Forest fire, as a discontinuous ecological factor of forest, causes the changes of carbon storage and carbon distribution in forest ecosystem, and affects the process of forest succession and national carbon capacity. Taking the burned land with different forest fire interference intensity as the research object, using the comparison method of adjacent sample plots, and taking the combination of field investigation sampling and indoor test analysis as the main means, this paper studies the influence of different forest fire interference intensity on the carbon pool of forest ecosystem and the change and spatial distribution pattern of ecosystem carbon density, and discusses the influence mechanism of forest fire interference on ecosystem carbon density and distribution pattern. The results showed that forest fire disturbance reduced the carbon density of vegetation (P < 0.05). The carbon density of vegetation in the light, moderate and high forest fire disturbance sample plots were 67.88, 35.68 and 15.50 t∙hm^-2, which decreased by 15.86%, 55.78% and 80.79% respectively compared with the control group. In the light, moderate and high forest fire disturbance sample plots, the carbon density of litter was 1.43, 0.94 and 0.81 t∙hm^-2, which decreased by 28.14%, 52.76% and 59.30% respectively compared with the control group. The soil organic carbon density of the sample plots with different forest fire disturbance intensity is lower than that of the control group, and the reduction degree gradually decreases with the increase of soil profile depth. The soil organic carbon density of the sample plots with light, moderate and high forest fire disturbance is 103.30, 84.33 and 70.04 t∙hm^-2 respectively, which is 11.670%, 27.899% and 40.11% lower than that of the control group respectively; the carbon density of forest ecosystem was 172.61, 120.95 and 86.35 t∙hm^-2 after light, moderate and high forest fire disturbance, which decreased by 13.53%, 39.41% and 56.74% respectively compared with the control group; forest fire disturbance reduced the carbon density of eucalyptus forest, which showed a law of carbon density decreasing with the increase of forest fire disturbance intensity. Compared with the control group, the effect of light forest fire disturbance intensity on the carbon density of eucalyptus forest was not significant (P > 0.05), while the effect of moderate and high forest fire disturbance intensity on the carbon density of eucalyptus forest was significant (P < 0.05).

An α, α^′-dipyridyl adduct of a complex compound hexaaquatribenzene-1,2,4,5-tetracarbonatotetra iron (III) with porous structure was synthesized for the first time. According to the results of elemental, X-ray, IR-spectroscopic and differential-thermal analyses the individuality, chemical formula, thermal destruction, and form of coordination of acidic anion and dipyridyl were established. During interaction of a complex compound with dipyridyl, it completely loses all crystallization molecule of water resulting in a compound with a chemical formula of Fe₄(C₆H₂(COO)₄)₃(dpy)₂(dipyridyl). Using the identification of diffraction pattern the parameters of lattice cell of the complex compound were determined.

This study provides empirical data on the impact of generative AI in education, with special emphasis on sustainable development goals (SDGs). By conducting a thorough analysis of the relationship between generative AI technologies and educational outcomes, this research fills a critical gap in the literature. The insights offered are valuable for policymakers seeking to leverage new educational technologies to support sustainable development. Using Smart-PLS4, five hypotheses derived from the research questions were tested based on data collected from an E-Questionnaire distributed to academic faculty members and education managers. Of the 311 valid responses, the measurement model assessment confirmed the validity and reliability of the data, while the structural model assessment validated the hypotheses. The study’s findings reveal that New Approaches to Learning Outcome Assessment (NALOA) significantly contribute to achieving SDGs, with a path coefficient of 0.477 (p < 0.001). Similarly, the Use of Generative AI Technologies (UGAIT) has a notable positive impact on SDGs, with a value of 0.221 (p < 0.001). A Paradigm Shift in Education and Educational Process Organization (PSEPQ) also demonstrates a significant, though smaller, effect on SDGs with a coefficient of 0.142 (p = 0.008). However, the Opportunities and Risks of Generative AI in Education (ORGIE) study did not find statistically significant evidence of an impact on SDGs (p = 0.390). These findings highlight the potential opportunities and challenges of using generative AI technologies in education and underscore their key role in advancing sustainable development goals. The study also offers a strategic roadmap for educational institutions, particularly in Oman to harness AI technology in support of sustainable development objectives.

This comprehensive review explores the forefront of nanohybrid materials, focusing on the integration of coordination materials in various applications, with a spotlight on their role in the development of flexible solar cells. Coordination material-based nanohybrids, characterized by their unique properties and multifunctionality, have garnered significant attention in fields ranging from catalysis and sensing to drug delivery and energy storage. The discussion investigates the synthesis methods, properties, and potential applications of these nanohybrids, underscoring their versatility in materials science. Additionally, the review investigates the integration of coordination nanohybrids in perovskite solar cells (PSCs), showcasing their ability to enhance the performance and stability of next-generation photovoltaic devices. The narrative further expands to encompass the synthesis of luminescent nanohybrids for bioimaging purposes and the development of layered, two-dimensional (2D) material-based nanostructured hybrids for energy storage and conversion. The exploration culminates in an examination of the synthesis of conductive polymer nanostructures, elucidating their potential in drug delivery systems. Last but not least, the article discusses the cutting-edge realm of flexible solar cells, emphasizing their adaptability and lightweight design. Through a systematic examination of these diverse nanohybrid materials, this review sheds light on the current state of the art, challenges, and prospects, providing valuable insights for researchers and practitioners in the fields of materials science, nanotechnology, and renewable energy.

Brunei Darussalam is a small Sultanate country with diverse forest cover. One of them would be Mangrove Forest. As it has four main administrative districts, Temburong would be the chosen case study area. The methods of collecting data for this article are by collecting secondary data from official websites and the map in this article (Figure 1) are showing the forest cover in Brunei Darussalam as of 2020. The aim of this article is to explain the mangrove forest especially at the Temburong District. As for the objectives, it would to be able to show the different types of forests in Temburong, hoping in ability to explain the different subtypes of mangroves forest and to explain in general the green jewel of Brunei Darussalam. Temburong has become the second highest tree coverage in Brunei Darussalam of 124 kha as of 2010, while the mangrove forest covering about 66% of total mangrove forest of 12,164 km² out of 18,418 hectares. Mangrove forest has seven subtypes: Bakau species, Nyireh bunga, Linggadai, Nipah, Nipah-Dungun, Pedada and Nibong. Selirong Forest Reserve and Labu Forest Reserve are the two-mangrove forest reserves in Brunei Darussalam at Temburong District. Forest cover in Brunei Darussalam are 3800 hectares as of 2020 and has lost its tree coverage of 1.17 kha and one of the reasons would be forest fire and the tree cover loss due to fire is around 197 ha and the district that has lost its tree cover mostly was at Belait District of total 13.4 kha between the year 2001 until 2022.

Prepolymers containing isocyanates must be prevented from curing when exposed to moisture, which can be achieved by blocking the isocyanate groups with a suitable agent. The study carefully examines several blocking agents, including methyl ethyl ketoxime (MEKO), caprolactam, and phenol, and concludes that methyl ethyl ketoxime is the best choice. Spectroscopic and thermal analyses, as well as oven curing studies, are conducted with various blocking agents and isocyanate prepolymer to castor oil ratios, revealing MEKO to be the most effective blocking agent which gets unblocked at higher temperatures.