Research News

The poor in India has continuous future benefits from globalization through improved healthcare – A new research from SRM University-AP economists
In a groundbreaking study, Dr. Manzoor H. Malik, an Assistant Professor in the Department of Economics, and Sodiq O. Bisiriyu, a Research Scholar, have developed a comprehensive framework known as the globalization-growth-poverty (GPP) triangular nexus.

This innovative model examines the interplay between globalisation waves, economic growth trends, and their collective impact on poverty reduction in India, aligning with the nation’s commitment to achieving Goal 1 of the Sustainable Development Goals.

The researchers used three different indicators of poverty, encompassing the monetary and non-monetary constructs. The research controls for the impact of government development spending and domestic investment in the GPP nexus. The result of the research validates the significant globalization-led growth hypothesis in the short run and establishes the existence of the GPP triangular nexus in India. Additionally, the researchers found positive association of globalization and growth with monetary and non-monetary poverty measures in the short-run while the impact on monetary measure in the long-run is ambiguous.

Finally, the results offer significant insight into the impact of government development spending and domestic investment on poverty. The results prove that government development expenditure in India is detrimental to non-monetary poverty while domestic investment have insignificant impact on all poverty constructs.

From policy perspective, the researcher said, “the short-run validation of globalization-led growth hypothesis for India is challenging and calls for government broad-based framework to tackle impediments of long-term globalization-led growth and monetary poverty benefits”. They emphasized that only sustained long-term growth can accelerate the vision of India as stated in “Viksit Bharat 2047” agenda. Published in the esteemed ‘Quality & Quantity’ journal by Springer, with an impact factor of 2.87, this study provides valuable insights for academics, practitioners, and policymakers. It sheds light on the complex dynamics shaping contemporary socio-economic environments and offers evidence-based analysis supported by an extensive review of relevant literature.

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In a significant development, Prof. Kamesh AVS, Professor at Paari School of Business, along with his PhD Scholar, Ms. Ashrafunnisa Mohammed, has successfully published and filed a groundbreaking patent titled “SYSTEM AND METHOD TO DETECT BOTTLENECKS AND ENHANCE EMPLOYEE PRODUCTIVITY” with the Application Number: 202441014093 A in the Patent Office Journal.

This pioneering system aims to revolutionise the way organisations detect and alleviate bottlenecks within their operations, consequently boosting overall employee productivity. The patent’s unique approach and methodology signify a remarkable stride towards fostering efficiency and performance in the workplace. Prof. Kamesh AVS and Ms. Ashrafunnisa Mohammed’s collaborative effort underscores their commitment to innovation and research excellence. Their accomplishment not only reflects their expertise in the field but also highlights the spirit of ingenuity and problem-solving that drives academia at Paari School of Business.

The SRM AP community extends its heartfelt congratulations to Prof. Kamesh AVS and Ms Ashrafunnisa Mohammed on this remarkable achievement and eagerly anticipates the positive impact their invention will have on the realm of employee productivity and operational efficiency.

Abstract of the Research
SYSTEM AND METHOD TO DETECT BOTTLENECKS AND ENHANCE EMPLOYEE PRODUCTIVITY
The present disclosure relates to a system for detecting bottlenecks and enhancing employee productivity. The system broadly includes an input module (106), a pre-processing module (108), a segmentation module (110), a feature selection module (112), a feature extraction module (114), a data training module (116), and a classification module (118). The system also consists of a data repository (102), a processor (104), and an evaluation module (120). The present disclosure aims to examine counterproductive work behaviors of employees through the effort-reward imbalance model by considering dark triad traits as moderators. The dark triad traits can indulge the employees more in unethical practices in organizations and one among those traits is Narcissism which negatively affects counterproductive work behaviors. Organizations can predict the Dark Triad traits in individuals, and they can avoid unethical practices in organizations and counterproductive work behaviors.

Explanation of the Research in Layperson’s Terms:

The present process aims to examine counterproductive work behaviors through the effort-reward imbalance model by taking into consideration Dark triad traits as moderators. The Dark Triad traits can indulge the employees more in unethical practices in organizations and one among those traits is Narcissism which negatively affects counterproductive work behaviors. Organizations can predict the Dark Triad traits in individuals, and they can avoid unethical practices in organizations and can avoid counterproductive work behaviors. There is a notable knowledge gap concerning the moderating role of Dark Triad traits in the relationship between efforts and rewards imbalance and counterproductive work behaviors, even though there is existing research on both the association between Dark Triad traits and counterproductive work behaviors and the relationship between efforts and rewards imbalance and counterproductive work behaviors.

Practical Implementation or Social Implications Associated with the Research:

• The Invention aims at identifying and eliminating the consequences of the Dark Triad Traits while performing Human Resources Practices like Recruitment, Training and Development, Performance Analysis, and Compensation and Reward Management system.
• The Invention either weakens or eliminates the Counter Productive work behaviors as a potential consequence of springing up of Dark Triad traits during the execution of various Human Resource practices in the organizations and this leads to achieving the estimated Organizational Productivity as per the strategy.
• Organizations can identify the impact of the Dark triad traits on employees and take steps to reduce the stress that leads to unproductive work behaviors.
• Organizations can eliminate the job stressors which are seen as the main sources of
• Counterproductive work behaviors can indicate the Dark triad traits’ influence on individuals.
• Management should investigate the causes of rudeness in the workplace to improve morale and productivity.
• During the hiring process, management should use a battery of psychological tests to gain insight into candidates’ personalities.
• Management can formulate standard policies to eliminate malicious activities and avoid effort-reward imbalances and counterproductive work behaviors.
• Understanding the causes of counterproductive workplace behavior is vital because it has become a widespread and expensive problem for businesses worldwide.

Future Research Plans
To Incorporate AI and ML tools to identify the Dark Triad traits, thereby enhancing the employee evaluation process and mitigating counterproductive work behaviors within organisations.

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In a remarkable stride for the field of wireless communication, Prof. Rupesh Kumar from the Department of Electronics and Communication Engineering has authored a pivotal book that promises to redefine our understanding of radar and RF systems. The book, entitled “Radar and RF Front End System Designs for Wireless Systems,” is the latest gem in the prestigious “Advances in Wireless Technologies and Telecommunication (AWTT)” series.

With his profound expertise, Prof. Kumar navigates through the complexities of designing state-of-the-art front-end systems, offering readers a treasure trove of knowledge that bridges theory and practical application. This book is set to become an essential read for aspiring engineers and seasoned professionals alike, enriching the academic and industry landscape with its innovative approach.
Join us in celebrating Prof. Kumar’s exceptional contribution to the world of electronics and communication engineering. Dive into the depths of this masterful work and emerge with insights that could shape the future of wireless systems.

About the Book:
Radar and RF Front End System Designs for Wireless Systems delves into the intricate world of wireless technologies, particularly focusing on radar and RF front-end systems. The advent of wireless communication has ushered in a new era of connectivity, revolutionising various sectors including healthcare, smart IoT systems, and sensing applications. In this context, the role of RF front-end systems, with their reconfigurable capabilities, has become increasingly vital. The impetus behind this book stems from the remarkable surge in innovation witnessed in RF front-end systems. Researchers and practitioners alike have contributed a plethora of new configurations and design architectures, paving the way for unprecedented advancements in wireless systems. Our aim with this publication is to provide a platform for researchers to explore both theoretical insights and practical applications, thereby facilitating the dissemination of the latest trends and developments in the field. The contents of this book cover a wide spectrum of topics, ranging from RF frontend antenna systems to the impact of artificial intelligence and machine learning in system design. With contributions from experts in academia and industry, readers can expect a comprehensive exploration of radar and antenna system design, modeling, and measurement techniques. We envision this book serving as a valuable resource for students, researchers, scientists, and industry professionals seeking to deepen their understanding of RF front-end antenna and radar system designs. Whether it’s exploring reconfigurable antenna systems for 5G/6G networks, or delving into radar modelling and signal processing techniques, this book offers insights that are both timely and relevant.

Co-author of the Book:

Shilpa Mehta, a co-author of the book, holds a PhD from Auckland University of Technology, New Zealand. Presently, she serves as a Teaching Assistant at AUT, Auckland. Shilpa received the Summer Doctoral Research Scholarship for her PhD work. Her research spans across projects such as Radio Frequency Integrated Circuits, RF front ends, Optimization, Internet of Things, Wireless Communication, Artificial Intelligence, Healthcare, Radars, Software-defined Radios, and Smart Cities.

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The Department of Computer Science and Engineering is proud to announce the acceptance of the book chapter titled, Dielectric Characterization of Ovine Heart Tissues at Terahertz Frequencies via Machine Learning: A Use Case for in-vivo Wireless Nano-Communication in the book, “Edge-Enabled 6G Networking: Foundations, Technologies, and Applications.” The book chapter by Dr Manjula R and her students, Ms NSK Sarayu, Ms N Sai Sruthi, Ms D Samaya, and Mr K Tarun Teja from the department caters to UG/PG and PhD students, educational institutions, and medical healthcare sectors. Dr Manjula’s research doesn’t just underscore the significance of understanding the dielectric properties of heart tissues but also highlights the transformative potential of machine learning in predicting, diagnosing and offering therapeutic interventions equipped with real-time monitoring capabilities. The research also lays the groundwork for future advancements in this field, facilitating the development of more efficient and reliable in-vivo sensing technologies.

Abstract of the Book Chapter:

A new generation of sensing, processing, and communicating devices at the size of a few cubic micrometers are made possible by nanotechnology. Such tiny devices will transform healthcare applications and open up new possibilities for in-body settings. A thorough understanding of the in-vivo channel characteristics is essential to achieve efficient communication between the nanonodes floating in the circulatory system (here, it is the heart) and the gateway devices fixed in the skin. This entails one to have accurate knowledge on the dielectric properties (permittivity and conductivity) of cardiac tissues in terahertz band (0.1 to 10 THz). This research examines the strength of the machine learning models in accurate calculation of the dielectric properties of the cardiac tissues. Initially, we generate the data using 3-pole Debye Model and then use machine learning models (Linear Regression, Polynomial Regression, Gradient Boosting, and KNN), on this data, to estimate the dielectric properties. We compare the values predicted by machine learning models with those given by the analytical model. Our investigation shows that the Gradient Boosting method has better prediction performance. Further, we have also validated these results using Origin software employing curve fitting technique. In addition, the research also contributes to the study of data expansion by predicting unknown data based on available experimental data, emphasizing the broader applicability of machine learning in biomedical research. The study’s conclusions enhance areas like non-invasive sensing in the context of 6G, which may improve data and monitoring in a networked healthcare environment.

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In a  research paper published in Economic and Political Weekly, Dr Vineeth Thomas, an Assistant Professor at the Department of Liberal Arts, delves into the socio-political and economic implications of the “Karnataka’s Mandate for Kannada on Signboards” amendment. The article highlights the social and cultural significance of the amendment and raises awareness about the potential economic challenges it may pose. This insightful paper not only makes for an engaging read but also serves as a valuable resource for policymakers and politicians, bringing attention to the practical and social implications of the amendment.

Abstract

The Kannada Language Comprehensive Development (Amendment) Bill, 2024, ratified by the Karnataka Legislative Assembly and Legislative Council, stands as a legislative landmark with profound implications. This commentary critically analyses the socio-economic-political implications, unravelling the intricate web of influences that the Kannada Language Comprehensive Development Bill introduces within the diverse and dynamic landscape of Karnataka.

Citation
Roshmi Antony, Vineeth Thomas, Lulubala Nayak (2024)-, Karnataka’s Mandate for Kannada on Signboards, Economic and Political Weekly, ISSN (Online) – 2349-8846 (SCOPUS /ABDC Indexed)

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“This is a remarkable opportunity for our students to enhance their fields of study, gain academic insights from expert scientists and participate in cutting-edge research projects at IGCAR. This will ensure that we at SRM AP nurture students with a great scientific temperament,” stated Prof. Manoj K Arora, Vice Chancellor of SRM University-AP on signing the MOU with IGCAR.

SRM University-AP has signed a Memorandum of Understanding (MOU) with the Indira Gandhi Centre for Atomic Research (IGCAR) at Kalpakkam, Tamil Nadu, to collaborate on academic and research projects in Biomedical Research, Disaster Management, and other domains. The MOU was signed by Dr B Venkatraman, Director-IGCAR and Prof. Manoj K Arora, Vice Chancellor, SRM University-AP in the presence of Dr Vidya Sundarrajan, Head PHRMD & QAD, IGCAR Kalpakkam, Mrs M Menaka, Head RAMS, RESD, SQRMG, IGCAR, Kalpakkam, Prof. Ranjit Thapa, Dean-Research, SRM AP and Dr K A Sunitha, Associate Professor, SRM AP.

The MoU underscores a mutually beneficial agreement between the two institutes. On the academic front, the MOU provides internship opportunities, research collaboration for projects and industry visits for the students and faculty of SRM AP. This ensures a knowledge transfer between the two organisations, promoting stellar growth in scientific and technological advancements.

SRM AP has already collaborated with IGCAR on a consultancy project in the pioneering field of Biomedical Research last year. The parties have successfully conducted health screening of over 1500 subjects in the Chengalpattu region in Tamil Nadu, with SRM Medical Hospital & Research Centre and AIIMS Mangalagiri as secondary collaborators. Upon the successful completion of the project, IGCAR and SRM University-AP further extend their association with an official MOU for academic and research collaborations. “The MOU with SRM University-AP for translational research will be a huge motivation for the young faculty and scholars to pursue breakthrough research in their scientific domains,” remarked Dr B Venkatraman, Director-IGCAR.

Both institutes plan to extend their collaborative health screening project to the state of Andhra Pradesh, focusing on the neighbouring villages of SRM AP. Dr K A Sunitha, Project Head from SRM University-AP, opines that this project aims not just the possibility of translational research but also research for the societal cause. This research enables us to understand the correlated factors that influence various health disorders. Prof. Ranjit Thapa, Dean-Research also stated his enthusiasm for the project and expanding their research ventures to other domains.

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In a significant advancement for sustainable energy technology, the Indian Patent Office Journal has officially granted a patent for the “Mini magnetically levitated wind turbine system for power generation.” This groundbreaking invention, bearing Application Number: 202241051560, is the brainchild of Dr Goutam Rana, Assistant Professor in the Department of Electronics and Communication Engineering.

Dr Rana, along with his dedicated team of B. Tech ECE students—Mr Vybagula Sai Vamsi, Mr Moparthi Teja, Mr Indrakanty Satwik, and Mr Pidikiti Venkata Abhinash have developed a system that promises to revolutionise how we harness wind energy. The turbine’s miniaturised and magnetically levitated design allows for efficient power generation with minimal mechanical friction, leading to a longer lifespan and reduced maintenance costs.
The team’s innovation aligns with global efforts to transition to renewable energy sources and showcases the potential of academic research in contributing to real-world challenges. The patent grant not only recognises the technical ingenuity of the invention but also underscores the collaborative spirit of the students and faculty at the institution.

Abstract:

Due to the increasing demand and supply gap, in the electrical energy system, wind energy is coming out as an alternative form of clean-with zero-carbon footprint renewable energy sources for power generation. The same is true for hydrocarbon-based fuels whose resources are limited and the contribution of vehicular pollution is also raising concerns in every-degrading the air quality index (AQI) of Indian cities. The electric and hybrid vehicles thus emerging fast as an alternative but often being hindered by the unavailability of proper charging infrastructures on roads.

The current invention is aimed to enable the use of wind turbines for harnessing wind energy and utilize the same to charge batteries of electrical vehicles or hybrid vehicles. The major challenges that have prevented the use so far are mainly two viz. low air flow and larger air drag. To address low airflow in normal road conditions in congested city alleys, we demonstrated the use of magnetically levitated Vertical-axis turbines instead of conventional ball-baring-based Horizontal-axis wind turbines. To reduce the air drag the use of vertical axis magnetically levitated wind turbines is a good option since the air drag experienced in the blade unit is not exactly in contact with the car body.

To improve on the drag further we have introduced an array of mini turbine units instead of one big unit which helps in distributing the total drag over a large area and since air can pass easily through small units overall drag experienced will be small. Also, to keep the levitation small, the rotating unit is made lighter with 3D printing perforated PLA material.
The rest of the operation of the system is similar to any wind turbine system i.e. with the help of permanent magnet and coil arrangement we will convert the wind energy (rotor movement) into electrical energy (e.m.f.). Only here instead of one single source, we will generate multiple small sources of induced electrical energy which can then be coupled together and used for charging the battery.

Since the invention uses magnetic levitation, friction is minimal. This helps the rotor to become independent of natural wind flow and use the movement of the vehicle to generate the required torque for the rotor movement. Our invention can be installed in the rooftop space of any vehicle and since it is divided into an array of smaller units, allows the optimum use of available space of the used vehicle. Overall cost and weight are also very minimal. Here, the most practical use case can be the widespread E-rickshaws in India. The choice of the use case is based on the fact of their large presence, longer run hours, and limited speed for the runs.

Explanation of the Invention in Layperson’s Terms:
The invention will act as a source of energy and can be used to charge batteries of electric vehicles or hybrid vehicles. The device converts wind energy to electrical energy through mini wind turbine arrays which can be placed on top of the rooftop of the vehicles. The rotor is kept suspended from the stator unit using magnets to eliminate friction. This helps to operate the device without the presence of strong natural wind, it utilizes the movement of the vehicle to generate the necessary rotation. The mini turbine arrays and magnetic suspension help to reduce the effect of wind drag (extra wind replaced by the turbine unit).

Practical Implementation or the Social Implications Associated
The invention is intended to solve a few on-road challenges of Electric Vehicles (EVs). The current invention is:
1. Low cost and one-time investment with zero maintenance charge for an EV
2. The proposed device can act as a secondary power source for the vehicle
3. The proposed device will convert wind energy, thus completely environment-friendly, and with comes with absolutely zero carbon footprint
4. The proposed device can add some extra mileage to the current battery storage as much as it runs.
5. With other renewable sources together a hybrid vehicle can be built which is free of fossil fuel completely.

Future Research Plans:

The current invention is in just proof of concept stage. We are currently working on the following
1. to improve the overall efficacy of the device such that each unit can harness wind energy to its optimal potential. With this, we will try to ensure that the battery gets charged completely (or at least a significant percentage) during each run during the day.
2. We are also working on the numerical study to calculate the actual wind drag with a more optimal design so that we can estimate how many units a certain vehicle will require and what should be the optimal placement scheme to utilize the maximum wind effect.

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In a significant academic achievement, Dr Anirban Ghosh, Assistant Professor from the Department of Electronics and Communication Engineering along with Mr Naga Srinivasarao Chilamkurthy, PhD Scholar, and Mr Shaik Abdul Hakeem, an undergraduate student, have made a remarkable contribution to the field of communication engineering. Their paper, titled “Optimal Routing Protocol in LPWAN Using SWC: A Novel Reinforcement Learning Framework,” has been published in the esteemed IEEE Sensors Journal, with an impressive impact factor of 4.3.

This publication marks a milestone for the university and highlights the innovative research being conducted by its faculty and students. The paper delves into the development of an optimal routing protocol for Low-Power Wide-Area Network (LPWAN) using State-Wise Communication (SWC), employing a novel reinforcement learning framework to enhance network efficiency and performance.
This work will pave the way for advancements in LPWAN technologies, which are crucial for the Internet of Things (IoT) ecosystem. The university community celebrates this achievement and looks forward to the positive impact it will have on technology and society.

Abstract:
Low Power Wide Area Network (LPWAN) has emerged as a dominating communication technology that offers low-power and wide coverage for the Internet of Things (IoT) applications. However, the direct data transmission approach has a limited network lifetime. Even multi-hop data transmission experiences several difficulties including high data latency, poor bandwidth utilization, and reduced data throughput. To overcome these challenges, in this paper, a recent breakthrough in social networks known as Small-World Characteristics (SWC) is incorporated into LPWANs.

In particular, in this work, Small-World LPWANs (SW-LPWANs) are developed by using the Reinforcement Learning (RL) technique and using different node centrality measures like degree, betweenness, and closeness centrality. Further, the performance of the developed SW-LPWANs is evaluated in terms of energy efficiency (alive/dead devices, and network residual energy) and Quality-of-Service (average data latency, data throughput, and bandwidth utilization), and is compared with that of conventional multi-hop LPWAN. Finally, to validate the simulation results, similar analyses are performed on the real-field LPWAN testbed.

The obtained simulation results confirm that SW-LPWAN developed by the RL method performs better than other techniques, with 11% more alive devices, 5.5% higher residual energy, 2.4% improved data throughput, and 14% efficient bandwidth utilization compared to the next best method. A similar trend is observed with real-field LPWAN testbed data also.

Explanation of the Research in Layperson’s Terms

Social networks primarily revolve around establishing human connections, whereas LPWANs are designed for connecting IoT devices that have limited battery-driven power. In this context, the smart devices must communicate in an IoT setting to conserve the limited energy available to them. To achieve this, the concept at the core of social networking also known as small world characteristic is incorporated into LPWAN using the Q-learning technique.

Practical Implementation or the Social Implications of the Research

IoT applications such as remote healthcare, smart environmental monitoring, asset tracking, and smart traffic systems require low transmission delay and high network lifetime. The proposed research helps in achieving the above parameters.

Collaborations
Dr Om Jee Pandey, Assistant professor Department of Electronics Engineering, Indian Institute of Technology, (BHU), Varanasi. e-mail: omjee.ece@iitbhu.ac.in

Dr Linga Reddy Cenkeramaddi, Professor, Department of Information and Communication Technology, University of Agder, Norway. e-mail:linga.cenkeramaddi@uia.no

Future Research Plan
In the next phase of research, we will be interested in investigating how the energy efficiency and other quality of service of smart devices in an IoT setting can be improved if they are partially or completely mobile.

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The Department of Computer Science and Engineering is proud to announce that the patent titled “A System and a Method for Assisting Visually Impaired Individuals” has been published by Dr Subhankar Ghatak and Dr Aurobindo Behera, Asst Professors, along with UG students, Mr Samah Maaheen Sayyad, Mr Chinneboena Venkat Tharun, and Ms Rishitha Chowdary Gunnam. Their patent introduces a smart solution to help visually impaired people navigate busy streets more safely. The research team uses cloud technology to turn this visual information into helpful vocal instructions that the users can hear through their mobile phones. These instructions describe things like traffic signals, crosswalks, and obstacles, making it easier for them to move around independently, making way for an inclusive society.

Abstract

This patent proposes a novel solution to ease navigation for visually impaired individuals. It integrates cloud technology, computer vision algorithms, and Deep Learning Algorithms to convert real-time visual data into vocal cues delivered through a mobile app. The system employs wearable cameras to capture visual information, processes it on the cloud, and delivers relevant auditory prompts to aid navigation, enhancing spatial awareness and safety for visually impaired users.

Practical implementation/Social implications of the research

The practical implementation of the research involves several key components.

• Developing or optimising wearable camera devices that are comfortable and subtle for visually impaired individuals. These cameras should be capable of capturing high-quality real-time visual data.
• A robust cloud infrastructure is required to process this data quickly and efficiently using advanced computer vision algorithms and deep learning algorithms.
• Design and develop a user-friendly mobile application that delivers processed visual information as vocal cues in real-time. This application should be intuitive, customisable, and accessible to visually impaired users.

The social implications of implementing this research are significant. We can greatly enhance their independence and quality of life by providing visually impaired individuals with a reliable and efficient navigation aid. Navigating city environments can be challenging and hazardous for the visually impaired, leading to increased dependency and reduced mobility. The research aims to mitigate these challenges by empowering users to navigate confidently and autonomously. This fosters a more inclusive society where individuals with visual impairments can participate actively in urban mobility, employment, and social activities.

In the future, the research cohort plans to further enhance and refine technology to better serve the needs of visually impaired individuals. This includes improving the accuracy and reliability of object recognition and scene understanding algorithms to provide more detailed and contextually relevant vocal cues. Additionally, they aim to explore novel sensor technologies and integration methods to expand the capabilities of our system, such as incorporating haptic feedback for enhanced spatial awareness. Furthermore, we intend to conduct extensive user testing and feedback sessions to iteratively improve the usability and effectiveness of our solution. This user-centric approach will ensure that our technology meets the diverse needs and preferences of visually impaired users in various real-world scenarios.

Moreover, the team is committed to collaborating with stakeholders, including advocacy groups, healthcare professionals, and technology companies, to promote the adoption and dissemination of this technology on a larger scale. By fostering partnerships and engaging with the community, they can maximise the positive impact of their research on the lives of visually impaired individuals worldwide.

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In a significant stride towards understanding cholesterol homeostasis, Dr Koyel Chakravarty, Assistant Professor and Mr Sukdeb Manna, a PhD Scholar in the Department of Mathematics has co-authored a paper titled “Unlocking Cholesterol Homeostasis: A Mathematical Modelling Perspective.” The paper has been published in the esteemed journal, The European Physical Journal Plus, with an impact factor of 3.4. This collaborative effort showcases the innovative application of mathematical modelling in unravelling the complexities of cholesterol regulation within the body.

The research not only contributes to the existing body of knowledge in this field but also sheds light on potential avenues for further exploration and understanding. Dr Chakravarty and Mr. Manna’s work underscores the importance of interdisciplinary approaches in scientific research and highlights SRM University-AP’s commitment to fostering cutting-edge research and innovation.

Their collaborative efforts serve as an inspiration to aspiring researchers and underscore the university’s dedication to pushing the boundaries of knowledge and discovery. Congratulations to Dr Chakravarty and Mr Manna on this remarkable achievement, and we look forward to more groundbreaking contributions from them in the future.

Abstract:
Limited progress in the mathematical modelling of cholesterol transport systems is hampering novel therapeutic interventions. This issue is addressed by the present study through precise design, employing four compartmental models to elucidate cholesterol dynamics in the comprehensive bloodstream. Disparities in medical advancements, particularly in cholesterol-related pathophysiology, are aimed to be bridged, advancing medical science and patient care outcomes.

Therapeutic strategies for reducing blood cholesterol are explored by the model, with parameter influences on equilibrium stability revealed through sensitivity analysis. System parameters are effectively manipulated by imposing sensitivity analysis, and pinpointing areas for model refinement. Stability analysis contributes to diverse realistic models, confirming local asymptotic stability. Model efficacy in studying cholesterol transport dynamics is supported by analytical and numerical assessments. The study concludes with the present model validation to substantiate it by comparing the present outcomes with the existing ones.

Explanation of The Research in Layperson’s Terms:

Basically, scientists are having trouble figuring out how to model how cholesterol moves around in the body, which is important for developing new treatments. This study tries to solve that problem by creating detailed models that show how cholesterol behaves in different parts of the bloodstream. The goal is to bridge the gap in medical knowledge about cholesterol-related problems and improve how we treat patients. The models help us understand how different treatments might affect cholesterol levels, and by analyzing them closely, we can figure out which factors are most important. This lets us tweak the models to make them more accurate. The study shows that the models are reliable by testing them both analytically and numerically, and comparing the results to what we already know.

Practical Implementation or the Social Implications of the Research

1. Personalized Medicine: The mathematical models developed in this research could help in designing personalized treatment plans for individuals with high cholesterol levels. By understanding how different factors affect cholesterol dynamics, doctors can tailor therapies to each patient’s specific needs, leading to more effective and targeted treatments.
2. Drug Development: Pharmaceutical companies could use these models to screen potential drugs for lowering cholesterol. By simulating how different compounds interact with cholesterol transport systems, researchers can identify promising candidates for further testing, potentially speeding up the drug development process.
3. Healthcare Cost Reduction: Better understanding of cholesterol dynamics could lead to more efficient use of healthcare resources. By optimizing treatment strategies and preventing complications related to high cholesterol, healthcare costs associated with conditions like heart disease could be reduced, benefiting both individuals and society.
4. Public Health Initiatives: Insights from the research could inform public health initiatives aimed at reducing cholesterol-related diseases. For example, policymakers could use the models to design targeted interventions such as education campaigns promoting healthy lifestyle choices or policies to improve access to cholesterol-lowering medications.
5. Improved Patient Outcomes: Ultimately, the goal of this research is to improve patient outcomes by better understanding and managing cholesterol homeostasis. By developing more accurate models of cholesterol transport dynamics, healthcare providers can make more informed decisions, leading to better control of cholesterol levels and reduced risk of cardiovascular disease and other related conditions.

Future Research Plans:

1. Current models may focus on a limited set of factors influencing cholesterol transport. Future research could explore the integration of additional biological factors such as genetic variations, hormonal influences, and dietary components into the models to create a more comprehensive understanding of cholesterol homeostasis.
2. Most existing models of cholesterol transport assume static conditions. Future research could develop dynamic models that capture the time-dependent changes in cholesterol levels in response to various stimuli, such as meals, physical activity, and medication intake. Dynamic models would provide a more accurate representation of real-world cholesterol dynamics and enable the evaluation of time-sensitive interventions.

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