Devi Ahilya University (informally abbreviated DAVV), formerly Indore University, is a State University whose jurisdiction was initially restricted to Indore city. Later on, its jurisdiction was extended to seven tribal-dominated districts of Indore division namely, Jhabua, Alirajpur, Dhar, Khargone, Khandwa, Burhanpur and Barwani. It is thus catering to the educational needs of the most industrially developed district of Madhya Pradesh, Indore on one hand and to the seven tribal and rural backward districts of the State on the other. DAVV is the only University in Madhya Pradesh accredited A+ Grade by NAAC.
Seed treatments, crucial for safeguarding seeds and optimizing crop yield, have witnessed a shift towards environmentally friendly alternatives to chemical treatments. Plasma and magnetic fields have emerged as promising technologies in agriculture, offering a sustainable approach to enhancing crop development. Exposure to magnetic fields and plasma induces positive effects on plant growth, influencing gene expression and ultimately boosting crop productivity. These technologies induce changes at the molecular level, impacting epigenetic, transcriptomic, proteomic, and metabolic processes. These changes manifest in enhanced germination rates, improved early seedling development, optimized phytohormone levels, and enhanced activity of metabolic and defense enzymes. This review delves into the application of plasma and magnetic fields in agriculture, highlighting their potential to enhance cereal production. Recent research demonstrates that processing diverse cereals like wheat, rice, barley, and maize using these technologies leads to significant improvements in plant growth, yield, and stress resilience. The development of more effective and scalable plasma and magnetic field systems, crop-specific treatment parameter optimization, and precision agriculture application exploration will be the main areas of future study.
Wound healing is a multifactorial biological process that requires the coordinated regulation of inflammation, cell migration, angiogenesis, growth, and extracellular matrix remodeling. These drawbacks of existing wound care treatments prompt the need to seek safe and cost-effective agents and multi-target agents. This was demonstrated in a study that investigated the wound-healing capacity of a natural flavonoid glycoside, rutin, using an integrated in vitro-in silico methodology. An MTT assay was used to determine the cytocompatibility of rutin in L929 fibroblast cells, and the results showed that cell viability was high at a wide range of concentrations. A scratch wound healing assay showed enhanced fibroblast migration and wound closure in a concentration-dependent manner, and wound contraction was nearly complete within 72 h at optimum concentrations. To understand the molecular mechanisms underlying these effects, network pharmacological analysis revealed 94 common targets between rutin-associated wound healing and rutin-associated genes. Protein-protein interaction analysis identified key regulatory nodes, such as PIK3R1, PRKCA, and EGFR, which are central to the pathways that regulate cell proliferation, migration, angiogenesis, and inflammatory regulation. Enrichment analysis of gene ontology and KEGG pathways revealed that the PI3K-Akt, MAPK, VEGF, and AGE-RAGE signaling pathways were highly involved. Molecular docking showed good binding affinities of rutin to PIK3R1, PRKCA, and EGFR, which was also confirmed by 100 ns molecular dynamics simulations that revealed complex stability and favorable conformational behavior. Density functional theory analysis showed that the electronic characteristics were in line with the antioxidant activity and the strong intermolecular interactions. Together, these results demonstrate that rutin is a promising multifunctional topical wound-healing agent and provide mechanistic evidence for its use in topical therapeutic applications.
The terahertz (THz) spectrum enables ultra-high data rate communication for defense, biomedical, and space applications. This paper presents a graphene-based dual-port tunable MIMO antenna designed for efficient THz operation. Each port comprises three patches with a 50 Omega offset feed on polyimide (& varepsilon;(r) = 3.5) and alumina (& varepsilon;(r) = 9.4) substrates, forming a stepped resonator structure. The proposed antenna achieves a wide 5.5-10 THz bandwidth, 12 dBi peak gain, and < -20 dB isolation, with reduced mutual coupling via circular patch-edge cuts. To enhance and predict antenna performance, machine learning regression models-Linear Regression, Gaussian Process Regression (GPR), and Support Vector Regression (SVR)-are implemented using MATLAB to estimate the reflection coefficient (S-11) from design parameters. The GPR and SVR model exhibits the lowest mean square error and the highest correlation with simulated results, enabling data-driven parameter optimization and rapid performance prediction. Comprehensive performance metrics including Channel Capacity Loss (CCL), Total Active Reflection Coefficient (TARC), Mean Effective Gain (MEG), and Envelope Correlation Coefficient (ECC) confirm the antenna's suitability for THz MIMO applications with excellent diversity performance. The integration of EM simulation and machine learning thus offers a powerful framework for adaptive, high-efficiency THz antenna design.
The emergence of quantum computing poses a transformative challenge to established cybersecurity protocols and traditional cryptographic systems, necessitating an urgent transition toward post-quantum cryptography. As quantum threats evolve from theoretical possibilities to practical risks, governments and industrial sectors are increasingly compelled to develop strategies for adopting quantum-resistant algorithms. This paper evaluates the global landscape of post-quantum security, with a specialized focus on the defense strategies adopted by technologically advanced nations. It investigates the efforts of these countries to construct quantum-resilient security architectures while addressing the distinct technical and resource constraints faced by developing nations. A primary contribution of this research is the analysis of the Industry Readiness Assessment Survey, which evaluates organizational awareness and technical preparedness within the specific context of India’s digital and regulatory environment. The findings highlight the critical importance of mitigating "harvest now, decrypt later" threats through international cooperation and the development of sovereign transition plans. By synthesizing empirical survey data with strategic policy analysis, this paper provides a roadmap for securing national interests and ensuring long-term data integrity against future quantum computational capabilities
Zero moment point (ZMP) is a key biomechanical indicator of dynamic gait stability, conventionally measured using force plates or pressure insoles that are costly and impractical for continuous wearable use. This work presents a low-cost wearable framework for ZMP estimation using only thigh-shank inertial measurement units (IMUs) and knee joint kinematics. A custom flex sensor-based insole was used solely to compute reference ZMP during training and evaluation. Data were collected from healthy subjects walking on flat and inclined treadmills. A bidirectional long short-term memory-artificial neural network model trained on synchronized IMU and knee angle data achieved subjectwise fivefold cross-validation RMSEs of 0.56 cm (mediolateral) and 0.09 cm (anterior-posterior), with corresponding R(2 )values of 0.82 and 0.90. Leave-one-subject-out evaluation demonstrated subject-independent generalization with a modest increase in error due to intersubject variability. Real-time deployment on an NVIDIA Jetson Nano achieved an average inference time of 9.2 ms with a quantized model size of 1.8 MB, enabling on-device ZMP estimation in controlled gait settings.
