One of the most important ways to achieve the goals stipulated by the Paris (2015) Agree-ment on climate change is to solve a two-fold task: 1) the adsorption of CO2 by the forest communities fcom the atmosphere during global warming and 2) their adaptation to these climate changes, which should ensure the effectiveness of adsorption itself. Report presents the regional experience of the numerical solution of this task. Calculations of the carbon balance of forests in the Oka-Volga River basin were carried out for global forecasts of moderate and extreme warming. The proposed index of labile elastic-plastic stability of forest ecosystems, which characterizes their succession-restorative po-tential, was used as an indicator of adaptation. A numerical experiment was conducted to assess the effect of the elastic-plastic stability of forest formations and the predicted climatic conditions on the carbon balance. In the upcoming 100-year forecast period, the overall stability of forest formations should increase, and to the greatest extent with extreme warming. Accordingly, one should expect a significant increase in the ability of boreal forests to ab-sorb greenhouse gases. It is determined unambiguous picture of a significant increase in the adsorption capacity of boreal forests with a rise in their regenerative potential.

In order to meet the guidance, publicity and commercial functions, various types of billboards have become important permanent facilities in the airport terminal, which are distributed all over the terminal. The advertising materials inside billboards have certain fire hazards, and there is a lack of research on the fire risk of advertising materials at present. Therefore, it is necessary to study the fire risk of advertising materials in airport terminal. Taking PVC board, a commonly used advertising material, as the research object, Pyrosim was used to model and analyze its fire, and the characteristics of fire spread, smoke flow, and distribution of combustion products such as CO and CO2 in the terminal building were obtained. This study explores the fire combustion characteristics of advertising materials in civil airport terminals, providing a basis for fire prevention management in civil airport terminals.

The use of porous media to simplify the thermohydraulic of a nuclear reactor is the topic of recent research. As a case study, the rector of 200 kW installed at Missouri University of Science and Technology is modeled in this paper. To help this objective, a fundamental CFD examination was completed to supplement the neutronics investigation on the present reactor. Characteristics of thermal energy removal from a typical research reactor are modeled by numerical thermal transport in porous media. The neutron flux is modeled by the nodal expansion method. For the thermo-hydraulic part, a three-dimensional governing equation is solved by an iterative method to find the steady-state solution of fluid flow and temperature in loss of coolant condition where the heat produced in the reactor core is removed by free convection. The profiles of heat flux for various power levels are benchmarked. Pressure, temperature, and velocity contours in the power passage were assessed at 300 kW and 500 kW power levels. To reduce the computational cost, a porous media approach for the whole geometry was utilized. The numerical results agree with the experimental results. The developed model can be used for safety and reliability analysis for various loss of coolant accidents.

In order to understand the finishing effect of Waterborne Acrylic Paint under different painting methods and amount, bamboo-laminated lumber for furniture was coated with waterborne acrylic paint, then the effects of different painting methods and amount on the drying rate, smoothness, hardness, adhesion and wear resistance of the paint film were investigated. Further, the mechanism of film formation was described by thermal property analysis using thermogravimetry and differential scanning calorimeter. The results show that different painting methods have little effect on film properties, the drying time of primer and topcoat are not affected by them, which is 8/8.5 min for primer surface/solid and 6.5/7 min for topcoats. The film surface hardness and adhesion can reach B and 0 grade, the best wear resistance of the film is 51.24 mg·100 r⁻¹ when using one-layer primer one-layer topcoat. Different coating amount has great influence on film properties, the drying speed of the film increases with the increase of the painting amount. The film properties reach the best when the painting amount is 80 g/m², while too little painting amount leads to the decrease of hardness, and too much leads to the wear resistance weaken. Thermal analysis of the primer and topcoat show that water decomposition occurs at 100 ℃ and thermal decomposition of organic components occur at 350 ℃. Topcoats have better thermal stability than primers higher than that of topcoat, the topcoat displayed better thermal stability than the primer.

This research underscores the importance of enhancing the early detection of diabetic retinopathy and glaucoma, two prominent culprits behind vision loss. Typically, retinal diseases lurk without symptoms until they inflict severe vision impairment, underscoring the critical need for early identification. The research is centered on the potential of leveraging fundus images, which offer invaluable insights by analyzing various attributes of retinal blood vessels, such as their length, width, tortuosity, and branching patterns. The conventional practice of manually segmenting retinal vessels by medical professionals is both intricate and time-consuming, demanding specialized expertise. This approach, reliant on pathologists, grapples with limitations related to scalability and accessibility. To surmount these challenges, the research introduces an automated solution employing computer vision. It conducts an evaluation of diverse retinal vessel segmentation and classification methods, including machine learning, filtering-based, and model-based techniques. Robust performance assessments, involving metrics like the true positive rate, true negative rate, and accuracy, facilitate a comprehensive comparison of these methodologies. The ultimate goal of this research is to create more efficient and accessible diagnostic tools, consequently enhancing the early detection of eye diseases through automated retinal vessel segmentation and classification. This endeavor combines the capabilities of computer vision and deep learning to pioneer new benchmarks in the realm of biomedical imaging, thereby addressing the pressing issues surrounding eye disease diagnosis.