AI and augmented reality for 3D Indian dance pose reconstruction cultural revival.

This paper delves into the specialized domain of human action recognition, focusing on the Identification of Indian classical dance poses, specifically Bharatanatyam. Within the dance context, a "Karana" embodies a synchronized and harmonious movement encompassing body, hands, and feet, as defined by the Natyashastra. The essence of Karana lies in the amalgamation of nritta hasta (hand movements), sthaana (body postures), and chaari (leg movements). Although numerous, Natyashastra codifies 108 karanas, showcased in the intricate stone carvings adorning the Nataraj temples of Chidambaram, where Lord Shiva's association with these movements is depicted. Automating pose identification in Bharatanatyam poses challenges due to the vast array of variations, encompassing hand and body postures, mudras (hand gestures), facial expressions, and head gestures. To simplify this intricate task, this research employs image processing and automation techniques. The proposed methodology comprises four stages: acquisition and pre-processing of images involving skeletonization and Data Augmentation techniques, feature extraction from images, classification of dance poses using a deep learning network-based convolution neural network model (InceptionResNetV2), and visualization of 3D models through mesh creation from point clouds. The use of advanced technologies, such as the MediaPipe library for body key point detection and deep learning networks, streamlines the identification process. Data augmentation, a pivotal step, expands small datasets, enhancing the model's accuracy. The convolution neural network model showcased its effectiveness in accurately recognizing intricate dance movements, paving the way for streamlined analysis and interpretation. This innovative approach not only simplifies the identification of Bharatanatyam poses but also sets a precedent for enhancing accessibility and efficiency for practitioners and researchers in the Indian classical dance.

Chitosan-cellulose hydrogel conjugated with L-histidine and zinc oxide nanoparticles for sustained drug delivery: Kinetics and in-vitro biological studies.

Functionalised nanohybrid hydrogel using L-Histidine (HIS) conjugated chitosan, phyto-synthesised zinc oxide nanoparticles (ZNPs) and dialdehyde cellulose (DAC) was formulated as a sustained drug delivery carrier for the polyphenol drugs - Naringenin (NRG), Quercetin (QE) and Curcumin (CUR). A maximum loading efficiency of 90.55 %, 92.84 % and 89.89 %, respectively were optimised for NRG, QE and CUR in the hybrid hydrogel. The maximum drug release was favoured for the optimum drug loading and at pH-5. HIS-chitosan conjugation stabilised the hydrogel and enabled a sustained drug delivery. Drug release kinetics predicted a non-Fickian diffusion-based mechanism along with polymer erosion. Prominent antimicrobial activity against Staphylococcus aureus and Trichophyton rubrum strains were predicted to evolve based on the synergic formulation. Significant biocompatibility towards L929 cells revealed their support for normal cell survival. Anticancer studies towards A431 cells exhibited excellent cytotoxicity with a 15 to 30-fold increase using the hybrid carrier, compared to the free polyphenol drugs.

Synergic formulation of onion peel quercetin loaded chitosan-cellulose hydrogel with green zinc oxide nanoparticles towards controlled release, biocompatibility, antimicrobial and anticancer activity.

The therapeutic prospective of a novel carrier based delivery of phyto-derived quercetin (QE) extracted from onion peel waste was studied in the present work. Dialdehyde cellulose (DAC) developed from sugarcane bagasse (SCB) cellulose effectively crosslinked chitosan hydrogel. The hydrogel matrices were embedded with green zinc oxide nanoparticles (ZnO NPs), phyto-synthesized using musk melon seeds. The hybrid carrier formulation was characterised using analytical techniques such as XRD, FTIR and SEM analysis. The onion peel drug (OPD) analysed for its bioactive components using HPLC was reported as a potential source of QE. Taguchi optimization for the QE drug loading in the nanohybrid hydrogel indicated a remarkable improvement by 39% in comparison to drug loading in hydrogel without ZnO NPs. The maximum QE release was obtained at an optimal drug loading condition with pH 5.0, which favoured the anticancer applications. The drug release revealed a Fickian diffusion mechanism by adopting various kinetic models. The commercial QE and QE in OPD (QE/OPD) loaded nanohybrid hydrogels were found to inhibit the growth of Staphylococcus aureus and Trichophyton rubrum strains. The biocompatibility and anticancer properties of the QE/OPD loaded nanohybrid hydrogels were established against normal L929 murine fibroblast cells and A431 human skin carcinoma cell lines respectively.

Highly biocompatible chitosan with super paramagnetic calcium ferrite (CaFe2O4) nanoparticle for the release of ampicillin.

The CaFe2O4 nanoparticles (CFNP) were synthesized using the solution combustion method. The CFNP-chitosan-ampicillin was prepared by the ionic gelation method using tripolyphosphate (TPP). The CFNP, chitosan-CFNP, chitosan-CFNP-ampicillin materials were characterized by XRD, FT-IR and TGA analysis in order to evaluate the particle nature and size, the presence of functional groups and their thermal stability. The FESEM and EDAX analysis were performed to understand the surface morphology of the materials and the presence of CFNP in the material, respectively. The vibrating sample magnetometer (VSM) analysis was performed to analyze the magnetic property of the chitosan-CFNP material. The squareness value of 0.1733 obtained by VSM measurements indicates the super paramagnetic nature of chitosan-CFNP. Taguchi orthogonal array method was applied to identify the significant impacting parameters for maximizing the drug encapsulation of chitosan-CFNP. The drug release studies showed that the drug was released rapidly in acidic medium as compared to the basic or neutral medium. The drug release kinetic data were fitted with different linear kinetic model equations and the best fit was obtained with Korsmeyer-Peppas model. The model drug ampicillin release from chitosan-CFNP was tested against staphylococcus epidermis bacteria through disc diffusion method for checking biocompatibility and antibacterial activity.