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SRM University-AP Founder Chancellor Dr T R Paarivendhar and Pro-Chancellor Dr P Sathyanarayanan met with the Honourable Chief Minister of Andhra Pradesh, Shri Nara Chandrababu Naidu, to extend their congratulations on his fourth tenure as the head of the state government. Upon assuming the office as the Chief Minister after his landslide victory, Shri Chandrababu Naidu generously welcomed the institution leaders with the assurance and support for the university’s development and the provision of necessary facilities.

Founder Chancellor Dr T R Paarivendhar remarked, “Shri Chandrababu Naidu is a visionary leader with an ambitious dream to revitalise the governance, economy, and businesses in the capital city of Amaravati. As the first educational institute to plant roots in Amaravati soil, we confidently look forward to the cordial support in developing SRM University-AP into a world-class university.”

Pro-Chancellor of SRM University-AP, Dr P Sathyanarayanan, congratulated the veteran leader on his political triumph and conveyed his best for his successful tenure. He said, “With Shri Chandrababu Naidu, an exemplary commander at the apex of the state, Andhra Pradesh is set to transcend the frontiers of socio-economic development. SRM University-AP as an academic university will flourish with the development of Andhra Pradesh.”

SRM University-AP was established in the year 2017 when Shri Chandrababu Naidu was presiding as the Chief Minister of the State. Currently housing the School of Engineering and Sciences, Easwari School of Liberal Arts and Paari School of Business, the university has a visionary plan to extend its campus to include a law school, medical school and other emerging schools and programmes. Shri Chandrababu Naidu-led state support will propel the progress of the varsity, helping to provide quality education, employment and academic capital to the ground roots of Andhra Pradesh.

In a significant contribution to the intersection of technology and healthcare, Dr V M Manikandan, Assistant Professor in the Department of Computer Science and Engineering along with a team of dedicated undergraduate students, has co-authored a pivotal book chapter. The chapter, titled “Advancements and Challenges of Using Natural Language Processing in the Healthcare Sector,” has been published in the insightful book “Digital Transformation in Healthcare 5.0.”

The collaborative effort by Dr Manikandan, Mr Shasank Kamineni, Ms Meghana Tummala, Ms Sai Yasheswini Kandimalla, and Mr Tejodbhav Koduru delves into the innovative applications and potential hurdles of implementing natural language processing (NLP) technologies in healthcare. Their work highlights the transformative power of NLP in analysing vast amounts of unstructured clinical data, thereby enhancing patient care and medical research.
This academic achievement showcases the expertise and commitment of the faculty and students and underscores the institution’s role in driving forward the digital revolution in healthcare. The chapter is expected to serve as a valuable resource for researchers, practitioners, and policymakers interested in developing smarter, more efficient healthcare systems.

Introduction of the Book Chapter

“Digital Transformation in Healthcare 5.0: IoT, AI, and Digital Twin” delves into how advanced technologies like IoT, AI, and digital twins are reshaping healthcare. It provides a comprehensive look at the integration challenges and technological advancements aiming to modernise medical practices. The chapter “Advancements and Challenges of Using Natural Language Processing in the Healthcare Sector” specifically explores how NLP processes vast data in healthcare to transform it into actionable insights, enhancing efficiency and patient care while highlighting the implementation challenges of these technologies. This book is crucial for healthcare and technology professionals interested in the future of digitally enhanced healthcare.

Significance of the Book Chapter

The chapter “Advancements and Challenges of Using Natural Language Processing in the Healthcare Sector” is significant because it encapsulates my interest and expertise in harnessing NLP to enhance healthcare operations. It showcases the potential of technology in transforming healthcare data into valuable, actionable insights, directly aligning with my focus on improving patient outcomes through technological innovation.

Link to the Book Chapter

In a remarkable achievement, Dr Maheshwar Dwivedy, Associate Professor in the Department of Mechanical Engineering, has made a significant contribution to the field of materials science with his latest publication. The paper, entitled “Understanding heterogeneity and anisotropy of duplex stainless steel elastic/plastic nature through property mapping technique,” has been published in the esteemed journal Materials Letters, which boasts an impact factor of 3.0.

Dr Dwivedy’s research provides insightful analysis of the complex behaviours of duplex stainless steel, a material known for its high strength and corrosion resistance. By employing a property mapping technique, the study reveals the intrinsic heterogeneity and anisotropy of the material’s elastic and plastic properties. This groundbreaking work not only advances the understanding of duplex stainless steels but also opens up new possibilities for their application in various industries.
The publication of this paper in a journal with a significant impact factor is a testament to the quality and importance of the research conducted by Dr Dwivedy and his team. It underscores SRM University – AP’s commitment to fostering cutting-edge research and innovation.

Abstract
Accelerated property mapping, an advanced indentation technique, was used to describe the nanomechanical behaviour of duplex stainless steel (DSS) surfaces prior to and post-heat treatments. Heterogeneity in deformation responses and relative elastic and/or plastic nature of DSS was assessed on longitudinal and transverse directions through load-displacement curves, property maps, histograms of hardness (H), modulus (E) and indentation works. Empirical ratios such as H/E, (H/E)1/2, H3/E2 and plasticity index were employed to understand the anisotropy across the directions. It is crucial that for structural designing, heterogeneity and anisotropy of mechanical behaviour need to be accounted for improved property–optimisation.

Explanation of the Research in Layperson’s Terms

Duplex stainless steel (DSS), a unique category of steel, contains almost equal amounts of ferrite and austenite phases within its microstructure. These are employed in applications like boilers, pressure vessels, heat exchangers, etc., as they offer superior strength, ductility, toughness, and corrosion resistance properties compared to other steels. Mechanical characteristics of DSS are significantly influenced by manufacturing protocols including heat treatments. It is believed that anisotropy and heterogeneity in mechanical behaviour can be driven by microstructures post-material processing.

A comprehensive understanding of DSS material behaviour at the macroscopic scale is not feasible without knowledge of its features and their properties locally. Although the mechanical properties of DSS have been widely explored from a macroscopic perspective as well as innovative nano-scale property mapping techniques, the number of studies addressing anisotropy seen through small-scale characterization is rather restricted. In general, the preliminary assessment of the mechanical behaviour commonly done through hardness (H) and modulus (E) properties. For estimating the elasticity and/or plasticity of material or any surface, different empirical ratios were adopted namely H/E, H3/E2 and (H/E)1/2.

Practical Implementation or the Social Implications Associated
• This study demonstrates the notable differences in mechanical properties in longitudinal and transverse directions along with heterogeneity before and after heat treatments.
• It is felt crucial that for structural designing, heterogeneity and anisotropy of mechanical behaviour need to be accounted for improved property-optimisation.

Link to the article