In today’s age of digital data interchange, safeguarding the security and privacy of visual information has emerged as a critical and immediate priority. This study introduces a novel approach to image encryption leveraging the combined strength of 2D Henon chaotic mapping and evolutionary algorithms, specifically Genetic Algorithms (GA). The proposed method aims to enhance the security of image data through a multi-step encryption process. Initially, the plain image is transformed into a cipher image using the 2D Henon chaotic map, which introduces a high level of randomness and complexity. Subsequently, an evolutionary algorithm, particularly the Genetic Algorithm, is employed to further optimize and strengthen the encryption by iteratively refining the cipher image. The evolutionary process enhances the scrambling of image pixels, ensuring robustness against attacks and increasing the encryption’s complexity. The synergy between the Henon chaotic map and Genetic Algorithm offers a potent encryption framework capable of securing image data efficiently while preserving its integrity during transmission and storage. Experimental evaluations and analyses showcase the effectiveness and resilience of the proposed encryption scheme against various cryptographic attacks, establishing its potential for secure image communication applications.

A field experiment was conducted during the season of 2021-22 at the Horticulture Research Farm of BBAU, Lucknow. The trial was carried out in a Randomized Block Design (RBD) and replicated thrice, aligned with sustainable agriculture principles, evaluated the effects of integrated nutrient management (INM) on the "Japanese White" radish across nine treatments: T1 (NPK at 80:60:80 kg/ha), T2 (vermicompost @ 4tons/ha), T3 (FYM @15 tons/ha), T4 (poultry manure @ 3 tons/ha), T5 (50% NPK + 50% vermicompost), T6 (50% NPK + 50% FYM), T7 (50% NPK + 50% poultry manure), T8 (50% vermicompost + 50% FYM) and T9 (50% vermicompost + 50% poultry manure); the results showed that treatment T5 outperforming others with a maximum fresh root weight of 119.08g, dry root weight of 21.09g, root length of 19.09cm, root diameter of 4.54cm and yield of 401.43q/ha, alongside superior nutritional quality viz., ascorbic acid (9.01mg/100g), total soluble solids (4.90°Brix), total sugars (5.07%) and reducing sugars (3.21%) demonstrating that a balanced 50% inorganic (NPK) and 50% organic (vermicompost) approach not only meets nutrient needs but also halves chemical fertilizers use, potentially lowering costs and enhancing sustainability in farming practices

Aims: The study aims to evaluate the effectiveness of biofertilizers on yield and quality attributes of Broccoli (Brassica oleracea var. italica L.). Background: The excessive and prolonged use of chemical fertilizers in broccoli cultivation has led to several negative consequences, including soil degradation, nutrient imbalance, reduced microbial diversity, and environmental pollution. These adverse effects ultimately hinder the sustainable enhancement of yield and crop quality. In contrast, biofertilizers offer an eco-friendly and efficient alternative, promoting soil health and enhancing plant growth through natural processes. By improving nutrient availability, stimulating root development, and supporting beneficial microbial activity, biofertilizers play a crucial role in boosting both yield and the quality of broccoli heads. Their use not only reduces dependency on harmful synthetic inputs but also contributes to long-term agricultural sustainability and food safety. Methodology: This study was conducted during 2022–2023 at the Horticulture Research Farm-1, Department of Horticulture, Babasaheb Bhimrao Ambedkar University, Lucknow (U.P.), India. The experiment included twelve treatments (T0–T11) to evaluate the impact of various biofertilizer combinations on broccoli yield and quality. T0 was the control (no fertilizer), while T1 received 100% RDF (Recommended dose of fertilizers). Treatments T2 to T4 involved sole applications of Azotobacter, Azospirillum and VAM (Vesicular arbuscular mycorrhiza), respectively. T5 to T7 combined RDF with each biofertilizer (50% each), and T8 to T10 tested biofertilizer pairings (50% each). T11 integrated RDF, Azotobacter, Azospirillum, and VAM at 25% each to assess synergistic effects. Findings: The treatment T7 (RDF + VAM at 50% each) recorded the highest performance across all yield and quality parameters of broccoli, including maximum curd weight (558.64 g), curd diameter (168.22 mm), curd volume (1196.36 cc), total yield (359.98 q/ha), and vitamin-C content (92.54 mg/100g). It also showed the highest dry matter content (31.16%) and titratable acidity (0.87%). T6 (RDF + Azospirillum at 50% each) was the next best treatment, showing significant improvements in yield and quality traits compared to other combinations. Conclusion and Recommendation: The study concluded that the combination of RDF and VAM at 50% each (T7) was most effective in enhancing broccoli yield and quality, followed by RDF + Azospirillum (T6). It is recommended to adopt the T7 treatment for sustainable production with reduced chemical input and improved crop performance.

Background: Internet use has evolved into an inseparable routine of human life, and it has revolutionized the world with its infinite possibilities. This study aims to assess the prevalence and pattern, associated factors and its consequences/side effects of Internet addiction among medical students in Patna, Bihar. Methods: This is a cross sectional study done among 400 students in tertiary care centre of Bihar. The 20-item Young Internet Addiction Test (IAT) was used to measure internet addiction. Results: Out of 400 participants, 38.3% were mild, 25% moderate and 3.5% were severely addicted to internet. Feeling bored was the triggering factor for increased use, apart from using this for academics, entertainment, and social media. Conclusions: Internet use can have an addictive potential and can become a behavioural disorder, if used for long which can ultimately interfere in our daily activities. Thus, assessing the problem at regular interval will give an insight to planning in future.

Aim: To investigate the effect of various planting dates and spacing on cabbage growth. Study Design: The experimental design Factorial Randomized Block Design (FRBD) was used. Place and Duration of Study: An experiment was conducted in the rabi seasons of 2021–22 and 2022–23 at the Horticulture Research Farm, Babasaheb Bhimrao Ambedkar University, Lucknow (U.P.) Methodology: There were twelve treatments with three replications. The variety selected for experiment was Pusa Mukta. Results: The combined data of two years showed that treatment P1 (30 November) had significantly higher plant survivability (95.28%), plant height (14.67 cm, 21.31 cm and 28.39 cm) at 30, 45 and 60 DAT, respectively, stem diameter (2.11 cm), no. of non-wrapper leaves (16.28), no. of wrapper leaves (27.19), plant spread E-W (49.40 cm) and plant spread N-S (52.63 cm). Among spacings. The findings showed that the S4 (60 cm x 60 cm) plant spacing achieved maximum plant survivability at 91.59%. It also led to the greatest plant height at 30, 45 and 60 days after transplanting (DAT) with measurements of 15.73 cm, 22.45 cm and 31.12 cm, respectively. Additionally, this spacing resulted in the largest stem diameter (2.31 cm), the highest no. of non-wrapper leaves (17.40), no. of wrapper leaves (28.30), greatest plant spread in both East-West (52.79 cm) and North-South (56.08 cm) directions. Conclusion: The results obtained from pooled data of two years showed that treatment P1 (30 November) and Spacing 60 cm x 60 cm had significantly higher growth parameters.

This paper explores the marketing channels of Bajra in Jaipur, Rajasthan, focusing on the distribution pathways, marketing costs, and margins associated with each channel. Utilizing an exploratory research design, the study conducted structured interviews and surveys with 120 Bajra growers across six villages in the Jobner Block. Three primary marketing channels were analyzed: direct sales from producers to consumers (Channel I), sales through wholesalers to consumers (Channel II), and sales involving wholesalers and retailers (Channel III). The findings indicate that Channel I, where producers sell directly to consumers, is the most efficient, characterized by the lowest price spread and the highest producer share in consumer spend (91.35%). This channel also exhibited the highest marketing efficiency (10.57), suggesting it minimizes costs while maximizing returns for producers. Channels II and III introduce additional costs and intermediaries, leading to higher price spreads and reduced producer shares. The study underscores the importance of streamlined marketing channels in enhancing the profitability and sustainability of agricultural practices in rural India.

Abstract: The increasing prevalence of chronic illnesses, including diabetes-related conditions and heart disease, poses a challenge to international healthcare systems. Reducing the detrimental effects of chronic disorders on patient outcomes requires early detection and treatment. This study investigates the possible uses of deep learning and predictive analysis in illness forecasting, with an emphasis on diabetes and heart disease specifically. Strict preparation methods were used, making use of a substantial dataset from the reference dataset source, to guarantee data quality. List-specific models and architectures were used for training and validation in order to assess how well different deep learning models performed in the prediction of sickness. The results show the potential of the suggested technique in the early diagnosis of sickness. They contain notable findings and promising performance metrics. By providing insight into the feasibility and efficacy of deep learning models for the prognosis of diabetes and heart-related illnesses, this work contributes to the expanding corpus of knowledge in healthcare analytics.

This paper presents optimal placement of thyrisor controlled series compensator (TCSC) to improve voltage profile and thus improve stability of the system. IEEE 30 bus test system is considered for case study. Newton-Raphson method is applied for load flow analysis. The optimal location of TCSC is chosen by using FVSI method. Load flow has been carried out with optimal placement of TCSC and both system parameters (with and without TCSC) are compared. The overall cost function has been minimized using genetic algorithm (GA) optimization technique. Minimization of total cost which includes the TCSC installation cost and voltage deviation cost is considered as the objective function. The power loss with TCSC is reduced from 5.16 MW to 5.08 MW. The simulation is carried out using MATLAB environment.

This case study explores the behavioural issues observed among Class VI-VIIII students in Jawahar Navodaya Vidyalaya (JNV) residential schools. Drawing upon observations from 12 JNVs across different regions in India, the study highlights the prevalence of homesickness, peer pressure, academic stress, social adjustment difficulties, and discipline problems among students. Through an analysis of underlying causes and potential solutions, the study provides insights into addressing these behavioural challenges effectively in the residential school setting. Keywords: Behavioural issues, Class VI-VIIII students, Jawahar Navodaya Vidyalaya, Residential schools, Homesickness, Peer pressure, Academic stress, Social adjustment, Discipline problems.

Broccoli (Brassica oleracea var. italica; 2n = 18), which is originated from the Mediterranean region commonly known as hari gobhi in Hindi and a member of cole group, belongs to the family Brassicaceae or crucifereae. The present research work on the effect of different biofertilizers on the growth parameters of broccoli was carried out at the Horticultural Research Farm-1, Department of Horticulture, Babasaheb Bhimrao Ambedkar University (A central University) Vidya Vihar, Raebareli Road, Lucknow-226025 (U.P.) during the rabi season, 2022-2023. The research material comprised twelve treatments and three replications in Randomized Block Design. The highest plant height (55.97 cm), number of leaves per plant (21.72), leaf length (48.27 cm), leaf width (23.51 cm), plant spreading east-west (46.63 cm), plant spreading north-south (46.32 cm), stem diameter (6.89 cm), stem length (26.53 cm) was observed at 90 DAT in T7 (RDF + VAM (50% + 50% Each) as compared to T0 (Control) treatment.

This paper verifies the optimum configuration and techno-economic viability of hybrid renewable energy systems (HRES) for electrifying the Andaman and Nicobar Islands. Plan to develop a better electric system that uses centralized renewable generations, such as solar panels, wind turbines, energy storage devices, and a diesel generator to ensure the reliability of power supply. Our electricity needs must be optimally satisfied by the chosen HRES. A test system is created with a few houses in the Andaman and Nicobar Islands to conduct a case study. Further, to increase the system’s reliability, we have probabilistically determined solar irradiance and wind speed using a machine learning technique, i.e., Random Forest. The suggested HRES satisfied the anticipated home load demand of 17.79 kWh/day and peak load of 1.490 Kw. For the energy dispatch of HRES, the optimal economical design of the system is determined based on the Cost of Electricity (COE) and renewable fraction using the proposed TFSO, PSO, AOA, GA, MFA and HOMOR Pro software. The optimal result of COE ₹ 4.21 at renewable fraction 89.04 is obtained using the Proposed TFSO algorithm. After the economic validation of the system using these algorithms, technical validation of the resulting outcome is done using Typhoon HIL real-time simulator, and the result is observed from DSO, where it is found that the voltage and frequency regulation is within its permissible limit.