Rama Devi Women's University

Traditional medical systems across the world have long employed plant-based remedies for the management of eye disorders. Ethnomedicinal knowledge plays a vital role in primary eye care. The present study compiles and analyses ethnomedicinal plants traditionally used for the treatment of various eye problems through literature survey. A total of 30 common plant species belonging to diverse botanical families were documented in this communication. It was noticed that leaves, roots, fruits, flowers and bark were the most frequently utilized plant parts while decoctions, extracts, distillates, pastes and eye washes constituted the major preparation methods. Several remedies were applied topically as eye drops or washes whereas others were consumed orally or used as dietary supplements. The continued use of these remedies highlights their perceived therapeutic efficacy and cultural importance. However, scientific validation, standardization and safety assessment remain limited for many formulations. Therefore, the paper highlights the need for pharmacological and clinical investigations to validate traditional claims and to support the development of safe and plant-based ophthalmic therapeutics.

Lepidoptera, as one of the diverse insect orders, play a very critical role in ecological and economic perspectives, yet it remains taxonomically challenging due to morphological convergence, cryptic diversity, and incomplete classification frameworks. Over the last two decades, DNA barcoding, primarily targeting the mitochondrial COI gene, has revolutionised species identification and biodiversity assessment. This mini-review summarises certain key advances in Lepidoptera barcoding across four thematic areas: large-scale biodiversity surveys; pest species diagnostics; cryptic species discovery; and future conservation planning. Case studies from tropical forests, island ecosystems, and high-altitude plateau ecozones have illustrated the precision and practical value of this method. However, gaps persist, including uneven representation in global databases, taxonomic instability in certain groups, and methodological inconsistencies across the whole taxonomic spectrum. We have discussed integrative approaches towards merging DNA barcoding with morphological, genomic, and ecological data, and outlined priorities for expanding coverage, improving accuracy, and embedding molecular identification into conservation policy. By harbouring both its achievements and limitations, this review has positioned “DNA barcoding” as a milestone technology for Lepidoptera systematics and applied biodiversity management in various important ecozones of Earth.

Photocatalysis can be considered as one of the leading scientific approaches for the conversion of solar energy to chemical energy to fulfill energy requirements. Upgrading the photocatalytic activity by minimizing photoexciton recombination is a practical challenge to the scientific community. Here, we have designed a Ti3C2 MXene-modified ZIF-8 MOF-derived C, N doped ZnO (CNZ)/B-doped g-C3N4 (BCN) photocatalytic system via the calcination route and studied its performance toward photocatalytic H2 evolution and H2O2 production reactions. Suitable physicochemical characterizations like XRD, FT-IR, XPS, EDX, FESEM, TEM, UV–vis DRS, and PL analyses have been performed, which unveiled the successful integration of Ti3C2 on binary CB (1:1). The mechanistic rationale behind meliorating the photocatalytic performance of the composite photocatalyst is primarily the well-built close contact between CNZ and BCN, observed from FESEM and HRTEM patterns. Moreover, the incorporation of multilayered Ti3C2 as a cocatalyst acts as an electron acceptor and expedites the spatial charge separation process supported by PL, TRPL, and electrochemical measurements. In addition, Ti3C2 MXene also provides rich active sites for eventual photocatalytic reactions. Impressively, the ternary photocatalyst CNZ/BCN/MXene (CBM-x) shows heightened photocatalytic performance when subjected to photocatalytic H2O2 production (3150.74 μmol h–1g–1), which reaches nearly 2-fold improvement over the binary CB (1:1) photocatalyst. Moreover, this optimized ternary composite achieved an enhanced H2 evolution rate of 14,495 μmol h–1 g–1. The present work provides a highly efficient cocatalyst-integrated photocatalyst system operated through the Z-scheme mechanism for large-scale energy generation.

Introduction: Today, the natural ventilation is emphasized to minimize the energy consumption. It also helps to decrease interior temperatures and maintain internal humidity. In this work, the effect of the rear window opening (factor-1), its position (factor-2) and also the effect of the position of a heat source (factor-3) on Air Exchange Efficiency (AEE) and Heat Source Surface Temperature (HSST) is evaluated. Materials and methods: The Taguchi Design of Experiment (DOE) is applied to shortlist nine simulations with different combinations of the levels for three factors. Then Computational Fluid Dynamics (CFD) simulations were performed and the responses (AEE & HSST) were recorded. The Signal-to- Noise (S/N) ratio values are evaluated separately for the responses and the rank table is prepared to see the impact of various factors for the best response value. Analysis of Variance (ANOVA) analysis is performed to evaluate the impact percentage of the factors to obtain the best responses. Results: From the mean S/N plots, the best and the worst combinations of levels of the factors for both responses are identified and then simulated. From the study, it is observed that the rear window opening and the window position has the highest and the lowest impact respectively to obtain the highest AEE. Similarly, the window position and the window opening have almost equal impact on lowering the HSST. Conclusion: The study concludes that proper positioning of window and its opening can be evaluated to get the best AEE and to transfer the maximum heat from the heat source in the room.

With the increasing number of devices being connected to the internet, the Internet of Things (IoT) has emerged as a promising technology to enhance the efficiency of various domains, including healthcare, transportation, and manufacturing. However, the reliability of IoT systems poses a significant challenge due to their distributed nature, heterogeneous devices, and dynamic environments. In this context, computational intelligence techniques have been employed to address the reliability issues of IoT systems. This article presents a comprehensive review of recent research on the application of computational intelligence techniques for enhancing the reliability of IoT systems. It provides an overview of IoT systems and the challenges they face concerning reliability. Also, discusses the principles and methodologies of computational intelligence techniques, including machine learning, deep learning, and evolutionary algorithms, and their potential applications in IoT reliability. Furthermore, this review work highlights several case studies that demonstrate the effectiveness of computational intelligence techniques in addressing various reliability issues in IoT systems, such as fault diagnosis, fault tolerance, and fault prediction. The case studies include the use of machine learning for fault detection in smart grids, deep learning for predictive maintenance in manufacturing, and the evolutionary algorithms for optimization of sensor placement in structural health monitoring.

Anthropogenic activities have increasingly led to habitat fragmentation and biodiversity loss across ecosystems worldwide, severely impacting species such as Lepidopterans, which act as ecological indicators. Among them, the Tropical Tasar Silkmoth (Antheraea mylitta Drury), a unique species endemic to India, which has been deeply woven into the lives and traditions of Scheduled Tribe and Scheduled Caste communities, has suffered heavy population losses as its natural habitats continue to shrink. This study investigates the distribution and genetic diversity of A. mylitta ecoraces across Odisha, where seven historical ecoraces have dwindled to five, with signs of local extinction in some regions. Through Cytochrome b as a mitochondrial molecular marker, phylogenetic analyses revealed the gene flow patterns consistent with geographical proximity but also uncovered unexpected genetic similarities, suggesting historical population mixing. Habitat degradation, primarily from mining and deforestation, has severely impacted tasar host plant availability, leading to a decline in the tasar silk production and threatening the wild ecorace survival. The findings highlight the critical need for conservation strategies focusing on habitat protection, genetic monitoring, and sustainable management to preserve A. mylitta populations and the forest ecosystems they symbolize.