Volume 11 | Issue 11 |

 Abstract

Polycystic ovary syndrome (PCOS) is a common endocrine disorder affecting 6-15% of women worldwide. Its etiology involves insulin resistance, hyperandrogenism, obesity, hormonal imbalances, genetic factors, environmental exposures, stress, and ovarian follicular defects. PCOS significantly impacts women's quality of life and mental well-being. Management strategies should address these multifactorial aspects, including lifestyle interventions for obesity and hormonal balance. A better understanding of PCOS complexities can improve reproductive and metabolic outcomes for affected women.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Hyperandrogenism, Follicular Defects, Endocrine, Multifactorial, Insulin resistance, obesity.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Key Words: Ecocriticism, , Deep ecology , Environmental issues, etc

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Floods are among the most devastating natural disasters, causing extensive damage to both human lives and infrastructure worldwide. Timely and accurate flood prediction is crucial for mitigating the impacts of these events and enhancing community resilience. This abstract presents an overview of the current state of flood prediction, highlighting the growing importance of advanced forecasting models and data-driven approaches in improving prediction accuracy. Traditional flood prediction methods often rely on historical data and basic hydrological models, which may not adequately capture the complexities of modern climate patterns and urbanization. In recent years, advancements in technology, remote sensing, and computational power have revolutionized flood prediction by enabling the development of sophisticated predictive models. Integrating diverse datasets such as rainfall, river discharge, topography, land use, and weather forecasts to create a comprehensive understanding of the hydrological system. Leveraging machine learning and AI algorithms to process and analyze vast amounts of data, enabling the detection of patterns and trends that were previously challenging to identify. Utilizing satellite and remote sensing technologies to monitor environmental changes and provide real-time information on flood-prone areas.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Flood Prediction, Machine Learning,Pytorch,Deep Learning

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Accurate forecasting of electrical appliance usage and peak demand is crucial for effective planning, maintenance, and the development of automation in electrical power systems. Discrepancies between actual appliance consumption and energy demand may arise from various factors, such as losses in lines and appliances, as well as mismanagement of energy demand. A groundbreaking approach for forecasting household electric appliance consumption and peak demand through a hybrid machine learning (ML) framework is presented here. To address these variations, a thorough examination of smart meter data is essential to pinpoint the key attributes and primary causes of differences between electrical appliance consumption and customers' peak demand. Understanding these intricacies is vital for optimizing power system operations and implementing strategies to enhance efficiency and reliability. The study employs a comprehensive dataset spanning multiple households, ensuring the generalizability of the proposed methodology. Results demonstrate superior predictive capabilities compared to traditional models, offering significant advancements in energy demand forecasting precision. This hybrid approach not only captures nuanced relationships within the data but also adapts dynamically to changing environmental and behavioral factors. As the energy landscape evolves, our innovative methodology stands poised to revolutionize how we understand and anticipate household electricity consumption, providing valuable insights for policymakers, utility providers, and consumers alike.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Machine learning, Data filtering, Electrical appliance consumption, Peak demand, Smart meters

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Osteoporosis is a chronic skeletal disease that is characterised by reduced bone mineral density (BMD) with an increased risk of fractures. Its occurrence is being observed increasingly in post-menopausal women and the elderly population. Primary prevention is the best way to combat this problem. Medical intervention in the form of allopathic remedies and in severe cases, surgery is required and is the traditional approach. Pharmacological treatment includes antiresorptive and bone anabolic drugs that may help restore mass and quality. However, these techniques are accompanied by an array of undesired side effects due to less researched long-term issues and patient incompatibility in many scenarios. Mainstream medical practice is centralised around healing through allopathic medicine and has not yet fully acknowledged nutrient strategies to enhance skeletal health. For a holistic approach to the treatment of this rampant disorder, a balance between lifestyle, nutritional, and dietary factors is essential. This article discusses the effects of the intake of adequate amounts of nutrients in a prophylactic as well as therapeutic role. The significance of calcium, phosphorus, proteins, fatty acids, magnesium, vitamin D, and vitamin K is reviewed. Incorporation of these nutrients in daily diet is imperative to curb this medical pandemic along with amendments in lifestyle.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Skeletal disease, Proteins, Fatty acids, Magnesium, Vitamin D, Vitamin K

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The article focuses on the government policies and initiatives that have played a vital role in shaping India's network infrastructure over the years. It mainly concentrates on the funding mechanisms, considering their feature and the impact on the development of roads and networks in India.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

BOT Models, Financial Structure, NHAI, PPP.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Breast milk is the perfect food for normal neonate. It is the best gift a mother can give her baby. It contains all the nutrients for normal growth and development of a baby from the time of birth to first six months of life. Proper proportion and in a form that is easily digested and absorbed .Infants need to be given only exclusive breast feeding for the first six months of life."If the winter comes can the spring be for behind."Great poet says that the spring is followed by winter. That reveals that the joy after suffering. But labour does not come to end with child birth. The mothers do suffer much difficulty after childbirth. The design adopted for the study was quasi experimental pre- test and post -test control group design to assess the effectiveness of breast massage on reduction of breast engorgement among mothers undergone caesarian section. Purposive sampling was used to select 60 mothers in selected hospitals among that 30 samples were allotted for experimental group, 30 samples for control group. The data collection tools developed for generating the necessary data were standard scale was used to assess breast engorgement among mothers undergone caesarian sectionThe reliability of rating scale (r=0.9) was established by test retest technique method. The tool was found to be reliable. Pilot study was conducted to find out the feasibility of the study and to plan for data analysis. There was no significant difference between mean pretest level of breast engorgement among mothers undergone caesarian section in experimental and control group (t=0.86, p<0.05). There was a significant difference between mean post test level of breast engorgement among mothers undergone caesarian section in experimental and control group(t=4.88, p<0.05). There was a significant difference between mean pre and post test level of breast engorgement among mothers undergone caesarian section in experimental group(t=5.76, p<0.05). There was a no significant difference between mean pre and post test level of breast engorgement among mothers undergone caesarian section in control group(t=0.05, p<0.05). There was no significant association between post-test level of breast engorgement and experimental group demographic variables in age, education, occupation, postnatal day, feeding started, duration and frequency of feeding among mothers undergone caesarian section at ( p<0.05) level. There was a significant association between post-test level of breast engorgement and experimental group demographic variables in gravida, among mothers undergone caesarian section at (p<0.05) level. There was no significant association of post-test level of breast engorgement and control group demographic variables in age, education, occupation, postnatal day, feeding started, duration and frequency of feeding among mothers undergone caesarian section at ( p<0.05) level. There was a significant association between post-test level of breast engorgement and control group demographic variables gravida, among mothers undergone caesarian section at (p<0.05) level. Conclusion: The results of the study concluded that breast massage was effective on reduction of breast engorgement among mothers undergone cesarean section Breast massage is easy to practice, not painful and can enhance comfort to mother in the postnatal period, hence could easily be adopted as a regular intervention.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Breast Engorgement, Mother

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Background: HIV and TB pose significant public health threats, but their combined impact has a much greater effect on epidemiological progression and the global health landscape. Having HIV is the primary factor that raises the risk of developing active TB. This not only makes individuals more prone to initial infection or reinfection but also increases the likelihood of TB reactivation in those with latent TB.This observational study was conducted with the objective to identify the prevalence and prescribing patterns of TB among PLHIV in a tertiary care teaching hospital. Methods: A prospective observational was conducted in 250 HIV patients on ART who attended an ART clinic over a 6-month period . Result: This study showed 250/100 (40%) prevalence of tuberculosis among people living with HIV, of which 68(68%) were males and 32(32%) were females. Low CD4 count (< 200/?l) had A strong statistical connection is observed between co-infection of HIV and TB compared to just having HIV infection.The treatment of HIV/TB Co-infection majority of the population received CAT 1 medications , for patients who were resistant to CAT 1 medications , Bedaquilline was recommended as CAT 2 medication. Conclusion: The increasing HIV prevalence is connected to more tuberculosis cases, demanding a reevaluation of control strategies. Integrated programs targeting behavior change and condom use can lower HIV transmission and vulnerability. Success hinges on public awareness and effective health education on tuberculosis and HIV spread.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

CD4+ cells, HIV, Tuberculosis, ART,ATT.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

It can be challenging to secure the cyber physical systems (CPS) that underpin the Internet of Things (IoT) since security measures taken into account for general information and technology operations (IT/OT) might not function well in a CPS environment. In this paper, we suggested an automatic cyber attack detection and classification framework based on machine learning. For the purpose of ensuring the safety of Internet of Things use cases, it employs a variety of machine learning models. Learning Based - Cyber Attack Detection(LB-CAD) is the approach we suggested. The input of the algorithm consists of an ML pipeline and an IoT integrated use case dataset.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

ML-Based Cyber Attack Identification in CP Networks

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

^^Hkkjrh; laxhr esa dk"kh ds eafnjksa dh Hkwfedk^^

  License

Creative Commons Attribution 4.0 and The Open Definition