Explore the vast range of titles available.

In Indian mythology, feminist theory significantly shapes cultural narratives and practices. By challenging the male-dominated power structures prevalent in individual relationships and society at large, feminist interpretations shed light on the roles and concerns of female characters, questioning traditional patriarchal views. This feminist re-examination influences practices such as women's participation in rituals and worship and advocates for women's rights and gender equality. It also critiques patriarchal customs and traditions. Feminist perspectives have inspired new literary and artistic works, further amplifying feminist voices in Indian mythology. Epics like the Ramayana and Mahabharata portray mothers in complex and diverse ways, reflecting both patriarchal and feminist themes. A feminist approach to these texts acknowledges the empowering and restrictive aspects of these depictions, recognizing their historical and cultural contexts. Feminist attributes include complexity, refinement, critique of patriarchal values, and the recognition of nurturing and self-sacrificing motherhood as sources of strength. Mothers like Kausalya (Rama’s mother), Gandhari (Dhritarashtra’s wife), and Kunti (the mother of the Pandavas) wield significant influence over their sons, shaping their actions and decisions. These mothers are often portrayed as selfless caregivers, prioritizing their children’s needs above their own. While these portrayals highlight their strength and devotion, they also reinforce traditional feminine ideals. The epics critique the expectation of maternal self-sacrifice, as seen in Kunti’s sacrifices for her sons. Feminist theory reshapes cultural narratives and practices, promoting a more equitable society. Its influence continues to evolve, driving social change and challenging existing norms. The feminist movement has played a pivotal role in advocating for women's suffrage, greater access to education, and confronting societal injustices linked to class, culture, religion, sexuality, gender, race, and nationality. Feminist literary theory has deliberately transgressed traditional boundaries across literature, social sciences, and philosophy, helping us understand how gender has been constructed and represented through language.

This research paper presents a comprehensive assessment of the built-up area in Mysuru City over the decade spanning from 2010 to 2020, employing advanced geospatial techniques. The study aims to analyze the spatiotemporal patterns of urban expansion, land-use dynamics, and associated factors influencing the city’s built environment. Remote sensing imagery, Geographic Information System (GIS) tools, and machine learning algorithms are leveraged to process and interpret satellite data for accurate land-cover classification. The methodology involves the acquisition and preprocessing of multi-temporal satellite imagery to delineate and map the built-up areas at different time intervals. Land-use change detection techniques are employed to identify and quantify alterations in urban morphology over the specified period. Additionally, socio-economic and environmental variables are integrated into the analysis to discern the drivers of urban growth. The outcomes of this research contribute valuable insights into urbanization dynamics and land-use planning strategies, facilitating informed decision-making for sustainable urban development.

Land Use and Land Cover (LULC) classification is critical for monitoring and managing natural resources and urban development. This study focuses on LULC classification for change detection analysis of remotely sensed data using a machine learning-based Random Forest classifier. The research aims to provide a detailed analysis of LULC changes between 2010 and 2020. The Random Forest classifier is chosen for its robustness and high accuracy in handling complex datasets. The classifier achieved a classification accuracy of 86.56% for the 2010 data and 88.42% for the 2020 data, demonstrating an improvement in classification performance over the decade. The results indicate significant LULC changes, highlighting areas of urban expansion, deforestation, and agricultural transformation. These findings highlight the importance of continuous monitoring and provide valuable insights for policymakers and environmental managers. The study demonstrates the effectiveness of using advanced machine-learning techniques for accurate LULC classification and change detection in remotely sensed data.

Land Use and Land Cover (LULC) classification is critical for monitoring and managing natural resources and urban development. This study focuses on LULC classification for change detection analysis of remotely sensed data using a machine learning-based Random Forest classifier. The research aims to provide a detailed analysis of LULC changes between 2010 and 2020. The Random Forest classifier is chosen for its robustness and high accuracy in handling complex datasets. The classifier achieved a classification accuracy of 86.56% for the 2010 data and 88.42% for the 2020 data, demonstrating an improvement in classification performance over the decade. The results indicate significant LULC changes, highlighting areas of urban expansion, deforestation, and agricultural transformation. These findings highlight the importance of continuous monitoring and provide valuable insights for policymakers and environmental managers. The study demonstrates the effectiveness of using advanced machine-learning techniques for accurate LULC classification and change detection in remotely sensed data.

Machine learning and artificial intelligence are becoming a major influence in various research and commercial fields. This review attempts to explain machine learning techniques and applications in various fields. Challenges and future directions are also proposed, including data analysis suggestions, effective algorithms based on the situation, industrial implementation, organization’s risk tolerance, cost-benefit comparisons and the future of machine learning techniques. Applications discussed in this paper range from technological development and health care to financial issues and sports analytics.

Throughout history, humans have faced pandemics that impact the social and economic landscape and drive innovation to overcome the crisis. The COVID-19 pandemic has affected many individuals, impacted the global economy, changed social interaction, and created pressure to find a solution. This paper provides a comprehensive review that aims to help in achieving the goal of prediction, prevention, and monitoring of the global pandemic. Various data analysis methods that use available pandemic information to project future cases and deaths have been demonstrated. Similarly, spatial investigations that visually describe the transmission of the disease and indicate the similarities between infected regions have been shown. Additionally, specific environmental factors that affect the diffusion of the coronavirus have been described. Furthermore, prevention techniques and guidelines are discussed. Then, IoT's potential in monitoring the disease, helping patients, and contributing to healthcare is highlighted. Finally, the paper provides a concluding interpretation of the pandemic problem and makes recommendations.

Nanotechnology in modern material science is a research hot spot due to its ability to provide novel applications in the field of dentistry. Zinc Oxide Nanoparticles (ZnO NPs) are metal oxide nanoparticles that open new opportunities for biomedical applications that range from diagnosis to treatment. The domains of these nanoparticles are wide and diverse and include the effects brought about due to the anti-microbial, regenerative, and mechanical properties. The applications include enhancing the anti-bacterial properties of existing restorative materials, as an anti-sensitivity agent in toothpastes, as an anti-microbial and anti-fungal agent against pathogenic oral microflora, as a dental implant coating, to improve the anti-fungal effect of denture bases in rehabilitative dentistry, remineralizing cervical dentinal lesions, increasing the stability of local drug delivery agents and other applications.

An endophytic fungal strain isolated from the leaves of was identified as VJ1/VS1 based on nucleotide sequencing of internal transcribed spacer region (ITS 1-5.8S-ITS 2) of 18S rRNA gene (NCBI accession number KX213894). In this study, an efficient and ecofriendly approach has been reported for the synthesis of silver nanoparticles (AgNPs) using aqueous culture filtrate of . Ultraviolet-visible analysis confirmed the synthesis of AgNPs by showing characteristic absorption peak at 435 nm. Fourier transform infrared spectroscopy analysis revealed the presence of phenolic compounds and proteins in the fungal filtrate, which are plausibly involved in the biosynthesis and capping of AgNPs. Transmission electron microscopy (TEM) showed that the AgNPs were spherical in shape of 2-10 nm in size. Selected area electron diffraction and X-ray diffraction studies determined the crystalline nature of AgNPs with face-centered cubic (FCC) lattice phase. Dynamic light scattering analysis showed that the biosynthesized AgNPs possess high negative zeta potential value of -35.7 mV. Biosynthesized AgNPs were proved to be potential antioxidants by showing effective radical scavenging activity against 2,2'-diphenyl-1-picrylhydrazyl and H O radicals with IC values of 76.95±2.96 and 94.95±2.18 µg/mL, respectively. The biosynthesized AgNPs exhibited significant cytotoxic effects against B16F10 (mouse melanoma, IC =26.43±3.41 µg/mL), SKOV3 (human ovarian carcinoma, IC =16.24±2.48 µg/mL), A549 (human lung adenocarcinoma, IC =39.83±3.74 µg/mL), and PC3 (human prostate carcinoma, IC =27.71±2.89 µg/mL) cells. The biosynthesized AgNPs were found to be biocompatible toward normal cells (Chinese hamster ovary cell line, IC =438.53±4.2 µg/mL). Cytological observations on most susceptible SKOV3 cells revealed concentration-dependent apoptotic changes that include cell membrane blebbing, cell shrinkage, pyknotic nuclei, karyorrhexis followed by destructive fragmentation of nuclei. The results together in this study strongly provided a base for the development of potential and versatile biomedical applications of biosynthesized AgNPs in the near future.

Mineral Trioxide Aggregate (MTA) has been a material of revolution in the field of dentistry since its introduction in the 1990s. It is being extensively used for perforation repairs, apexification, root-end filling, obturation, tooth fracture repair, regenerative procedures, apexogenesis, pulpotomies, and as a pulp-capping material because of its desired features such as biocompatibility, bioactivity, hydrophilicity, sealing ability, and low solubility. Even though its application is wide, it has its own drawbacks that prevent it from reaching its full potential as a comprehensive replacement material, including a long setting time, discoloration, mud-like consistency, and poor handling characteristics. MTA is a material of research interest currently, and many ongoing studies are still in process. In this review, the newer advancements of this versatile material by modification of its physical, chemical, and biological properties, such as change in its setting time, addressing the discoloration issue, inclusion of antimicrobial property, improved strength, regenerative ability, and biocompatibility will be discussed. Hence, it is important to have knowledge of the traditional and newer advancements of MTA to fulfill the shortcomings associated with the material.