Volume 14 | Issue 2 |

 Abstract

In an environment characterized by heightened global volatility, uncertainty, and an increasing frequency of supply chain disruption events, the strategic design of agile and resilient supply chain operations has become imperative. This paper examines how the integration of AI-powered supply chain control towers with advanced digital twin simulations can form an intelligence-driven ecosystem for real-time and anticipatory decision-making. We develop a multi-layered theoretical framework that connects data ingestion, predictive and prescriptive analytics, visualization, and simulation-based planning through closed-loop feedback mechanisms grounded in Industry 4.0 and digital twin literature. Using a simulation-based experimental study, we demonstrate measurable improvements in demand forecasting accuracy, disruption detection and response times, resource efficiency, and sustainability-related outcomes. All performance metrics reported are derived from the authors' experimental simulations. Despite these benefits, adoption challenges remain, including data interoperability across heterogeneous platforms, algorithmic transparency, and cybersecurity risks. To address these gaps, the paper outlines a future research agenda focused on ethical AI design, real-time adaptive learning, and cross-industry standards to enable scalable deployment. Overall, the integration of AI control towers and digital twins represents a promising pathway toward more resilient, responsive, and increasingly autonomous supply chain networks.

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 Keywords

Supply Chain Resilience, Digital Twin, Control Tower, Predictive Analytics, Disruption Management, Real-Time Simulation, Industry 4.0, Intelligent Logistics

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Kamala Markandaya is an internationally recognized Indian English novelist whose writings vividly depict the condition of Indian women trapped within patriarchal structures. Her narratives highlight how these women, confined by oppressive social norms, are often silenced to the point that their resistance goes unnoticed. A close examination of her works shows her deep insight into the human mind; she studies human emotions with remarkable precision and penetrates even the most concealed layers of thought. She stands out among Indian English writers for her bold and unconventional advocacy of women's sexuality and bodily autonomy. Markandaya demonstrates a heightened awareness of gendered morality and the social systems that uphold it. She is one of the few Indian female writers who dared to portray the discrimination faced by women in a predominantly patriarchal society, while envisioning a world of equality and harmony between men and women. Her sensitive portrayal of women--married or single--who feel confined within relationships reveals her perceptiveness and emotional depth. Her novel Possession explores multiple facets of the human psyche, especially that of women. The reading of the novel feels like a therapeutic journey in which characters gradually reveal their inner selves, particularly Valmiki, the central figure around whom the other characters revolve. Their complex emotional exchanges enrich the narrative and take the reader on a psychological ride. This paper attempts to delve into the deeper layers of Possession, interpreting it through a psychoanalytic lens.

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 Keywords

Patriarchy, resistance, sexuality, entrapped, therapeutic.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Sudha Aroda Ki Kahaniya Me Stree Chetna

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Creative Commons Attribution 4.0 and The Open Definition

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Sudha Aroda Ki Kahaniya Me Stree Chetna

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Creative Commons Attribution 4.0 and The Open Definition

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Pravahika is a common gastrointestinal disorder described in Ayurvedic classics, characterized by frequent defecation associated with pain, tenesmus, mucus, and sometimes blood. In Balaroga (paediatric age group), Pravahika remains a significant health concern due to immature digestive fire (Mandagni), poor immunity, improper feeding practices, and recurrent infections. The disease closely resembles dysentery and inflammatory bowel conditions described in modern medicine. According to Ayurveda, Pravahika mainly occurs due to vitiation of Vata and Kapha Dosha, with involvement of Purishavaha Srotas and Pakwashaya, leading to repeated straining and passage of small quantities of stool. Children are more vulnerable due to their anatomical and physiological delicacy (Sukumarata), dependency on caregivers, and inability to maintain dietary discipline. Classical texts such as Caraka Sa?hita, Sushruta Sa?hita, and Kashyapa Sa?hita emphasize early diagnosis and gentle management using Deepana-Pachana drugs, Grahi dravyas, appropriate diet, and supportive therapies suitable for children. This review highlights the Ayurvedic concept of Pravahika in Balaroga, including its Nidana, Samprapti, Lakshana, differential diagnosis, and principles of management, along with correlation to modern paediatric dysentery. Understanding Ayurvedic fundamentals in childhood Pravahika can help in effective prevention, early intervention, and reduction of complications, thereby improving child health outcomes.

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 Keywords

Pravahika, Balaroga, Paediatric dysentery, Mandagni, Grahani, Vata-Kapha, Purishavaha Srotas, Ayurveda

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Creative Commons Attribution 4.0 and The Open Definition

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Abhiyan Hi Nayi , Rastriya Chetna Hai Adhyatmak

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Abhiyan Hi Nayi , Rastriya Chetna Hai Adhyatmak

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Creative Commons Attribution 4.0 and The Open Definition

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The aims to examine parents awareness, perception, and buying behaviour regarding organic baby care products. The study focuses on understanding the factors influencing purchase decisions, the level of awareness among parents, and the impact of demographic variables such as age, gender, education, and income on their purchasing patterns. The research is based on primary data collected from 100 respondents in Coimbatore City using a structured questionnaire. Statistical tools such as percentage analysis, Chi-square test, and One-Way ANOVA were employed to analyze the data. The findings reveal that the majority of respondents are young female parents below 25 years with diploma-level education and income below INR30,000. Although awareness about organic baby care products is high, the level of detailed knowledge remains moderate. Natural ingredients and environmental friendliness are the major factors influencing purchase decisions, while high price, limited availability, and lack of clear information act as significant barriers. The study also indicates that income significantly influences the type of organic baby care products purchased, and education plays a significant role in shaping parents' reasons for usage and their belief that organic products contain fewer harmful chemicals. The study concludes that while there is strong market potential for organic baby care products in Coimbatore City, improving affordability, accessibility, and product awareness is essential to enhance purchase behaviour and encourage long-term adoption among parents.

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 Keywords

Parents Satisfaction, Parents Experience, purchase behavior, product awareness and satisfaction level of parents.

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Creative Commons Attribution 4.0 and The Open Definition

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The agricultural productivity is highly dependent on the climate variability, soil conditions and the management of the resources. Application of conventional decision making has led to the wrong choice of crops, poor yield forecasting and high risk of financial losses among the farmers. To solve these dilemmas, the proposed paper introduces a smart Farm Decision Support System (FDSS) that has been modeled based on the machine learning algorithm, the random forest algorithm. The suggested model is a multi-dimensional analytics system that analyzes farm data such as the soil characteristics, rain distributions, temperature fluctuations, seasonal shifts, the use of fertilizers and past records of crop yield. The classification and regression tasks are performed with the help of the Random Forest algorithm to suggest appropriate crops, predict the performance of yield, predict the amount of fertilizer required, and recommend the profit potential. Because of an ensemble learning, Random Forest improves the predictive accuracy, reduces overfitting, and increases the robustness of the model in different environmental conditions. An easy-to-use dashboard system allows the farmer and the agricultural officers to enter the parameters of the fields and get real-time and data-driven recommendations. The effectiveness of experimentation proves the better accuracy of predictions and more reliable decisions, in comparison to traditional approaches. The proposed system helps in precision agriculture by ensuring that resources are utilized in the most efficient way, less risk is taken, and sustainable farming methods are ensured using artificial intelligence-based analytics.

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Precision Agriculture, Farm Decision Support System, Machine Learning, Random Forest Algorithm, Crop Recommendation, Yield Prediction, Fertilizer Optimization, Profit Estimation, Sustainable Agriculture, Data-Driven Farming

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Creative Commons Attribution 4.0 and The Open Definition

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Kamala Markandaya's Nectar in a Sieve occupies a central place in Indian English fiction for its profound depiction of destitution, famine, and the dislocation of rural communities. Told through the voice of Rukmani, a poor village woman, the novel reveals how entrenched social inequalities, environmental volatility, colonial-era economic pressures, and gendered responsibilities shape the fragile realities of survival. This study explores how the text represents poverty and hunger as more than economic hardships; they function as existential forces that shape identity, dignity, interpersonal bonds, and emotional endurance. By situating the story within the historical and socio-economic conditions of mid-twentieth-century India, the paper illustrates how Markandaya foregrounds the subtle, private anguish of ordinary individuals to expose the pervasive nature of systemic oppression. The analysis argues that the novel's lasting influence lies in its ability to humanize deprivation while simultaneously exposing its devastating effects, offering insights into resilience, moral ambiguity, and the quiet forms of resistance that hunger produces. Through literary interpretation, historical context, and critical engagement, this paper provides a detailed examination of how poverty and hunger operate both literally and symbolically in Nectar in a Sieve, highlighting the novel's enduring significance as a powerful commentary on social inequity.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

deprivation, resilience , moral ambiguity , resistance , social inequity.

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Creative Commons Attribution 4.0 and The Open Definition

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Bacteriocins are considered a blessing for the food industry. They act as a preservative to inhibit the growth of bacteria in the food items during the production or preservation process. These bacteriocins are produced by the bacteria, which reduces the growth of closely related bacterial strains. Food safety has become a serious issue in the present era for which bacteriocins, an antimicrobial compound, can effectively fight against food-pathogenic bacteria. Different views of the actions of bacteriocins have been elaborated. Bioengineered bacteriocins, or the hurdle approach to bacteriocins, can increase the efficacy of preservation and reduce the resistance effect against bacteriocins. They are mostly produced by LAB (Lactic acid bacteria), which is naturally present in most food. They can also be combined with antimicrobial proteins, agents, and natural phenolic compounds. The combined approach can act as a barrier to developing bacteriocin-resistant strains. It can also be combined with physical treatments like pulse electric fields and high-pressure processing by which foods can be more effectively preserved. This chapter summarizes and focuses on the importance and potential applications of bacteriocins as a food preservative in the food industry.

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Bacteriocins, Bio preservative, Lactic acid bacteria, Hurdle technology

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Creative Commons Attribution 4.0 and The Open Definition

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In recent years, social media platforms have emerged as critical sources of data, providing rich and diverse in formation about public opinions, behaviors, and emotions. Sentiment analysis and emotion detection in social media text have gained considerable attention, serving as essential tools for understanding user sentiments and emotional responses. This survey explores the advancements and methodologies employed in sentiment analysis and emotion detection, focusing on various techniques including rule based, machine learning, and deep learning approaches. It highlights the challenges in here not in analyzing informal and context-rich social media language, such as slang, emojis, and multi lingual content. Additionally, the survey discusses the role of pre-processing strategies, feature extraction methods, and the effectiveness of different models like LSTM, BERT, and Transformer based architectures in capturing complex emotional nuances. The paper also examines the applications of these techniques in diverse domains such as brand monitoring, crisis management, and mental health analysis. By providing a comprehensive overview of the existing literature and emerging trends, this survey aims to guide future research directions and improvements in sentiment analysis and emotion detection in the dynamic context of social media text.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

LSTM,CNN,NLP,SENTIMENT ANALYSIS

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Creative Commons Attribution 4.0 and The Open Definition