results 229-240 of 704
An Experimental and CFD- DEM study of spouted Fluidized Bed heat exchanger for Non-Spherical particles
01/03/2023
Inventors: Dr. Pritanshu Ranjan, Dr. Ranjit Patil
This paper presents an experimental and computational study of a spouted fluidized bed heat exchanger designed for non-spherical particles. The research combines experimental measurements with Computational Fluid Dynamics (CFD) and Discrete Element Method (DEM) simulations to analyze the performance and behavior of the heat exchanger. It focuses on understanding how...
This paper presents an experimental and computational study of a spouted fluidized bed heat exchanger designed for non-spherical particles. The research combines experimental measurements with Computational Fluid Dynamics (CFD) and Discrete Element Method (DEM) simulations to analyze the performance and behavior of the heat exchanger. It focuses on understanding how non-spherical particles affect fluid flow, heat transfer, and overall efficiency in the system. The study aims to optimize the design of spouted fluidized beds for improved heat exchange performance and better handling of non-spherical particles, which are common in industrial processes. The goal is to provide insights into enhancing the effectiveness and reliability of heat exchangers used in various applications. (Mechanical Engineering)
Development of New and Novel Nanostructured Materials
18/02/2023
Inventors: Dr. N N Ghosh, Ms. Manisha Mhalsekar
This paper focuses on the development of new and novel nanostructured materials, emphasizing the synthesis, characterization, and potential applications of these materials. It explores various methods for fabricating nanostructures, such as nanoparticles, nanotubes, and nanowires, and examines their unique properties, including enhanced mechanical, electrical, and optical characteristics. The study highlights...
This paper focuses on the development of new and novel nanostructured materials, emphasizing the synthesis, characterization, and potential applications of these materials. It explores various methods for fabricating nanostructures, such as nanoparticles, nanotubes, and nanowires, and examines their unique properties, including enhanced mechanical, electrical, and optical characteristics. The study highlights recent advancements in nanomaterial technologies and their applications in fields like electronics, medicine, and energy. The goal is to advance the understanding and utilization of nanostructured materials, opening new possibilities for innovation and technological development in various scientific and industrial domains. (Chemistry)
Impact of Indigenous S & T innovations developed by Start-ups incubated in academic institutes in India
31/01/2023
Inventors: Dr. Rajorshi Sen Gupta, Dr. Aswini Kumar Mishra
This paper examines the impact of indigenous science and technology (S&T) innovations developed by start-ups incubated in academic institutions in India. It focuses on how these innovations contribute to technological advancement, economic growth, and societal benefits. The study assesses the success stories and challenges faced by these start-ups, evaluating their...
This paper examines the impact of indigenous science and technology (S&T) innovations developed by start-ups incubated in academic institutions in India. It focuses on how these innovations contribute to technological advancement, economic growth, and societal benefits. The study assesses the success stories and challenges faced by these start-ups, evaluating their influence on various sectors such as healthcare, agriculture, and information technology. The paper also explores the role of academic incubators in fostering innovation, providing resources, and supporting entrepreneurial ventures. The goal is to understand the broader impact of these innovations on industry, academia, and the Indian economy. (Economics and Finance)
A Study On Molecular Mechanisms Of Alternative Splicing And Its Regulator SMAR1 In TNF-Α Induced Metabolic Syndrome In Mammalian Skeletal Muscle And Hypothalamic Neuronal Cells
25/01/2023
Inventors: Dr. Indrani Talukdar, Dr. Arnab Banerjee
This paper investigates the molecular mechanisms of alternative splicing and the role of the regulator SMAR1 in TNF-α induced metabolic syndrome within mammalian skeletal muscle and hypothalamic neuronal cells. The study focuses on how TNF-α, a pro-inflammatory cytokine, triggers metabolic syndrome and alters splicing patterns of specific genes. It examines...
This paper investigates the molecular mechanisms of alternative splicing and the role of the regulator SMAR1 in TNF-α induced metabolic syndrome within mammalian skeletal muscle and hypothalamic neuronal cells. The study focuses on how TNF-α, a pro-inflammatory cytokine, triggers metabolic syndrome and alters splicing patterns of specific genes. It examines the involvement of SMAR1, a splicing regulator, in modulating these alternative splicing events and their impact on cellular function. The goal is to uncover the intricate relationship between inflammation, splicing regulation, and metabolic dysfunction, providing insights into potential therapeutic targets for metabolic syndrome and related disorders. (Biological Science)
Roadmap to Flat Holography: Field Theory Candidates
11/01/2023
Inventors: Dr. Rudranil Basu, Sourish Banerjee, Bhagya Krishnan, Sayali Bhatkar, Akhila Mohan
This paper outlines a roadmap for advancing flat holography, focusing on potential field theory candidates. Flat holography is a theoretical framework that seeks to understand how lower-dimensional physical theories can be derived from higher-dimensional ones through holographic principles. The study explores various field theories that could serve as candidates for...
This paper outlines a roadmap for advancing flat holography, focusing on potential field theory candidates. Flat holography is a theoretical framework that seeks to understand how lower-dimensional physical theories can be derived from higher-dimensional ones through holographic principles. The study explores various field theories that could serve as candidates for realizing flat holography, examining their properties, constraints, and how they could be utilized to achieve the goals of this theoretical approach. The roadmap includes a detailed analysis of different field theory models, their feasibility, and their potential contributions to the development of flat holography in theoretical physics. (Physics)
Deciphering Gene Co-Expression Network Of Salinity Stress Responsive Genes
09/01/2023
Inventors: Dr. Rajesh Mehrotra
This paper focuses on deciphering the gene co-expression network of genes responsive to salinity stress. The study aims to understand how different genes interact and regulate each other in response to high salinity conditions, which can affect plant growth and development. By analyzing gene expression data under salinity stress, the...
This paper focuses on deciphering the gene co-expression network of genes responsive to salinity stress. The study aims to understand how different genes interact and regulate each other in response to high salinity conditions, which can affect plant growth and development. By analyzing gene expression data under salinity stress, the paper constructs and evaluates a co-expression network to identify key regulatory genes and pathways involved in stress response. The goal is to gain insights into the molecular mechanisms underlying salinity tolerance and to identify potential targets for improving crop resilience to saline environments. (Biological Science)
Ward identities in Celestial Conformal Field Theory through Explicit Examples
19/12/2022
Inventors: Dr. Rudranil Basu
This paper examines Ward identities within the framework of Celestial Conformal Field Theory (CCFT) through explicit examples. Ward identities are relations that arise from symmetries of a physical theory and are crucial in understanding the conservation laws and symmetry properties of the theory. The study focuses on applying these identities...
This paper examines Ward identities within the framework of Celestial Conformal Field Theory (CCFT) through explicit examples. Ward identities are relations that arise from symmetries of a physical theory and are crucial in understanding the conservation laws and symmetry properties of the theory. The study focuses on applying these identities to CCFT, which is a theoretical framework that extends conformal field theory to a celestial sphere or boundary. By using specific examples, the paper illustrates how Ward identities manifest in CCFT, providing insights into the underlying symmetries and their implications for the theory’s structure and predictions. (Physics)
Real Time Dynamics Of Quarks And Fluons: A Quantum Simulation Approach
26/12/2022
Inventors: Dr. Indrakshi Raychowdhury
This paper explores the real-time dynamics of quarks and gluons using a quantum simulation approach. It focuses on simulating the behavior and interactions of these fundamental particles in high-energy physics. The study involves developing and applying advanced quantum simulation techniques to model the complex dynamics of quarks (the building blocks...
This paper explores the real-time dynamics of quarks and gluons using a quantum simulation approach. It focuses on simulating the behavior and interactions of these fundamental particles in high-energy physics. The study involves developing and applying advanced quantum simulation techniques to model the complex dynamics of quarks (the building blocks of protons and neutrons) and gluons (the carriers of the strong force that binds quarks together). The research aims to provide insights into the fundamental processes occurring in quantum chromodynamics (QCD) and enhance the understanding of particle physics phenomena at a detailed, real-time level. (Physics)
Irreducibility of GLP and related Diophantine problems
29/12/2022
Inventors: Dr. Saranya G Nair
This paper investigates the irreducibility of General Linear Programs (GLPs) and related Diophantine problems. The study explores conditions under which GLPs and certain Diophantine equations (equations involving only integer solutions) can be deemed irreducible, meaning they cannot be simplified into a form that is easier to solve or understand. The...
This paper investigates the irreducibility of General Linear Programs (GLPs) and related Diophantine problems. The study explores conditions under which GLPs and certain Diophantine equations (equations involving only integer solutions) can be deemed irreducible, meaning they cannot be simplified into a form that is easier to solve or understand. The research examines theoretical aspects of irreducibility in the context of optimization problems and number theory, analyzing how these concepts impact problem-solving strategies and computational complexity. The goal is to advance the understanding of problem complexity in GLPs and Diophantine equations, contributing to more effective algorithms and solutions in these areas. (Mathematics)
Development Of A Digital Ecosystem For Leather Authentication And Species Identification
22/12/2022
Inventors: Dr. Amalin Prince
This paper focuses on developing a digital ecosystem for leather authentication and species identification. The ecosystem integrates various digital technologies to verify the authenticity of leather products and accurately identify the species from which the leather is derived. The study involves creating a comprehensive system that includes digital imaging, machine...
This paper focuses on developing a digital ecosystem for leather authentication and species identification. The ecosystem integrates various digital technologies to verify the authenticity of leather products and accurately identify the species from which the leather is derived. The study involves creating a comprehensive system that includes digital imaging, machine learning algorithms, and blockchain technology to track and authenticate leather products throughout the supply chain. The research aims to enhance transparency, prevent fraud, and ensure compliance with regulatory standards by providing a reliable, efficient method for verifying leather quality and origin. (EEE)
Indigenous Development Of Value Implants For Dentistry
22/11/2022
Inventors: Dr. D M Kulkarni
This paper explores the indigenous development of value implants for dentistry, focusing on creating cost-effective and locally manufactured dental implants. It involves designing and producing implants using materials and techniques suited to regional needs and resources. The study includes evaluating the performance, durability, and biocompatibility of these implants compared to...
This paper explores the indigenous development of value implants for dentistry, focusing on creating cost-effective and locally manufactured dental implants. It involves designing and producing implants using materials and techniques suited to regional needs and resources. The study includes evaluating the performance, durability, and biocompatibility of these implants compared to international standards. It also addresses the economic aspects, such as reducing costs and increasing accessibility for patients. The goal is to advance dental care by providing affordable, high-quality implants that meet local requirements and improve dental health outcomes. (Mechanical Engineering)
Developing Predictive Models For Drug Likeness Of Small Molecules
14/11/2022
Inventors: Dr. Raviprasad Aduri, Dr. Sukanta Mondal
This paper focuses on developing predictive models for assessing the drug-likeness of small molecules. Drug-likeness is a critical factor in drug discovery, determining whether a molecule has the properties required for it to be a viable drug candidate. The study involves creating and validating computational models that predict drug-likeness based...
This paper focuses on developing predictive models for assessing the drug-likeness of small molecules. Drug-likeness is a critical factor in drug discovery, determining whether a molecule has the properties required for it to be a viable drug candidate. The study involves creating and validating computational models that predict drug-likeness based on various molecular descriptors, such as solubility, permeability, and toxicity. These models use machine learning and statistical techniques to analyze large datasets of known drugs and their properties. The goal is to enhance the drug discovery process by providing accurate, early-stage predictions of a molecule's potential as a drug candidate. (Biological Science)
