Volume 13 | Issue 1

 Abstract

This paper introduces TO-DO ASSIST (Todify), a desktop application designed for task management that integrates a user's to-do list with artificial intelligence. Todify offers a unified platform for organizing personal tasks, utilizing AI for task delegation, and facilitating collaborative efforts to enhance task efficiency. Leveraging to-do list and instant messaging metaphors, the application allows users to initiate, manage, and modify complex tasks executed by agents. The interaction between the user and AI is streamlined through simple operations on to-do items and direct-manipulation chat. The goal is to establish seamless interactions that result in workload reduction, decreased cognitive load, and improved task performance. Unlike other task management applications, Todify not only assists with task organization but also provides creative suggestions for task completion, fostering user creativity. Importantly, the AI suggestions aim to enhance creativity without promoting laziness.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

API, Open AI, TODO

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Nirgundi Taila, a classical Ayurvedic preparation mentioned in the Yogaratnakara, is known for its efficacy in healing Dusta Vrana (non-healing ulcers). To enhance patient compliance with its topical application, the formulation was modified into a Malahara. This study aimed to evaluate the primary analytical properties and antimicrobial effects of the modified Nirgundi Malahara, ensuring its safety and efficacy in promoting ulcer healing. Analytical evaluations confirmed compliance with standard parameters, with pH at 3.88, low total ash content (0.03), absence of acid-insoluble ash, and minimal loss on drying (0.03). In vitro antimicrobial assays revealed that the Malahara exhibited significant activity against Escherichia coli (NCIM 2065) with inhibition zones of 15 mm and 13 mm at 80% and 50% concentrations, respectively, and against Staphylococcus aureus (NCIM 2127) with an inhibition zone of 11 mm at 80% concentration. These findings suggest that the modified Malahara may retain the therapeutic potential of the original Taila and offer a more effective and convenient formulation for managing Dusta Vrana .

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Malahara, Nirgundi Malahara, Analytical study, antimicrobial study

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study investigates the scepticism of feminist movements in the Digital Age of social media where people, brands, influencers etc. are advocating for feminism, inclusivity and body positivity while endorsing products for their respective businesses that contradict the same ideology. This research explores the paradox in upholding the feminist ideology while justifying the marketing language of monetisation through set beauty standards for the sake of consumerism through thematic analysis of secondary data.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Social Media, Feminism, Capitalism, Paradox, Hypocrisy, Female Body, Monetisation.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Although significant progress has been made in the pursuit of gender equality, women around the world still face persistent challenges that hinder their full participation in society. These challenges, ranging from economic inequality and cultural constraints to systemic violence, are present across different regions and cultures, albeit in varying forms. Women continue to experience a gender pay gap, underrepresentation in leadership positions, and a disproportionate share of unpaid domestic and caregiving work. Moreover, cultural practices such as child marriage and gender-based violence further exacerbate their struggles. Intersectionality adds another layer of complexity, as women from marginalized groups face compounded discrimination. Despite these barriers, efforts through global movements, policy changes, and educational initiatives offer pathways for progress. This article explores the ongoing predicaments faced by women today, emphasizing the need for comprehensive approaches that address systemic, cultural, and institutional inequalities, and calls for sustained efforts to empower women for a more inclusive and equitable future.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Gender equality, economic inequality, gender pay gap, leadership representation, unpaid care work, gender-based violence, cultural constraints, child marriage, intersectionality, systemic discrimination, women empowerment, global movements, policy reforms, education, social inequality, women's rights, gender stereotypes, societal barriers, empowerment initiatives, gender parity, cultural practices.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Drug discovery is undergoing a transformative shift, driven by the integration of innovative approaches that bridge the gap between scientific research, advanced technologies, and therapeutic development. Modern drug discovery faces significant challenges, including the complexity of disease mechanisms, drug resistance, and the need for more personalized therapies. This abstract explores the latest innovations shaping the field, focusing on cutting-edge strategies such as artificial intelligence (AI), machine learning (ML), and high-throughput screening, which are revolutionizing target identification, compound screening, and drug optimization. Additionally, the application of advanced technologies like CRISPR gene editing, organ-on-a-chip models, and systems biology is providing deeper insights into disease biology, enabling more precise drug development. The rise of biologics, including monoclonal antibodies and gene therapies, is also playing a pivotal role in targeting previously "undruggable" diseases. Furthermore, the increasing emphasis on precision medicine is guiding the development of more tailored therapeutic solutions based on genetic, environmental, and lifestyle factors. However, challenges related to drug safety, efficacy, and regulatory hurdles remain. As the pharmaceutical industry continues to embrace multidisciplinary collaboration, these innovations promise to significantly accelerate drug discovery timelines and lead to more effective and personalized treatments.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Drug discovery, innovative approaches, artificial intelligence, machine learning, high-throughput screening, CRISPR, organ-on-a-chip, biologics.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Biopesticides are eco-friendly alternatives to chemical pesticides, but their potential toxicological impacts on non-target aquatic organisms remain a concern. This study aimed to evaluate the toxic effects of Newtech biopesticides on the liver of Danio aequipinnatus (Ham Buch), a freshwater fish species widely distributed in the region of Navapur taluka of Nandurbar District. Specimens were exposed to varying concentrations of the biopesticide over 21 days, followed by histological examination of the liver tissues. The results showed significant dose-dependent alterations, including vacuolation, hepatocyte necrosis, and congestion of blood sinusoids. These findings suggest that although Newtech biopesticides are designed to minimize environmental damage, they may pose risks to aquatic organisms at higher concentrations as well as prolonged exposure. This study highlights the need for further research to assess the ecological safety and potential sublethal effects of biopesticides on aquatic ecosystems.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Toxicology, effect New tech, Liver Danio aequipinnatus.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The authors present a new deep learning architecture designed specifically for Deepfake image detection using CNNs. Their methodology is based on the concept of training a CNN model with a carefully compiled dataset consisting of genuine and fake images, which the authors have extracted very carefully from the Kaggle competition and datasets website. Following the training phase, the model undergoes a critical transfer learning phase, leveraging the powerful representations encoded within the Xception architecture, pre-trained on the vast and diverse ImageNet dataset. The crux of this approach lies in the model's ability to discern intricate patterns and nuanced features that distinguish authentic imagery from its synthetic counterparts. Through the systematic study of underlying structures and pixellevel subtleties, the CNN architecture learns to deconstruct subtle disparities present in Deepfake images and hence, strengthen its predictability. Preliminary results from the experimentation phase show the validity of the proposed CNN-based approach in the task of detecting and reporting the counterfeit image with an appreciable accuracy level. In all fairness, strides have been taken so far. However, this is still something that the entire research community strives to further polish and improve performance metrics of the model. As the iterations continue and the improvements are made, the goal remains to reach unprecedented levels of precision and robustness in Deepfake detection, making our defenses much stronger against falsified multimedia proliferation in the digital space.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Deepfake, Facial Forgery, Fake Media Synthetic media, AI-generated material, pattern recognition image classification, computer vision, data augmentation, overfitting, underfitting, model training, and evaluation.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Counterfeit detection in art and antiques is a persistent issue that undermines the value of cultural heritage and economic markets globally. Traditional methods of art authentication, while effective, rely heavily on expert evaluations, which can be time-consuming, costly, and prone to human error. This research aims to develop an innovative solution using Artificial Intelligence (AI) to automate and enhance the process of counterfeit detection. The proposed system integrates advanced machine learning techniques, such as Convolution Neural Networks (CNNs) for image-based analysis, which can detect subtle inconsistencies in brushstrokes, patterns, and textures, which are typically difficult for the human eye to discern. In addition to visual analysis, hyper spectral imaging (HSI) will be utilized to examine the materials and hidden layers of artworks, identifying anachronistic pigments, modern binders, or mismatched materials, further improving the accuracy of detection. Provenance validation, an integral aspect of art authentication, will be achieved using blockchain technology to ensure secure, immutable records of an artwork's history. By merging these AI approaches, the system offers a comprehensive solution that is both scalable and cost-effective for art galleries, auction houses, and collectors. This research has the potential to significantly reduce the occurrence of fraud in the art market, improve transparency, and preserve the integrity of cultural artifacts for future generations.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Counterfeit Detection, Art Authentication, Machine Learning, Convolution Neural Networks, Hyper spectral Imaging, Forgery Detection

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In an increasingly digital world, the threat of phishing attacks through malicious URLs poses a significant risk to users and organizations alike. This project aims to develop an AI-powered detection system that utilizes machine learning algorithms to evaluate and assess the maliciousness of URLs. The system features a robust REST API and a user?friendly web application, allowing users to input URLs and receive AI-generated probabilities regarding their safety in real time. Additionally, a feedback mechanism is integrated into the application, enabling users to confirm or correct assessed probabilities, thus enhancing the accuracy and reliability of the URL analysis. This continuous feedback loop not only improves the machine-learning model's performance over time but also fosters user engagement and cybersecurity awareness. The backend architecture is designed to be scalable, accommodating increased user load and facilitating integration with existing cybersecurity solutions. Ultimately, this project contributes to a safer online environment by empowering users with the tools and knowledge needed to recognize and avoid phishing threats.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

AI-Enhanced Phishing Defense, Malicious URL Detection,

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The project focuses on the development of an advanced system for the real-time detection of bacterial blight disease in pomegranate leaves using machine learning techniques. Utilizing Convolutional Neural Networks (CNNs) for image analysis, the system processes high-resolution images captured by mobile devices to identify specific visual indicators of bacterial blight. The integration of this technology enables farmers to receive immediate feedback regarding the health of their crops, facilitating timely intervention and management practices. The ultimate goal is to enhance agricultural productivity, reduce crop losses, and promote sustainable farming practices through early detection and accurate diagnosis optionally intelligent contact center environment.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Bacterial Blight, Disease Detection, Machine Learning, CNN, Agricultural Technology

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The increasing adoption of cloud computing across various organizations and the IT sector has transformed how data is stored and accessed, offering a cost-effective and efficient solution for managing information. With the rapid shift towards cloud-based services, users can enjoy enhanced data accessibility through the Internet, enabling real -time collaboration and resource sharing. However, this is widespread reliance on cloud technology raises significant is concerns regarding data security and privacy, particularly when sensitive information is entrusted to cloud storage providers, some of which may be perceived as untrustworthy. The primary challenge lies in securely sharing and storing data while ensuring that it is remains protected from potential breaches or unauthorized access in entrusted cloud environments. As organizations migrate to the cloud, the need for robust encryption and decryption techniques becomes paramount. This paper proposes a comprehensive approach to safeguarding sensitive client information by employing a combination of well-established encryption algorithms, specifically Advanced Encryption Standard (AES), Data Encryption Standard (DES), and SHA-256.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Cloud, Encryption/Decryption Technique, AES, DES and SHA-256.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The project implements real-time emotion surveillance for contact center agents through machine learning. Convolutional Neural Networks (CNNs) are utilized for facial expression recognition, while Recurrent Neural Networks (RNNs) handle voice emotion analysis. By processing audio-visual data, emotions are detected in real-time, delivering immediate feedback to supervisors and agents. The system aims to enhance customer interactions with consistent and positive experiences, improve agent performance with personalized stress management and training, and optimize operational efficiency by guiding workflow and resource allocation. The approach fosters a productive and emotionally intelligent contact center environment.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Emotion Detection; Voice Tone Analysis, CNN, RNN.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Empowerment of women is essentially the process of upliftment of economic, social and political status of women, the traditionally underprivileged ones, in the society. Women empowerment involves the building up of a society, a sociocultural and political environment, wherein women can breathe without the fear of oppression, exploitation, apprehension, discrimination and the general feeling of persecution which goes with being a woman in a traditionally male dominated structure. This paper explores the multidimensional challenges faced in empowering women in India. Despite legal frameworks and policies promoting gender equality, sociocultural norms and systematic barriers persist. The study also highlights issues such as education, economic participation, political representation and social changes for policy makers to address these challenges.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Women Empowerment, Gender Equality, Socioeconomic Barriers, Policy Implementation, Awareness

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In today's fast-paced world, people often find themselves overwhelmed with work commitments and busy schedules, leading to a disconnect from their personal and family life. When unexpected issues arise at home, such as plumbing failures or appliance breakdowns, they add to the stress, forcing individuals to juggle between their professional and personal responsibilities. In these situations, the ability to quickly resolve home maintenance problems is crucial for maintaining a balanced life. Envisioning a hassle-free environment where homes remain in optimal condition without the need for constant repairs, and services are readily available without negotiation or delay, is a common desire. This paper proposes a solution in the form of an online service platform that brings essential home maintenance services directly to the customer's doorstep. Through an easy-to-use mobile application, users can access a variety of services, including plumbing, electrical work, cleaning, repairs, and more. The proposed system offers a seamless platform where customers can conveniently book trusted and skilled service providers, ensuring high-quality service delivery with minimal effort. By integrating a user-friendly interface and a reliable system, the application aims to revolutionize the way people manage home services, providing a simple and efficient solution for everyday needs. The goal is to streamline the process of booking home services and make it more accessible, ensuring that users can focus on their professional and personal lives without worrying about home maintenance tasks.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Home service, on-demand services, mobile application, service provider, GPS, real-time availability, secure payments, user feedback.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

ABSTRACT Dendrimers are a new class of polymeric materials. A dendrimer described as a macromolecule characterized by its highly branched 3D structure which provides a high degree of surface functionality and versatility. Drugs are delivered through nanotubes in therapy, and specifically in the treatment of cancerous tumors. Dendrimers' unique characteristics such as hyper branching, well-defined spherical structure, and high compatibility with the biological systems are responsible for their wide range of applications including medical and biomedical areas. This review briefly discusses the various aspects of dendrimers including introduction, needs of dendrimer, advantages, disadvantages, properties, component of a dendrimers, structure, different methods of synthesis of dendrimers, characterization and dendrimers based products and their use as pharmaceutical, therapeutic, diagnostic agent and their potential for applications in drug delivery such as carrier molecule, toxicity, current challenges, future prospect, conclusion. The review aims to emphasize on construction, characterization, drug delivery and possible application of dendrimers in various areas of research, technology and treatment.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

KEY WORDS: Polymeric material, 3D structure, Hyper branched, High compatibility, Characterization, emphasize on construction.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Text-to-image generators represent a significant advancement in artificial intelligence, particularly in the realm of multimodal models that seamlessly combine natural language processing and computer vision. Systems like OpenAI's DALLoE and Google's Imagen utilize state-of-the-art transformers and diffusion models to generate highly detailed and contextually relevant images from textual prompts. By training on extensive datasets containing millions of image-text pairs, these models learn intricate relationships between linguistic inputs and visual concepts. This paper explores the mechanisms and applications of text-to-image generation, focusing on the ability of these systems to translate descriptive prompts into coherent and stylistically diverse visuals. The research highlights their potential in fields such as scientific visualization, virtual reality, gaming, and digital marketing, while also addressing ethical concerns, including misuse for creating deepfakes and biases introduced by imbalanced training datasets. Despite these challenges, text-to-image generation is poised to redefine digital content creation, offering unprecedented ease and creativity in producing sophisticated multimedia outputs from multi-language input sources.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Image generation, Text-to-image generation, Sketch-to-image generation, Layout-to-image generation, Image-to-image translation, Panoramic image generation, Artificial Intelligence, Text-to-Image Generation, Neural Networks, Transformer Architectures, Diffusion Models, DALLoE, Google Image, Visual Imagery, Creative Workflows, Digital Marketing, Game Design, Virtual Reality, AI Ethics, Intellectual Property, Bias in AI, AI Creativity, Dataset Limitations, Image Quality, Contextual Accuracy,

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Child malnutrition condition can be considered as a major health issue for a country since the children are the unborn pool which directly affects the profitable growth of the country. Proper nutrition is an essential element for the survival, growth, and development of children in society. Malnutrition is a global problem in moment's life. The primary target of this miracle is children under five times of age and substantially for developing countries. In this system, a data wisdom approach is proposed to prognosticate the malnutrition status of children under five times of age grounded on the training data-sets. Training data- sets downloaded from www.kaagle.com. Some retired factors were uprooted with the use of data mining ways. Bracket ways used for malnutrition status vaticination. We use algorithm "Bayesian classifier" for vaticination. The results shown on GUI. By testing and validating the knowledge, preventative conduct can be taken with the help of medical experts to reduce the malnutrition condition among children for applicable countries. We make this as real time operation useful for the society. To make real time operation we use technologies similar as "Visual Studio" as frontal end technology and "SQL Server" as end technology. Both the tools are important tools to work with real time operation. This system defines how data wisdom bracket ways can classify malnutrition status for children under five times of age. Generally, our system will attain the most robust results to prognosticate the malnutrition status grounded on clinical data- sets.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Tradescantia pallida -- the spiderwort, a perennial herb native to eastern Mexico Gulf coast, at present farmed as an ornamental commonly known as purple heart or purple queen. Because of its pendulous nature, it is commonly grown in green house or outdoors as groundcover or in containers. The plant is part of the genus Tradescantia in the Commelinaceae family, which comprises approximately 80 herbaceous species endemic to Neotropics. Although T. pallida is recognized in the Food Technology and Environmental area for its uses of identifying, binding and elimination work for soil; air contaminants. The research was also done on bioactive compounds, such as epigallocatechin and hydroxytyrosol that have anticancer, anti-inflammatory activity and antidiabetic & antioxidative. Most notably these phytochemicals, and others from Tradescantia give some of the numerous potential uses for this plant, which may be evidence that its bioactive components are synergistic. For millennia, herbs have been a valued food, flavoring and healing plants these days they are widely used in the form of powders or capsules, teas and extracts. The Tradescantia genus is particularly famous for its traditional medicinal properties against different diseases, traditionally anti-inflammatory and antioxidant- antibacterial, antiarrhythmic. Traditionally, Its roots have been brewed in drinks to cure some digestive and kidney disorders, while the leaves were traditionally used in the treatment of bug bites or stings. Individual species such as T. zebrina are used in Traditional Chinese Medicine for the treatment of chloasma, and throughout Jamaica; T. pallida has been taken for the treatment of tuberculosis, coughs and hypertension. One of the decoctions of its leaves, is used to prepare the beverage "Matali" in Mexico. Usually these plants are herbaceous, 30-60 cm tall with perennial or annual fibrous- to tuberous-rooted stems that give rise dense mats. Flowers are bisexual, actinomorpic or slight zygomorphic and has its own unique inflorescence. Those traditional uses of Tradescantia species may be widespread and clear, but further scientific work is needed to substantiate the cause-effect relationship underlying the supposed medicinal benefits

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Tradescantia pallida, Bioactive compounds, Phytochemicals , Medicinal properties, Environmental applications, Traditional uses.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Knowledge and Perception of Nursing Students on Respectful Maternity Care: A Study in Bhopal This study evaluated nursing students' knowledge and perception of Respectful Maternity Care (RMC) at a nursing college in Bhopal. Utilizing a quantitative approach, data was collected from 40 students through a structured questionnaire. Results indicated that 57% had adequate knowledge, 38% moderate, and 5% inadequate. Significant associations were found between knowledge levels with gender and education, revealing male students and those in General Nursing and Midwifery courses had lower knowledge compared to female students and those in Bachelor of Science in Nursing programs. The study emphasizes the necessity for training programs in RMC to enhance maternal care practices and underscores the importance of respect and dignity in healthcare settings. Future research should focus on larger samples and interventions to improve RMC knowledge among healthcare professionals.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Respectful Maternity Care, Nursing Students, Knowledge Assessment, Demographic Variables, Healthcare Education, Maternal Health.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Anaemia is the commonest haematological disorder that may occur in pregnancy. Iron deficiency is the most prevalent single deficiency state on a worldwide basis. It is important economically because it diminishes the capability of individuals who are affected to perform physical labour, and it diminishes both growth and learning in children . Iron is an important micronutrient which is Very Important for various functions in the human body. It is essential for cellular growth and differentiation, oxygen binding, transport and storage, enzymatic reactions, immune function, cognitive function, mental and physical growth etc. So, iron deficiency due to physiological or pathological reasons can affect mental and physical growth, resulting in decreased learning capacity and work productivity. Iron Deficiency Anemia is characterized by a defect in haemoglobin synthesis, resulting in hypochromic and microcytic red blood cells. Iron deficiency can result either due to less nutritional supply, increased demand or blood loss due to any reason. There are many reasons for iron deficiency and Iron Deficiency Anemia in adolescent girls. These may be deficient intake or absorption of iron, increased demand during adolescence, heavy blood loss during menstruation, parasitic infestation etc. More than half of the world's undernourished population lives in India. Although Iron Deficiency Anemia occurs at all ages and involves both sexes, adolescent girls are more prone to it. The World Health Organization (WHO) defined adolescents as the population of 10-19 years of age. About three fourth of adolescent females do not meet the dietary requirements. Majority of the adolescents think that they are in good health and show little concern for protecting their health. The main nutritional problems of adolescents are micronutrient deficiencies like iron deficiency, folate and vit.A. According to a study by WHO on anaemia during 1993-2005, the worldwide prevalence of anaemia was 25%. According to WHO guidelines for the control of IDA, nutritional anaemia is a major public health problem in India and is primarily due to iron deficiency. The National Family Health Survey-3 (NFHS-5,19-2021) data suggests that the prevalence of anaemia in adolescent girls (15-19 years) is 59.1%. According to the National Nutrition Monitoring Bureau Survey (NNMBS) 2006, the prevalence of anaemia in adolescent girls (12-14 years) is 68.6% whereas in (15-17 years) it is 69.7%. Aim of the study was to assess the effectiveness of Structured Teaching Programme On Knowledge Regarding Management Of Iron Deficiency Anaemia Among adolescent girls .

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Anemia, Girls

  License

Creative Commons Attribution 4.0 and The Open Definition