J.C. Bose University of Science and Technology, YMCA

Central nervous system (CNS) development commences in third week of gestation with neural stem cells (NSCs), which, through symmetric division, expand the pool of stem cells and generate diverse types of neuronal and glia cells of CNS via asymmetric division. During neurodevelopment, spatiotemporal coordination is fundamental for appropriate morphogenesis and producing neuronal connections. Besides gene regulatory networks, external and internal factors guide NSCs during self-renewal, fate determination and differentiation. Recent studies indicate metabolism as one of the common converging integrators in NSCs to trigger modifications in response to external factors. One such external factor is micronutrients that profoundly affect different stages of neurodevelopment, including, differentiation, neural migration and maturation. This review aims to provide a summary of recent insights into how metabolism and micronutrients regulate different events of neurodevelopment including proliferation, fate determination and differentiation. Notably, we focus on illustrating the implications of mitochondria as key determinants of NSC fate and functionality. We also highlight the recent development on how metabolism orchestrates the epigenome of NSCs during proliferation and differentiation. We further explore the role of nutraceuticals in mitigating the risk of neurodevelopmental and adult neurological disorders, highlighting recent innovations in their therapeutic applications. An in-depth grasp of these molecular processes is fundamental to improving translational strategies for treating neurological disorders.

The accumulation of discarded plastics contributes significantly to white pollution and biomagnification, positioning biodegradable plastics as a promising alternative. Currently, bioplastics account for less than 1

The current level of digital transformation is driving an increasing demand for achieving the triple bottom line sustainability. In this regard, banking 4.0 technologies can serve as a turning point in banking processes, contributing to sustainable development. In this context, this paper investigates how five pioneering technologies, such as artificial intelligence, blockchain, mobile banking, big data analytics, and cloud computing, influence the triple bottom line sustainability of the banking system, drawing on the dynamic capabilities view theory and upper echelon theory. A combination of structural equation modeling, necessary condition analysis, and a combined importance-performance map was applied to assess this model. A self-reported questionnaire was employed to collect data from 511 bank employees through purposive sampling. The findings confirmed that all five digital technologies influence triple bottom line sustainability, with each displaying varying performance and minimum levels based on their relative significance. The study results also demonstrated that financial inclusion, as a mediator, and top management commitment, as a moderator, can influence the interactions between the sustainability of the banking system and its predictions. The implications of this study can support practitioners and researchers in grasping that digitalization and sustainability are co-transformations rather than separate transformations unfolding in parallel.

Faridabad is among the most industrialized cities in India, with constantly high fine particulate matter (PM2.5) concentrations due to intensive industrial activities, traffic congestion, and combustion-related emissions. The samples of PM2.5 were collected at two representative sites of Faridabad from July 2022 to July 2023 to investigate the mass concentrations, elemental composition, source apportionment, and associated ecological risk. Statistical analysis showed that the mean PM2.5 concentrations (mean ± standard error) were 108 ± 16 µg m− 3 at site 1 and 154 ± 11 µg m− 3 at site 2, indicating substantially elevated particulate loadings in the study region. The mean PM2.5 levels were significantly above the national threshold levels, especially during post-monsoon and winter seasons. The samples were analysed using wavelength-dispersive X-ray fluorescence analysis, enabling the quantification of 27 elements. The Positive Matrix Factorization (PMF) analysis identified five major sources of PM2.5, including crustal dust, combustion, biomass burning, industrial emissions, and mixed sources, and the contribution of the sources was similar at both the sites. Industrial emission and combustion-related activities are dominant contributor to PM2.5 mass, while seasonal variability was mainly caused by meteorological conditions and episodic burning processes. Enrichment factor (EF) analysis established significant contribution of several toxic metals through anthropogenic sources. Although the contamination degree indicated localized high metal enrichment, both the pollution load index and the potential ecological risk suggested that the overall ecological risk remained the low to moderate range. The integrated results highlight the dominance of industrial and combustion activities in PM2.5 pollution in Faridabad and provide scientific evidence to support targeted emission control strategies rapidly growing urban-industrial regions.

Emotion recognition is fundamental to building socially intelligent robotic systems capable of effective and adaptive Human-Robot Interaction (HRI) and Collaboration (HRC). This literature review synthesizes recent advances from 2015 to 2025, covering 42 empirical studies focused on speech, facial, and multimodal emotion recognition approaches tailored for robotic contexts. We provide a modality-wise classification of methods, highlight key deep learning architectures and signal processing strategies, and analyze their performance across diverse robotic platforms and environments. Multimodal systems accounted for over 50