Higher and Technical Education Department

Global mental health is seriously threatened by environmental pollution, which is also rather increasing. Examining the complex link between several types of environmental pollution and a spectrum of mental diseases, this chapter offers a methodical review of material published mainly between 2007 and 2024. The chapter concludes with emphasizing the critical need of integrated public health policies, strict pollution control measures, sustainable urban planning, and focused interventions to minimize the widespread negative effects of environmental pollution on population mental health and support resilient communities.

This chapter explores the concept of nurturing organized imagination through the integration of emotional intelligence in education. Emotional intelligence plays a crucial role in shaping individuals' thoughts, behaviors, and interactions, offering promising potential in the educational realm. By understanding and effectively managing emotions, students and educators can unleash their creative thinking and problem-solving abilities. The chapter delves into the significance of emotional intelligence in maintaining emotional integrity across various social contexts and its alignment with the neo-humanistic approach in education. It highlights the importance of observing, experiencing, interpreting, and managing human tendencies to foster emotional assimilation and positive outcomes. Moreover, the chapter emphasizes the value of incorporating emotional intelligence in educational settings to cultivate a generation better equipped to navigate the complexities of modern society.

People’s views and values for wild animals are often a result of their experiences and traditional knowledge. Local folklore represents a resource that can enable an understanding of the nature of human-wildlife interactions, especially the underlying cultural values. Using archival searches and semi-structured interviews, we collected narratives about the ibex (Capra sibirica) (n = 69), and its predators, the wolf (Canis lupus) (n = 52) and the snow leopard (Panthera uncia) (n = 43), in Ladakh, India. We compared these stories to those of a mythical carnivore called seng ge or snow lion (n = 19), frequently referenced in local Tibetan Buddhist folklore and believed to share many of the traits commonly associated with snow leopards (except for livestock depredation). We then categorized the values along social-cultural, ecological and psychological dimensions. We found that the ibex was predominantly associated with utilitarianism and positive symbolism. Both snow leopard and wolf narratives referenced negative affective and negative symbolic values, though more frequently in the case of wolves. Snow leopard narratives largely focused on utilitarian and ecologistic values. In contrast, snow lion narratives were mostly associated with positive symbolism. Our results suggest that especially for snow leopards and wolves, any potentially positive symbolic associations appeared to be overwhelmed by negative sentiments because of their tendency to prey on livestock, unlike in the case of the snow lion. Since these values reflect people’s real and multifarious interactions with wildlife, we recommend paying greater attention to understanding the overlaps between natural and cultural heritage conservation to facilitate human-wildlife coexistence.

Objectives: COVID-19 pandemic is one of the prevalent challenges mankind has ever faced and there is a lot of uncertainty prevailing over the future with respect to COVID-19. In this situation machine learning algorithms can be useful for real-time analysis and prediction of trends of the infections. The objective of the research study is to analyze the COVID-19 trend in India and forecast the trend of outbreak in near future. This model can provisionally guide the government and healthcare organizations in making preparations for the upcoming situation arising out of COVID-19 transmission. Methods: The COVID-19 data from 30-Dec 2019 to 27-July 2020 was used for prediction of COVID-19 trend in next 30 days i.e. from 28 July to 26 August. The time series forecasting approaches with ARIMA Model and PROPHET were used for forecasting. The performance of these models was evaluated using validation metrics and good performance was indicated. Findings: The prediction results indicate an increasing trend of COVID-19 positive, active and deceased cases in India for next 30 days i.e. up to 26 August 2020. Novelty: COVID-19 pandemic is a new problem. The novelty and originality of this research lies in the fact that time series forecasting is used for real time analysis and prediction of COVID-19 pandemic. Keywords: COVID-19; time series analysis; ARIMA model; time series forecasting; PROPHET

Inorganic organic (IO) hybrids where inserted conducting organic polymer (COP) imprints their polymeric nature onto the hybrid material are one of the most promising candidates for solving many technological problems of modern technocratic society. The Inorganic-organic hybrid material of para toluidine (organic) & mercuric chloride (inorganic) was synthesized by using “instant-heating and slow-cooling” technique. Some light orange coloured plate-like crystals were obtained. XRD pattern of the grown crystal were analysed which shows that crystal has been grown into monoclinic crystal system in which a ≠ b ≠ c [10.061(4) Å ≠ 4.317(2) Å ≠ 12.987(5) Å] & α=γ= 90 o ≠ β [α = γ = 90 o , β=104.322(7) o ] and belongs to space group p2 1 .Analysis of secondary interactions shows that such material has potential application in opto electronics.

Magnetic nanoparticles due to their unique magnetic phenomenon, are gaining immense interest due to the utilization of these properties for a wide variety of applications in various arena especially in biomedical field. This book chapter, therefore, summarizes the synthesis of various types of magnetic nanoparticles using different approaches depending of their ability to generate either single core of multcore magnetic nanoparticles. The various biomedical applications of magnetic nanoparticles like Magnetic Resonance Imaging (MRI), drug delivery etc. along with possible limitations and challenges for their extended applications in medicine are also discussed.