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.

Background: India’s rich educational heritage dates to ancient times, with popular institutions like Nalanda, Takshashila, and Banarasi-Kasi flourishing as early as the 6th century BC, which offered diverse courses spanning medicine, mathematics, astronomy, and more. Invasions by the Mughals and British during the 12th to 18th centuries disrupted India’s traditional education systems. Post-independence, India faced the challenge of transitioning from ancient to modern education. Remarkably, the country managed to preserve its popular traditional education through a strategic change management approach by the educational institutions. The Government of India has introduced in the National Education Policy 2020 (NEP 2020) in July 2020, to bring transformational reforms in school and higher education systems. In this manuscript, we have summarized the salient features of the NEP 2020 and the preparedness steps to its effective implementation in Indian educational institutions. Method: We have utilised standard databases like PubMed, Science Direct, or Google Scholar, and/or public domains and the NEP 2020 document for this literature survey. Value addition: NEP 2020 aims to ensure access, equity, quality, affordability, and accountability with more flexible curricular structure, and holistic approaches. Despite the COVID-19 pandemic’s impact, dynamic planning, and collaboration among public and private institutions, and industries supported the effective implementation of NEP 2020. Notably, the change management approach, which has been a constant throughout India’s educational journey, played a pivotal role in keeping pace with technological advancements and fostering growth in the higher education system in India.

No less than 60% of timber production in Peru’s natural forests is the result of informal or illegal extractive activities that, by definition, are not sustainable. This article aims to demonstrate that even legitimate timber, such as timber harvested in more than 6 million hectares of forest concessions, does not meet the basic requirements of sustainable forest management. Forestry legislation itself, which does not emphasize forest management, institutional weaknesses and the socioeconomic environment are the main causes. In addition, the cutting cycles and the authorized minimum diameters, among other practices, do not allow the renewal of the resource and increase its degradation.

Extensive research on pro-environmental behaviour (PEB) reveals a significant knowledge gap in understanding the influence of social class, perceived status and the middling tendency on pro-environmental behaviour. Using the International Social Survey Programme Environment dataset, and conducting multilevel mixed-effects linear regressions, we find that the middling tendency and biased status perceptions significantly influences pro-environmental behaviour. Those who deflate their social position have higher pro-environmental behavior and this reinforces the idea that pro-environmental behaviour is driven by a post-materialist effect rather than a status enhancement effect. Moreover, the objective middle class is still a stronger contributor to higher PEB levels compared to subjective middle class. We also find the relation between class, status and PEB vary by country. These findings provide vital insights into the intricate and heterogenous dynamics between class, status and pro-environmental behaviour among different countries and shed light on class and status as driving forces behind pro-environmental behaviour.

Breast cancer was a prevalent form of cancer worldwide. Thermography, a method for diagnosing breast cancer, involves recording the thermal patterns of the breast. This article explores the use of a convolutional neural network (CNN) algorithm to extract features from a dataset of thermographic images. Initially, the CNN network was used to extract a feature vector from the images. Subsequently, machine learning techniques can be used for image classification. This study utilizes four classification methods, namely Fully connected neural network (FCnet), support vector machine (SVM), classification linear model (CLINEAR), and KNN, to classify breast cancer from thermographic images. The accuracy rates achieved by the FCnet, SVM, CLINEAR, and k-nearest neighbors (KNN) algorithms were 94.2%, 95.0%, 95.0%, and 94.1%, respectively. Furthermore, the reliability parameters for these classifiers were computed as 92.1%, 97.5%, 96.5%, and 91.2%, while their respective sensitivities were calculated as 95.5%, 94.1%, 90.4%, and 93.2%. These findings can assist experts in developing an expert system for breast cancer diagnosis.

Given the growing significance of the metaverse in research, it is crucial to understand its scope, relevance in the tourism industry, and the human-computer interaction it involves. The emerging field of metaverse tourism has a noticeable research gap, limiting a comprehensive understanding of the concept. This article addresses this gap by conducting a hybrid systematic review, including a variable-oriented literature review, to assess the extent and scope of metaverse tourism. A scrutiny on Scopus identified a reduced number of relevant documents. The analysis exposes theoretical and empirical gaps, along with promising opportunities in the metaverse and tourism intersection. These insights contribute to shaping a contemporary research agenda, emphasizing metaverse tourism. While this study offers an overview of current research in metaverse tourism, it is essential to recognize that this field is still in its early stages, marked by the convergence of technology and transformations in tourism. This exploration underscores the challenges and opportunities arising from the evolving narrative of metaverse tourism.