The role of trace gases in the storage of heat in the atmosphere of the Earth and in the exchange of energy between the atmosphere and outer space is discussed. The molar heat capacities of the trace gases water vapor, carbon dioxide and methane are only slightly higher than those of nitrogen and oxygen. The contribution of trace gases carbon dioxide and methane to heat storage is negligible. Water vapor, with its higher concentration and conversion energies, contributes significantly to the heat storage in the atmosphere. Most of the heat in the Earth’s atmosphere is stored in nitrogen and oxygen, the main components of the atmosphere. The trace gases act as converters of infrared radiation into heat and vice versa. They are receivers and transmitters in the exchange of energy with outer space. The radiation towards space is favored compared to the reflection towards the surface of the Earth with increasing altitude by decreasing the density of the atmosphere and condensation of water vapor. Predictions of the development of the climate over a century by extrapolation are critically assessed.

We develop a relatively cheap technology of processing a scrap in the form of already used tungsten-containing products (spirals, plates, wires, rods, etc.), as well not conditional tungsten powders. The main stages of the proposed W-scrap recycling method are its dispersing and subsequent dissolution under controlled conditions in hydrogen peroxide aqueous solution resulting in the PTA (PeroxpolyTungstic Acid) formation. The filtered solution, as well as the solid acid obtained by its evaporation, are used to synthesize various tungsten compounds and composites. Good solubility of PTA in water and some other solvents allows preparing homogeneous liquid charges, heat treatment of which yield WC and WC–Co in form of ultradispersed powders. GO (Graphene Oxide) and PTA composite is obtained and its phase transition in vacuum and reducing atmosphere (H₂) is studied. By vacuum-thermal exfoliation of GO–PTA composite at 170–500℃ the rGO (reduced GO) and WO_2.9 tungsten oxide are obtained, and at 700℃—rGO–WO₂ composite. WC, W₂C and WC–Co are obtained from PTA at high temperature (900–1000℃). By reducing PTA in a hydrogen atmosphere, metallic tungsten powder is obtained, which was used to obtain sandwich composites with boron carbide B₄C, W/B₄C, and W/(B₄C–W), as neutron shield materials. Composites of sandwich morphology are formed by SPS (Spark-Plasma Sintering) method.

This study aims to examine the entrepreneurial activities of 240 women in the districts of Konaseema, East Godavari, and Kakinada during 2021–2022, focusing on the diverse range of 286 enterprises they managed across 69 business types. These enterprises were tailored to local resources and market demands, with coconut wholesale, cattle breeding, and provision shops being the most common. The study also analyzes income distribution, noting that one-third of the women earned between ₹50,000–1,00,000 annually, while only 0.70% earned over ₹5,00,000. More than half of the enterprises served as the primary income source for their families. The research highlights the significant role these women entrepreneurs play in their communities, their job satisfaction derived from financial independence and social empowerment, and the challenges they face, such as limited capital and market access. Finally, the study offers recommendations to empower these women to seize entrepreneurial opportunities and enhance their success.

Presently, there exists a burgeoning trend of female entrepreneurs worldwide, notably within the realm of small and medium-sized enterprises (SMEs), many of which manifest as family-run enterprises. The systematic literature review endeavors to construct an integrative framework concerning the practical ramifications of female involvement in family businesses by amalgamating extant global studies. The findings elucidate the practical implications inherent in female participation across global family businesses, concurrently furnishing a reservoir of prospects for prospective investigations. The deduction posits the imperative eradication of gender disparities, cognizant that gender parity underpins economic and financial advancement and is contingent upon female involvement. Furthermore, familial enterprises are urged to acknowledge and integrate women’s contributions in entrepreneurial decision-making processes.

Brain tumors are a primary factor causing cancer-related deaths globally, and their classification remains a significant research challenge due to the variability in tumor intensity, size, and shape, as well as the similar appearances of different tumor types. Accurate differentiation is further complicated by these factors, making diagnosis difficult even with advanced imaging techniques such as magnetic resonance imaging (MRI). Recent techniques in artificial intelligence (AI), in particular deep learning (DL), have improved the speed and accuracy of medical image analysis, but they still face challenges like overfitting and the need for large annotated datasets. This study addresses these challenges by presenting two approaches for brain tumor classification using MRI images. The first approach involves fine-tuning transfer learning cutting-edge models, including SEResNet, ConvNeXtBase, and ResNet101V2, with global average pooling 2D and dropout layers to minimize overfitting and reduce the need for extensive preprocessing. The second approach leverages the Vision Transformer (ViT), optimized with the AdamW optimizer and extensive data augmentation. Experiments on the BT-Large-4C dataset demonstrate that SEResNet achieves the highest accuracy of 97.96%, surpassing ViT’s 95.4%. These results suggest that fine-tuning and transfer learning models are more effective at addressing the challenges of overfitting and dataset limitations, ultimately outperforming the Vision Transformer and existing state-of-the-art techniques in brain tumor classification.

Conspiracy theories during Covid-19 pandemic spread worldwide, including in Indonesia. What political and religious factors explain their spread in Indonesia with particular reference to the DKI Jakarta province, its surrounding municipalities, and West Sumatera province? This study aimed to answer the questions. It employed a qualitative approach with multi-data collection methods, including those from media, documents, and interviews. The spread of Conspiracy theories benefited from the democratic system that promotes the freedom of information in using social media. First, the government officials initially spread conspiracy theories to satisfy people’s anxiety about the obscured Pandemic. However, they resulted in the government’s ambiguous, controversial, and reckless policies leading to people’s distrust of the government. Jokowi-Makruf Amien, political opponents capitalized on the government’s poor policies to spread conspiracy theories which partly discredited the Jokowi-Amien administration. Both government officials and the opposition capitalized on politics and religious teaching or supra-natural pretexts to posit their conspiracy theories.