation time of the deposit), thereby bypassing these computationally expensive steps. As a basis, both an empirical experimental configuration and reactive transport simulations were used to generate training data for the neural network model. An ANN was constructed, trained, and tested on several test cases with different initial parameters, then the expected outcomes were compared to those derived from conventional modeling techniques. The results indicate that for the employed experimental configuration and a limited number of features, artificial intelligence technologies, specifically regression-based neural networks can model the recovery rate (or extraction degree) of the ISL process for mineral production, achieving a high degree of accuracy compared to traditional CFD and mass transport models. © 2024 by the authors.

This study investigates the feasibility of predicting students’ critical thinking levels using machine learning techniques applied to academic and behavioral data. Recognizing critical thinking as a core competency in modern education is yet notoriously difficult to measure directly. This research aims to establish relationship between critical thinking proficiency and quantifiable variables such as an academic performance, extracurricular involvement, and course selection. A dataset comprising 500 anonymized student records was compiled and preprocessed to extract relevant features. Three predictive models—Linear Regression, Decision Tree, and Random Forest Regressor—were trained and evaluated using standard performance metrics. Among the three, the Random Forest model achieved the highest predictive accuracy with an R2 score of 0.84, substantially outperforming the Decision Tree (0.65) and Linear Regression (0.37) models. The results indicate that patterns in students’ course preferences, levels of academic achievement, and engagement in non-academic activities collectively provide meaningful insights into their critical thinking capacity. These findings demonstrate that viability of data-driven frameworks for indirectly assessing cognitive skills and have potential applications in curriculum design, early intervention systems, and educational approach policy development. By leveraging accessible education data, the proposed approach contributes to more scalable, objective, and personalized evaluation strategies within broader domain of learning analytics