In this study, robust and defect-free thin film composite (TFC) forward osmosis (FO) membranes have been successfully fabricated using ceramic hollow fibers as the substrate. Polydopamine (PDA) coating under controlled conditions is effective in reducing the surface pores of the substrate and making the substrate smooth enough for interfacial polymerization. The pure water permeability (A), solute permeability (B), and structural parameter (S) of the resultant FO membrane are 0.854 L·m^–2·h⁻¹·bar⁻¹ (LMH/Bar), 0.186 L·m^–2·h⁻¹ (LMH), and 1720 µm, respectively. The water flux and reverse draw solute flux are measured using NaCl and proprietary ferric sodium citrate (FeNaCA) draw solutions at low and high osmotic pressure ranges. As the osmotic pressure increases, a higher water flux is obtained, but its increase is not directly proportional to the increase in the osmotic pressure. At the membrane surface, the effect of dilutive concentration polarization is much less serious for FeNaCA-draw solutions. At an osmotic pressure of 89.6 bar, the developed TFC membrane generates water fluxes of 11.5 and 30.0 LMH using NaCl and synthesized FeNaCA draw solutions. The corresponding reverse draw solute flux is 7.0 g·m^–2·h⁻¹ (gMH) for NaCl draw solution, but it is not detectable for FeNaCA draw solution. This means that the developed TFC FO membranes are defect-free and their surface pores are at the molecular level. The performance of the developed TFC FO membranes is also demonstrated for the enrichment of BSA protein.

The present work conducts a comprehensive thermodynamic analysis of a 150 MW_e Integrated Gasification Combined Cycle (IGCC) using Indian coal as the fuel source. The plant layout is modelled and simulated using the “Cycle-Tempo” software. In this study, an innovative approach is employed where the gasifier's bed material is heated by circulating hot water through pipes submerged within the bed. The analysis reveals that increasing the external heat supplied to the gasifier enhances the hydrogen (H₂) content in the syngas, improving both its heating value and cold gas efficiency. Additionally, this increase in external heat favourably impacts the Steam-Methane reforming reaction, boosting the H₂/CH₄ ratio. The thermodynamic results show that the plant achieves an energy efficiency of 44.17% and an exergy efficiency of 40.43%. The study also identifies the condenser as the primary source of energy loss, while the combustor experiences the greatest exergy loss.

The cost of diagnostic errors has been high in the developed world economics according to a number of recent studies and continues to rise. Up till now, a common process of performing image diagnostics for a growing number of conditions has been examination by a single human specialist (i.e., single-channel recognition and classification decision system). Such a system has natural limitations of unmitigated error that can be detected only much later in the treatment cycle, as well as resource intensity and poor ability to scale to the rising demand. At the same time Machine Intelligence (ML, AI) systems, specifically those including deep neural network and large visual domain models have made significant progress in the field of general image recognition, in many instances achieving the level of an average human and in a growing number of cases, a human specialist in the effectiveness of image recognition tasks. The objectives of the AI in Medicine (AIM) program were set to leverage the opportunities and advantages of the rapidly evolving Artificial Intelligence technology to achieve real and measurable gains in public healthcare, in quality, access, public confidence and cost efficiency. The proposal for a collaborative AI-human image diagnostics system falls directly into the scope of this program.

Infrared thermal imaging technology is another new branch for medical imaging after traditional medical imaging technologies such as X-ray, ultrasound and magnetic resonance (MRI). It has the advantages of noninvasive, nondestructive, simple and fast. Its application can radiate multiple clinical departments. This paper mainly expounds the principle, influencing factors of medical infrared thermography and its application in radiation protection and other medical fields.

COVID-19 has amplified existing imbalances, institutional and financing constraints associated with a development strategy that did not take sufficient account of challenges with emissions, environmental damage and health risks associated with climate change in a number of countries, including China. The recovery from the pandemic can be combined with appropriately designed investments that take into account human, social, natural and physical capital, as well as distributional objectives, that can also address commitments under the Paris agreement. An important criterion for sustainable development is that the tax regimes at the national and sub-national levels should reflect the same criteria as the investment strategy. Own-source revenues, are essential to be able to access private financing, including local government bonds and PPPs in a sustainable manner. Governance criteria are also important including information on the buildup of liabilities at all levels of government, to ensure transparent governance.
Despite differences in political systems, the Chinese experiences are relevant in a wide range of emerging market countries as the measures utilize institutions and policies reflecting international best practices, including modern tax administrations for the VAT, and income taxes, and benefit-linked property taxes, as well as utilization of balance sheets information consistent with the IMF’s Government Financial Statistics Manual, 2014. The options have significant implications for policy advice and development cooperation for meeting global climate change goals while ensuring sustainable employment generation with transparency and accountability.

Green manufacturing is increasingly becoming popular, especially in lubricant manufacturing, as more environmentally friendly substitutes for mineral base oil and synthetic additives are being found among plant extracts and progress in methodologies for extraction and synthesis is being made. It has been observed that some of the important performance characteristics need enhancement, of which nanoparticle addition has been noted as one of the effective solutions. However, the concentration of the addictive that would optimised the performance characteristics of interest remains a contending area of research. The research was out to find how the concentration of green synthesized aluminum oxide nanoparticles in nano lubricants formed from selected vegetable oils influences friction and wear. A bottom-up green synthesis approach was adopted to synthesize aluminum oxide (Al₂O₃) from aluminum nitrate (Al(NO₃)₃) precursor in the presence of a plant-based reducing agent—Ipomoea pes-caprae. The synthesized Al₂O₃ nanoparticles were characterized using TEM and XRD and found to be mostly of spherical shape of sizes 44.73 nm. Al₂O₃ nanoparticles at different concentrations—0.1 wt%, 0.3 wt%, 0.5 wt%, 0.7 wt%, and 1.0 wt%—were used as additives to castor, jatropha, and palm kernel oils to formulate nano lubricants and tested alternately on a ball-on-aluminum (SAE 332) and low-carbon steel Disc Tribometer. All the vegetable-based oil nano lubricants showed a significant decrease in the coefficient of friction (CoF) and wear rate with Ball-on-(aluminum SAE 332) disc tribometer up to 0.5wt% of the nanoparticle: the best performances (e_COF = 92.29; e_WR = 79.53) came from Al₂O₃-castor oil nano lubricant and Al₂O₃-palm kernel oil; afterwards, they started to increase. However, the performance indices displayed irregular behaviour for both COF and Wear Rate (WR) when tested on a ball-on-low-carbon steel Disc Tribometer.