Liquid Metal Battery (LMB) technology is a new research area born from a different economic and political climate that has the ability to address the deficiencies of a society where electrical energy storage alternatives are lacking. The United States government has begun to fund scholarly research work at its top industrial and national laboratories. This was to develop Liquid Metal Battery cells for energy storage solutions. This research was encouraged during the Cold War battle for scientific superiority. Intensive research then drifted towards high-energy rechargeable batteries, which work better for automobiles and other applications. Intensive research has been carried out on the development of electrochemical rechargeable all-liquid energy storage batteries. The recent request for green energy transfer and storage for various applications, ranging from small-scale to large-scale power storage, has increased energy storage advancements and explorations. The criteria of high energy density, low cost, and extensive energy storage provision have been met through lithium-ion batteries, sodium-ion batteries, and Liquid Metal Battery development. The objective of this research is to establish that Liquid Metal Battery technology could provide research concepts that give projections of the probable electrode metals that could be harnessed for LMB development. Thus, at the end of this research, it was discovered that the parameter estimation of the Li//Cd-Sb combination is most viable for LMB production when compared with Li//Cd-Bi, Li-Bi, and Li-Cd constituents. This unique constituent of the LMB parameter estimation would yield a better outcome for LMB development.

Resisting the adoption of medical artificial intelligence (AI), it is suggested that this opposition can be overcome by combining AI awareness, AI risks, and responsibility displacement. Through effective integration of public AI dangers and displacement of responsibility, some of these major concerns can be alleviated. The United Kingdom’s National Health Service has adopted the use of chatbots to provide medical advice, whereas heart disease diagnoses can be made by IBM’s Watson. This has the ability to improve healthcare by increasing accuracy, efficiency, and patient outcomes. The resistance may be due to concerns about losing jobs, anxieties about misdiagnosis or medical mistakes, and the consciousness of AI systems drifting more responsibility away from medical professionals. There is hesitancy among healthcare professionals and the general public about the deployment of AI, despite the fact that healthcare is being revolutionised by AI, its uses are pervasive. Participants’ awareness of AI in healthcare, AI risk, resistance to AI, responsibility displacement and ethical considerations were gathered through questionnaires. Descriptive statistics, chi-square tests and correlation analyses were used to establish the relationship between resistance and medical AI. The study’s objective seeks to collect data on primary and public AI awareness, perceptions of risk and feelings of displacement that the professionals have regarding medical AI. Some of these concerns can be resolved when AI awareness is effectively integrated and patients, healthcare providers, as well as the general public are well informed about AI’s potential advantages. Trust is built when, AI related issues such as bias, transparency, and data privacy are critically addressed. Another objective is to develop a seamless integration of risk management, communication and awareness of AI. Lastly to assess how this comprehensive approach has affected hospital settings’ ambitions to use medical AI. Fusing AI awareness, risk management, and effective communication can be used as a comprehensive strategy to address and promote the application of medical AI in hospital settings. An argument made by Chen et al. is that providing training in AI can improve adoption intentions while lowering complexity through the awareness of AI.

This article examines the history of Russian colonization in Kazakhstan, focusing on identity, resistance, and independence within Russia’s neo-imperial ambitions. It addresses the socio-political barriers in postcolonial Kazakhstan due to ties with Russia and explores how the Soviet migration policies shaped Kazakhstan’s demographic and political landscape. The study outlines the phases of Russian colonization, contrasting Russian narratives of a civilizing mission with Kazakh perspectives on exploitation and cultural erasure. Using postcolonial theory, it deconstructs these narratives and reveals power dynamics. Kazakh literature and poetry are analyzed as mediums of resistance, emphasizing the horse as a symbol of cultural identity. The article concludes by discussing the post-Soviet cultural transformations and the role of literature in nation-building, highlighting the importance of reclaiming cultural symbols and myths for understanding Kazakhstan’s colonial history and postcolonial transformation.

A numerical investigation utilizing water as the working fluid was conducted on a 2D closed loop pulsating heat pipe (CLPHP) using the CFD software AnsysFluent19.0. This computational fluid dynamics (CFD) investigation explores three instances where there is a consistent input of heat flux in the evaporator region, but the temperatures in the condenser region differ across the cases. In each case, the condenser temperatures are set at 10 ℃, 20 ℃, and 30 ℃ respectively. The transient simulation is conducted with uniform time steps of 10 s. Generally, the heat rejection medium operated at a lower temperature performs better than at a higher temperature. In this CFD study the thermal resistances gets decreased with the decreasing value of condenser temperatures and the deviation of 35.31% of thermal resistance gets decreased with the condenser region operated at the temperature of 10 ℃.

A Detailed geophysical investigation was conducted on Knossos territory of Crete Island. Main scope was the detection of underground archaeological settlements. Geophysical prospecting applied by an experienced geophysical team. According to area dimensions in relation to geological and structural conditions, the team designed specific geophysical techniques, by adopted non-catastrophic methods. Three different types of geophysical techniques performed gradually. Geophysical investigation consisted of the application of geoelectric mapping and geomagnetic prospecting. Electric mapping focusses on recording soil resistance distribution. Geomagnetic survey was performed by using two different types of magnetometers. Firstly, recorded distribution of geomagnetic intensity and secondly alteration of vertical gradient. Measured stations laid along the south-north axis with intervals equal to one meter. Both magnetometers were adjusted on a quiet magnetic station. Values were stored in files readable by geophysical interpretation software in XYZ format. Oasis Montaj was adopted for interpretation of measured physical properties distribution. Interpretation results were illustrated as color scale maps. Further processing applied on magnetic measurements. Results are confirmed by overlaying results from three different techniques. Geoelectric mapping contributed to detection of a few archaeological targets. Most of them were recorded by geomagnetic technique. Total intensity aimed to report the existence of magnetized bodies. Vertical gradient detected subsurface targets with clearly geometrical characteristics.