The effect of isocyanate trimer on the flame retardancy mechanism of polyisocyanurate (PIR) foam was studied in three aspects, including the mechanism of thermal decomposition in the condensed phase, the barrier mechanism of carbon layer formation on the surface in the condensed phase, and the mechanism in the gaseous phase, by using infrared spectroscopy, scanning electron microscopy, thermal analysis, a cone calorimeter, and high-temperature pyrolysis gas chromatography mass spectrometry. The results show that the trimmer can improve the thermal stability of the PIR foam and is not easily decomposed in the combustion. The trimmer can increase the carbon content of the PIR foam to 29.9% of that of the polyurethane (PU) foam. The carbon layer formed is denser, and it can retard heat and oxygen and thus improve the flame retardant properties; trimer can reduce the release of flammable polyol gas, decompose into more carbon dioxide, which is an inert gas, and it has certain flame retardant effects in the gaseous phase.

Based on the collective forest with common use rights, the social-ecological system analysis framework and autonomous governance theory proposed by Elinor Ostrom are introduced in the forest eco-economic system to analyze the interaction logic among the first-level subsystems and the secondary variables of the forest eco-economic system and the variables related to the autonomous governance of the system to explore the synergistic mechanisms affecting the forest eco-economic system. The results show that: in the case of information asymmetry, collective actions of governmental and non-governmental organizations will aggravate the dilemma of forest eco-economic synergistic development; actors extract forest resource units from the forest resource system to achieve economic benefits; and renewable resources of forest ecosystems can be sustained in the long term when the average extraction rate of humans from forest ecosystems does not exceed the average replenishment rate.

The focus of the article is the evaluation of the interaction between regional state bodies and business structures in Kazakhstan, specifically in terms of the development of public-private partnerships. The purpose of the research is to enhance the understanding of the theoretical and practical aspects of the mechanism of interaction between the state and business structures. Through an examination of the various structural components of the partnership development strategy, the study aims to identify the elements of the mechanism for the implementation of the state and business development strategy. Additionally, the research seeks to establish the correlation between the outcomes of the joint entrepreneurship mechanism and the criteria used to evaluate the performance of regional state bodies. To assess the effectiveness of the interaction between business and government at the regional level in Kazakhstan, a survey-based evaluation was conducted to measure the satisfaction levels of public utilities, entrepreneurs, and businesses with the activities of local authorities. The survey also evaluated the degree of corruption among local authorities. A matrix of interaction between business and government was created, and various models and algorithms for the interaction between government representatives and business structures were studied. The research findings highlight the importance of enhancing the collaboration between the state and the business sector, promoting the implementation of public-private partnerships, and establishing social partnerships to cultivate mutually beneficial relationships.

Research into electro-conductive textiles based on conductive polymers like polypyrrole has increased in recent years due to their high potential applications in various fields. Conductive polymers behave like insulators in their neutral states, with typical electrical conductivity in the range 10^–10 to 10^–25 Scm^–1. These neutral polymers can be converted into semi-conductive or conductive states with conductivities ranging from 1 Scm^–1 to 10^–4 Scm^–1 through chemical or electro-chemical redox reactions. By applying these polymers to a textile surface, we can obtain novel composites that are strong, flexible, lightweight, and highly electroconductive. These textile composites are suitable for applications such as heating pads, sensors, corrosion-protecting materials, actuators, electrochromic devices, EMI shielding, etc. The methods of application of conductive polymers onto the textile surface, such as in-situ chemical, in-situ electrochemical, in-situ vapor phase, in-situ polymerization in a supercritical fluid, and solution coating processes, are described here briefly. The merits and demerits of these methods are mentioned here. The reaction mechanisms of chemical and electrochemical polymerization proposed by the different researchers are described. Different factors affecting the kinetics of chemical and electrochemical polymerization are accounted for. The influence of textile materials on the kinetics of chemical polymerization is reviewed and reported.

In view of the fact that the convolution neural network segmentation method lacks to capture the global dependency of infected areas in COVID-19 images, which is not conducive to the complete segmentation of scattered lesion areas, this paper proposes a COVID-19 lesion segmentation method UniUNet based on UniFormer with its strong ability to capture global dependency. Firstly, a U-shaped encoder-decoder structure based on UniFormer is designed, which can enhance the cooperation ability of local and global relations. Secondly, Swin spatial pyramid pooling module is introduced to compensate the influence of spatial resolution reduction in the encoder process and generate multi-scale representation. Multi-scale attention gate is introduced at the skip connection to suppress redundant features and enhance important features. Experiment results show that, compared with the other four methods, the proposed model achieves better results in Dice, loU and Recall on COVID-19-CT-Seg and CC-CCIII dataset, and achieves a more complete segmentation of the lesion area.