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Publication "Two-Phase Flow and Boiling Heat Transfer Analysis of Macro and Mini-channels at Atmospheric and Subatmospheric System Pressure"(Indian Institute of Tehcnology, Jodhpur, 2024-02-29) Kothdia, HardikPhase change heat transfer processes find extensive application in heat extraction, harnessing both sensible and latent heat. Flow boiling, driven by rapid fluid vaporization, emerges as a highly effective method for high-flux heat transfer. Its versatile applications span refrigeration systems, thermal power plants, nuclear facilities, thermal desalination processes, and electronics cooling. The dominant forces governing flow boiling encompass surface tension, inertia, buoyancy, and viscous forces, crucial for maintaining thermal and momentum equilibrium. These forces are notably influenced by channel orientation, geometry, hydraulic diameter, and operating parameters. Importantly, the impact of these variables varies distinctly between the subcooled and saturated regions of flow boiling. Existing literature lacks comprehensive insights into the impact of orientation, geometry, diameter, and subatmospheric system pressure on flow boiling phenomena. This study delves into the impact of orientation on flow boiling heat transfer coefficients, employing both conventional straight tubes and helical coils. A spectrum of channel hydraulic diameters, spanning from 2 mm to 18 mm, is scrutinized to determine flow boiling heat transfer coefficients, two-phase pressure variations, and the dynamic behavior of wall temperature under two-phase flow conditions. Spatial and temporal variations in wall temperature are meticulously analyzed using thermal imaging technology. The experimental investigations encompass a wide range of operating conditions, including atmospheric and subatmospheric system pressure, with varying mass flux and heat flux values. The analysis includes an examination of the impact of Froude number and Boiling number. The study further investigates pressure drop and fluctuations within these channels under different operating pressure, and it offers a comparative analysis of existing correlations for flow boiling heat transfer coefficients and two-phase pressure drop. In the study, the flow boiling heat transfer coefficient in straight tube exhibits the highest values for horizontal flow, followed by vertical upward flow, and the lowest for vertical downward flow. Wall temperature displays radial asymmetry for Froude numbers below 0.22 due to gravitational effects but is symmetric for vertical up and downflow at all Froude numbers. Two-phase pressure fluctuations are more pronounced in horizontally oriented straight conventional tubes, and two-phase pressure drop is increased with higher mass flux and vapor quality in smaller diameter tubes at lower subatmospheric system pressure. Subcooled flow boiling heat transfer coefficient is higher at lower subatmospheric system pressure, with surface temperature showing radial symmetry under such conditions at all Froude numbers. For mini-channels, heat transfer stability is observed up to a boiling number of 1.76 × 10-4, but subcooled flow boiling heat transfer coefficient exhibits more fluctuations at higher Boiling numbers. Helical coils show variations in heat transfer distribution, critical heat flux, and pressure drop during flow boiling. Vertical-oriented helical coils display higher local and average heat transfer coefficients, with a higher burnout heat flux value compared to horizontal orientation. Two-phase pressure drop in helical coils is higher at subatmospheric system pressure and increases linearly with higher heat flux. This work contributes valuable insights into optimizing flow boiling processes in various geometries and operating conditions, advancing the understanding of heat transfer phenomena.Publication Studies on Electrochemical-Assisted Manufacturing Techniques and Associated Applications(Indian Institute of Tehcnology, Jodhpur, 2024-03-14) Gupta, AnkurAn ever-growing demand for small-scale functional components and the increasing trend of miniaturization in functional systems have led to the rise of microsystems technologies in recent years. Traditional manufacturing processes face limitations in producing precise smallscale tubular and complex structural profiles while maintaining required functional capabilities. Many unconventional manufacturing processes, including electrochemical-assisted techniques, have been revitalized to meet the need for miniaturization. Electroforming, as one of these unconventional processes, enables the low-cost fabrication of high-precision components in cutting-edge micro and nanotechnology domains at room temperature. This work proposes a cost-effective approach for manufacturing metallic and composite tubular structures as well as for metallic deposition on flat and complex surface profiles using an "in-house pulse electroforming" setup. In the upcoming chapter of this thesis, we present the amenable fabrication methodology for small-scale tubular structures, addressing the challenge of fluidic transportation without outflow, applicable in microfluidics, micro heat exchangers, and various biomedical microdevices. We also developed super hydrophobic surfaces over the electroformed structure, achieving a water contact angle of more than 150 degrees on both the interior and exterior surfaces. Additionally, with the widespread use of millions of dyes in the textile industry, there is an engineering challenge to remediate the wastewater generated and protect natural water sources. In this context, we developed nanofunctionalized electroformed tubes for the degradation of Azo dyes, which are considered poorly biodegradable industrial pollutants. Copper/graphene oxide electroform tubes are also developed using an in-built setup and these substrates are utilized for photocatalytic degradation of organic dyes (methyl orange and methylene blue) under sunlight irradiation. Additionally, we developed nano-sized SiC embedded Cu tubular structure, thereby enhancing its mechanical strength and corrosion resistance. We investigated the impact of pulse frequency, duty cycle, bath agitation, and salt concentration with the help of statistical tool (ANN, ANFIS) revealing nuanced effects on surface properties, microhardness, compression, corrosion, and hydrophobicity. Furthermore, the surface micromanufacturing technique is explored to develop porous copper electrode with unique structural and functional properties, holding potential for a wide range of applications in catalysis, sensing, energy storage, and filtration. In addition to it, another work was performed on 3D-printed complex structures to enhance their mechanical strength and functional properties, through a combination of pyrolysis and electrodeposition techniques. Digital light processing (DLP) based additively manufactured structures underwent pyrolysis, transforming into carbon with a 90% of volumetric shrinkage, followed by Ni-Cu bimetallic electrodeposition for hydrogen evolution reaction (HER) and microelectromechanical (MEMS) applications. In another study, we explored electrochemical energy to propose an effective solution for the treatment of textile wastewater before discharging it into natural waterbodies, which includes the real-time photocatalytic degradation using novel ZnO caterpillars along with the electrochemical processing. Additionally, to reduce the processing time, we also performed the analysis by exploring the ultrasonic-assisted technique along with the statistical optimization of parameters.Publication Application of Clay and Silica Alumina Supported Metal Catalysts for Hydrogenation and Hydrotreatment Reactions(Indian Institute of Tehcnology, Jodhpur, 2024-01-31) Sharma, Rakesh KumarConsidering the global quest for environmental sustainability and a dire need for effective energy use, catalytic hydrogenation and hydrotreatment have emerged as a critical process in value-added products, petrochemicals, and environmental industries. The thesis aims to develop efficient green catalytic systems synthesizing fine chemicals for industrial scale and exploring the potential of upgrading model compound methyl oleate and biomass resources such as vegetable oils for large-scale production of diesel-grade hydrocarbons. The main objectives laid out in this thesis are focused on the synthesis of natural clay or silica-alumina supported metal catalysts. The idea is to use these catalysts for various applications relating to value-added products and the production of biofuels. These catalysts frequently exhibit improved catalytic activity, enhancing reaction rates and better selectivity. The study aims to provide insights into sustainable chemistry and engineering practices, leading to industrial applications, catalyst design, and new sustainable catalysts. The study aims to enhance catalytic efficiency, minimize waste, and find economically viable and environmentally benign materials to ensure its wide usability and production. The studies undertaken in this thesis attempt to address some of these issues. The use of clay as a cost-effective, environmentally benign, and abundant support is an ideal choice. Clay-supported metal catalysts are compatible with green chemistry principles, leading to increased productivity and a reduced need for potentially hazardous solvents. The study presents a simple wet-impregnation route for a sustainable natural clay-supported palladium catalytic system for the hydrogenation of imine to amines, feedstock for agrochemicals, and pharmaceuticals. The catalytic system was investigated under mild reaction conditions, and its catalytic activity and effect on reaction conditions were analyzed. Catalyst immobilization on clay supports results in reduced costs and waste generation by allowing the recycling of metal catalysts. The mechanistic details of imine hydrogenation are elucidated, structural, chemical, and morphological properties of these catalysts are examined, and reaction conditions are optimized to achieve high conversion rates and selectivity. The study emphasizes the need for greener technology in synthesizing fine chemicals for industrial scale due to rising energy demand and environmental concerns. Additionally, studies have been done to explore the impact of non-noble metal integration in a SiO2–Al2O3 catalyst on the conversion of methyl oleate into diesel-grade aliphatic hydrocarbons. This study presents the effect of cobalt incorporation into the SiO2-Al2O3 hybrid catalytic system on the conversion, selectivity, and stability of the catalytic conversion of methyl oleate as a model compound for biofuels. The study found that the amount of Co loading, reaction time, temperature, and H2 pressures greatly influence the conversion and selectivity. The complete ester conversion rate and substantial yield towards n-heptadecane / n-octadecane are achieved under solvent-free conditions. Further, iron poisoning on nickel oxide supported on silica-alumina catalysts is investigated. Here, Bimetallic FexNiy/SA catalysts were synthesized using the hydrothermal method followed by chemical deposition strategies. The study also investigated the characterization and tuning of FexNiy/SA catalysts for the low-temperature hydrodeoxygenation (HDO) of methyl oleate and vegetable oils to n-alkanes. Out of all catalysts, The Fe1Ni1/SA catalyst demonstrated outstanding HDO efficiency, conversion, and hydrocarbon selectivity. The Fe2+/Fe3+ ratio in FeaOb species on the FexNiy/SA catalyst regulates the carbon number distribution of generated hydrocarbons, suggesting a viable strategy for designing an efficient HDO catalyst.Item On Some Problems For Graph Induced Symbolic Systems(Indian Institute of Technology Jodhpur, 2024-02-15) Sharma, PuneetSymbolic dynamics was introduced in the late 19th century by Jacques Hadamard, where he applied the theory of symbolic dynamics to examine the geodesic flows on surfaces of negative curvature [Hadamard, 1898]. Later, Morse and Hedlund used symbolic dynamics as a tool to study the qualitative behavior of a general dynamical system [Morse and Hedlund, 1938]. In 1948, Shannon employed symbolic dynamics to examine certain fundamental problems in communication theory [Shannon, 1948]. The convenience of symbolic representation and easier computability of the system has attracted attention of several researchers around the globe and the topic has found applications in various branches of science and engineering. In particular, the area has found applications in areas like data storage, data transmission and communication systems to name a few [Shannon, 1948; Lind and Marcus, 1995; Kitchens, 1998]. Since it is known that every discrete dynamical system can be embodied in a symbolic dynamical system (with an appropriate number of symbols) [Fu et al., 2001], it is sufficient to study the shift spaces and its subsystems to investigate the dynamics of a general topological dynamical system. In this work, we investigate a d-dimensional shift space arising from a d-dimensional graph G = (G1;G2 :::Gd), where each graph Gi has common set of vertices and i-th graph determines the compatibility of vertices in the i-th direction. In particular, we investigate non-emptiness, finiteness, existence of periodic points and mixing notions for a d-dimensional shift space. We examine the structure of the shift space using generating matrices and establish that a d-dimensional shift of finite type is finite if and only if it is conjugate to a shift generated through permutation matrices. We establish conditions under which a two-dimensional shift space is non-empty and contains periodic points. We introduce the notion of an E-pair for a two-dimensional shift space and use it to derive sufficient conditions for non-emptiness, finiteness and periodicity of the two-dimensional shift space under discussion. Additionally, we study properties such as transitivity, directional transitivity, weak mixing, directional weak mixing and total transitivity for the two-dimensional shift space XG. We assert that if the condition (HV)i j 6= 0 , (VH)i j 6= 0 holds for all i; j 2 V (G), then the irreducibility of any generating matrix guarantees the equivalence of transitivity and directional transitivity for the shift generated by the graph G = (H;V). We present examples demonstrating that weak mixing and totally transitivity are not analogous in two-dimensional shift spaces (it is known that these two notions coincide in one-dimensional case). Further, we characterize directional transitivity (in (r;s)-direction for rs > 0) through the block representation of HrV s. We provide necessary and sufficient criteria to establish horizontal (vertical) transitivity for the shift space XG. We investigate the topological dynamics of a general two-dimensional shift space generated by a graph G = (H;V) through matrices M;N; where M;N are indexed with allowed triangular patterns of form c a b ; x z y respectively. We investigate how the characteristics of matrices M and N are related to one another. We derive sufficient conditions on M and N to exhibit non-emptiness and existence of periodic points for shift space XG. We assert that if the condition MIJ 6= 0 , NI1J1 6= 0 holds for all E-pairs (I;I1) and (J;J1); then XG is doubly (1;1)-transitive ((1;1)-weak mixing) if and only if M is an irreducible (Primitive) matrix. We establish that under imposed conditions, (1;1)-weak mixing implies (r;s)-weak mixing (for rs > 0) for XG. We provide necessary and sufficient conditions for any graph G to be expressed as a graph product of two smaller graphs. We relate the dynamics of one-dimensional shift space XG with the dynamics of component shift spaces XGi, where graph G can be expressed as graph product (Cartesian, Tensor, Lexicographic and Strong Product) of two smaller graphs G1;G2. We investigate structural properties such as non-emptiness problem and the existence of periodic points for shift spaces through graph product of two-dimensional graphs. We assert that a shift arising from Cartesian (Lexicographic, Strong) product of two-dimensional graphs is always non-empty and possesses periodic points, but the shift arising from Tensor graph product is non-empty and contains a non-empty set of periodic points if and only if each component shift space (i.e., XGi) is non-empty and possesses periodic points. Finally, we examine various mixing notions such as transitivity, directional transitivity and weak mixing for two-dimensional shift space XG (under imposed condition) through its component subshifts XGi.Item Flexible Organic Transistors for E-Textile and Memory Applications(Indian Institute of Tehcnology Jodhpur, 2023-11-04) Tiwari, PrakashFlexible electronics has been explored as a low cost technology for numerous applications such as wearable devices, foldable displays, and E-textiles, etc. and offers advantages such as large area applicability, low temperature processing, and adaptability for heterogeneous integration. Organic field effect transistor (OFET) is a crucial device for flexible electronics, which has been explored for various circuit, sensing, and memory applications. Gate dielectric is a crucial component for optimization to achieve high performance and stability in OFETs. This work demonstrates OFET devices with various dielectric combinations for circuit and memory applications. Moreover, a unique strategy for fabrication of devices on textile substrates is demonstrated. To start with, flexible OFETs were demonstrated with bilayer hybrid gate dielectric with various polymers and polyelectrolyte dielectrics such as P(VDF-TrFE), PVP-co-PMMA and polyelectrolyte polyacrylic acid (PAA) in combination with a thin layer of high-k hafnium oxide (HfOx) grown by atomic layer deposition (ALD). TIPS-Pentacene was used as semiconductor. The optimized devices operated at -10 V with decent Ion/Ioff values ranging from ~104 to ~103. The devices with HfOx/PAA dielectric exhibited better performance compared to other counterparts due to higher capacitance density, along with excellent cyclic stability for continuous 500 cycles. Moreover, these devices showed high bending stability upon different radii up to 5 mm causing tensile stress. Further, a bilayer of polyvinyl alcohol (PVA)/(PAA) was used as gate dielectric to demonstrate low voltage high-performance flexible OFETs on a plastic and paper substrate. A super strong hydrogen bonding between PVA and PAA confirmed by fourier-transform infrared (FTIR) spectroscopy makes it a potential solution-processed bilayer dielectric candidate. Fabricated devices with TIPS-Pentacene: PS blend exhibited -5 V operation with nearly zero threshold voltage and high Ion/Ioff of ∼104. High bending stability was achieved upon successive bending in different ways. These devices were also used to demonstrate resistive-load inverter circuit. The devices fabricated on paper showed a significant level of disintegration in soil with a bio fertilizer. OFET devices on fabric substrate were successfully demonstrated by a simple lamination technique. These devices with TIPS-Pentacene:PS blend as active layer and high-k P(VDF-TrFE) gate dielectric showed maximum and average field effect mobility of ∼1.2 and ∼0.5(±0.3) cm2 V-1 s-1 in the saturation regime, and Ion/Ioff of ∼103 with an low operating voltage of -5 V along with excellent bending stability. Excellent cyclic stability for 500 cycles was performed. Moreover, a high shelf life in ambient for 26 weeks was observed from these devices. Finally, solution-processed flexible non-volatile memory (NVM) based on OFETs (OFETNVMs) were demonstrated with TIPS-Pentacene and P(VDF-TrFE) as gate dielectric. These OFET-NVMs showed excellent memory behaviour with very high memory window (MW) of 12 V for VGS sweep of ±15 V and low VDS of -5 V. Moreover, these devices show memory Ion/Ioff ∼103 for 100 continues cycles alongwith stable retention capability for higher than 104 s. These devices showed fairly stable and reliable NVM behaviour even after subjected to 100 repeated bending cycles. Despite of fact that minimal degradation in performance was observed upon bending. These devices are promising candidate for further exploration into flexible electronics due to overall excellent memory performance of the devices.Item Flash Evaporation Process: Semi-Analytical Model Development for Droplets and Laminar Thin Film Flow(Indian Institute of Technology Jodhpur, 2022-12) Chakraborty, Prodyut R.With the advent of miniaturization technology of electronic components and development of high energy devices, the cooling requirements of electronic systems has changed drastically. The localised high heat flux on micro level components has also become of the order of kW/cm2. For such a high heat flux, the conventional methods are unviable, as they need large flow rate of coolant to achieve tough temperature control. Due to the aforementioned reasons, the research in the field of Thermal Management System (TMS) for electronic systems becomes need of present to identify new cooling technologies. Flash evaporation cooling method is one of the potential contestants among futuristic thermal management technologies. Typically, flash evaporation process involves sudden depressurization of liquids below the saturation pressure corresponding to the liquid temperature. Due to the sudden drop in pressure, the whole energy cannot be contained in the liquid as sensible heat, and the surplus heat gets converted into latent heat of vaporization followed by a violent transition of liquid to vapor phase. During flash evaporation process, the latent heat of evaporation is absorbed mostly from the liquid itself, and temperature of the liquid falls very quickly. The commonly adopted mechanisms in industries are pool flashing, spraying of fluid in the form of droplets, flashing of flowing fluid and flashing of jets etc. Albeit being a fundamental cooling mechanism with numerous day today applications, there exists many a rarely studied problem description that involves evaporation cooling mechanism requiring suitable analytical treatment. Therefore, the present work focuses on investigating the flashing phenomenon with varying flow conditions? as droplet evaporation, flashing of film on vertical plane and convective heat transfer of falling film with emphasis on development of analytical and numerical models. The first part of the study is attributed to the development of a semi analytical transient heat diffusion model of droplet evaporation. The model is developed considering the effect of change in droplet size due to evaporation from its surface? when the droplet is injected into vacuum. Hertz and Knudsen formulation based on kinetic theory to evaluate evaporation mass flux from the free surface is considered. The study addresses the discrepancy in the values of obtained evaporation coefficients reported for diffusion based mathematical model and lumped heat model, where evaporation coefficient is termed as the ratio of actual evaporating mass flux rate to the maximum possible evaporating mass flux rate. The model shows strong dependence of evaporation coefficient on microdroplet size. Moreover, when the droplet radius is less than that of mean free path of vapor molecules at the evaporating surface, the evaporation coefficient is found to approach theoretical limit of unity and reduces rapidly for larger radii. Water has been considered as working fluid for the saturation temperature range of 295273.16K in the present study. The next set of analysis involves the development of a semi analytical model that addresses the hydrodynamic behavior of fluid film, falling on an adiabatic wall, under the effect of gravity with smooth laminar flow conditions. Although many researchers have carried out the hydrodynamic study of gravity driven vertical falling film in the last five decades, Reynolds Transport Theorem (RTT) has never been employed prior to the present work. The adopted approach is validated with the help of published literature, by comparing obtained parametric relations with the reported set of equations. A good agreement of the experimental results with obtained data provided an adequate confidence to use RTT for further study of convective heat transfer and flash evaporation. Thereby, the analysis led the foundation for heat transfer studies made further. With the shown conformity of previous investigations, the study is extended to convective heat transfer from the free surface of gravity driven vertical falling film. Unlike falling film evaporators, where fluid film gets heated from the wall on which it travels, the heat transfer takes place from the free surface to the film's interior in the present analysis. Consequently, an entirely new phenomenon has been considered, where thermal boundary layer develops at free surface, and thickens in the downstream flow direction towards wall. Therefore, the effect of thermal boundary layer on heat transfer mechanism from the free surface has rigorously investigated with the help of 1D heat transfer model. The developed model is based on the RTT. The model has further been extended by exposing the falling film in the vacuum, where pressure is maintained lower than the saturation pressure of liquid, corresponding to liquid temperature. A semi analytical 1D model has been developed considering RTT and Hertz and Knudsen formulation based on kinetic theory to evaluate evaporation mass flux from the free surface. Oneway coupling ( i.e hydrodynamic parameters effect the thermal behavior but reverses not true) has been employed. The rigorous study of the model involves the numerous parametric variations that have been checked for the physical consistency. The required parameters for the flash evaporation based thermal management system design have been evaluated minutely and distinctly. The detailed examination of thermal parameters like? surface temperature, bulk temperature, mass flux rate along with hydrodynamic parameters has been culminated in the form of unique unprecedented correlations. The correlations determined for local Nusselt number, surface temperature, bulk mean temperature and film thickness are validated with the set of data distinct from the data set through which the correlations are developed. Excellent agreement between the data obtained through proposed semi analytical model and data calculated through determined correlations is observed. The proposed analytical and numerical models along with the correlations, contribute towards heat transfer mechanism from the free surface of smooth laminar film under low pressure environment. The models further help to identify design parameters for flash evaporation based cooling. Moreover, the presented analysis provides an underlying basis for the development of two way coupling for thermal behavior and hydrodynamic analysis. Waviness of surface, temperature dependency of fluid properties, surface tension of liquid, buoyancy effect and roughness of adiabatic wall, may further be added in the present model at the cost of increasing complexity.Item Cascade Synthesis of Diverse Heterocycles(Indian Institute of Technology Jodhpur, 2023-06) Rana, Nirmal K.Heterocycles are the largest and most diversified families of organic compounds. They play significant roles in chemical synthesis as well as in bio-chemistry. Therefore, developing innovative and efficient methodologies for synthesizing multifunctional heterocyclic compounds, with the goal of achieving higher molecular complexity and improved functional group compatibilities from readily available starting materials under mild reaction conditions, is a significant area of today's research. Cascade approaches have long been acknowledged as they provide an admirable collection of strategies and tactics for developing novel and efficient routes with a minimum number of operations for synthesizing complex molecules. These classes of reactions represent not only the multiple bond-forming transformations but also the subsequent reactions in which the functionalities created in the earlier steps are manifested. One-pot approaches are used to increase the overall efficiency of processes by reducing physical efforts well as minimizing the use of solvents and chemicals. On the other hand, the use of supported catalysts/reagents has revolutionized the field of chemistry. The immobilization of the catalyst onto a solid support material prevents its loss during the reaction, increases its surface area, and enhances its selectivity and efficiency. It is an attractive field of research in organic synthesis due to several advantages over traditional catalysts/reagents i.e., simplified product purifications, reusability, reduction of side products, less waste generation, and economic process. These make the process more sustainable and greener as well. In this thesis, the research work encapsulated, is focused on the development of novel and sustainable cascade approaches towards the synthesis of diverse heterocyclic compounds. The thesis is divided into six chapters. Chapter 1 presents the importance of heterocycles and summarized the advancement of organocatalyzed methods towards the construction of diverse heterocycles such as tetrahydrothiophene, ?-pyrones, dihydroindoles and benzoxazoles. Next, we have discussed the objectives, scope and the structure of the thesis. Chapter 2 includes polymer-supported base-catalyzed synthesis of sulfur-containing heterocycles, trisubstituted tetrahydrothiophenes and spiro-thiazolone-tetrahydrothiophenes, via thia-Michael/aldol cascade approach. Chapter 3 deals with the synthesis of oxygen-rich heterocycles, ?-pyrones, through polystyrene-linked DMAP-catalyzed Michael-addition/lactonization/elimination reactions. In chapter 4, nitrogen-containing heterocycles, dihydroindoles, were synthesized utilizing supported-pyridinium ylide and sulfur ylide as a C-1 synthons. Chapter 5 represents the development of novel approach for the construction of 2-aryl benzoxazoles. These compounds seem to have potential activities as agonists for the biogenesis of utrophin. In the last chapter, we have concluded the thesis with future scopeItem Molecular Strategies Based Elevation of Protein Quality Control Mechanism: Rejuvenate Aberrant Proteins Aggregation Linked Defective Proteostasis(Indian Institute of Technology Jodhpur, 2023-11) Mishra, AmitGeneration of new proteins and removal of damaged or old polypeptides is an uninterrupted mechanism essential for a healthy cellular environment. Impairment in the removal of misfolded proteins can disturb proteostasis; such toxic aggregation of misfolded proteins can act as a preliminary causative agent for neurodegenerative disorders and imperfect aging. Therefore, removal of such abnormal aggregates can ensure the re-establishment of proteostasis; the ubiquitin-proteasome system (UPS) actively participates in the specific clearance of aberrantly folded clients with the help of complex proteasome machinery. The critical challenge is to design effective protein quality control (PQC) based molecular tactics that could potentially eliminate aggregation-prone protein load from the cell. E3 ubiquitin ligases impart ability for identifying unique critical misfolded protein clients for targeting them towards proteasomal degradation. Several neurodegenerative and neurodevelopmental disorders are known to have compromised functioning of specific protein quality control E3 ubiquitin ligases. The work presented here involves use of Itraconazole and Resveratrol to improve critical protein quality control functions of the cell in order to improve the removal of toxic abnormal protein aggregates thus, increasing cellular resistance towards proteotoxic stress mechanisms. The results demonstrate specific potentials of Itraconazole to enhance proteasome activity for increasing the clearance of various model and neurodegeneration causative abnormal proteins. Furthermore, Resveratrol exposure was found to significantly enhance the LRSAM1 E3 ubiquitin ligase, found mutated during spongiform neurodegeneration, levels in the cell. The expression levels of LRSAM1 were also found to influence the proteasome chymotrypsin-like and post-glutamyl peptidyl-hydrolase like functions. Resveratrol being a plant based stilbenoid compound was able to stop the occurrence of toxic proteinaceous species in the cell. The present work implicates the potential of improving protein quality control as significant therapeutic measure against several protein aggregation-based disorders. Moreover, specific potentials of upregulating proteasome and quality control E3 ubiquitin ligase functions by Itraconazole and plant derived Resveratrol can help to increase cellular cytoprotectionItem Towards More Realistic Shock Models with Applications in Optimal Maintenance(Indian Institute of Technology Jodhpur, 2023-02) Hazra, Nil KamalIn this thesis we study some generalized shock models with applications in optimal maintenance. Most of the systems used in reality are directly or indirectly a↵ected by some harmful “instantaneous” events (shocks of di↵erent nature), which either cause the system’s failure or decrease the system’s lifetime. Thus, the study of systems’ lifetimes subject to external shocks is one of the important problems in reliability theory. In a shock modeling, one has to answer two important questions, namely, “how the occurrences of shocks a↵ect or decrease the lifetime of a system” and “how one can model the occurrences of shocks on a system ”. In this thesis, we answer these questions in di↵erent setups. Existing shock models are usually classified into four broad classes, namely, extreme shock models, cumulative shock models, run shock models and !-shock models. The !-shock model, which is an object of our study, is di↵erent in nature from other aforementioned shock models. In all !-shock models developed so far in the literature, the recovery time ! was assumed to be constant. However, this assumption is too restrictive and unrealistic in describing many real-life scenarios. Indeed, ! can obviously depend on other parameters, namely, magnitude of shocks, arrival times of shocks, etc. This motivates us to introduce a new time-dependent !-shock model wherein the recovery time of a system is assumed to be an increasing function of arrival times of shocks. For this model, we assume that shocks occur according to the generalized P´olya process (GPP) that contains the homogeneous Poisson process (HPP), the non-homogeneous Poisson process (NHPP) and the P´olya process as particular cases. We further generalize this model to the general !-shock model by considering the recovery time ! as the function of both arrival times and magnitudes of shocks. We also consider a more general and flexible shock process, namely, the Poisson generalized gamma process (PGGP) that includes the HPP, the NHPP, the P´olya process and the GPP as the particular cases. With the same motivation, we study a history-dependent mixed shock model which is a combination of the history-dependent extreme shock model and the history-dependent !-shock model. As an application of the aforementioned new shock models, we study the optimal replacement policy. Although Poisson processes are widely used in various applications for modeling of recurrent point events, there exist obvious limitations. Several specific mixed Poisson processes (which are formally not Poisson processes any more) that were recently introduced in the literature overcome some of these limitations. We define a general mixed Poisson process with the phase-type (PH) distribution as the mixing one. As the PH distribution is dense in the set of lifetime distributions, the new process can be used to approximate any mixed Poisson process. We study some basic stochastic properties of this new process and discuss some relevant applications by considering the extreme shock model, the stochastic failure rate model and the !-shock model. We introduce and study a general class of shock models with dependent inter-arrival times of shocks that occur according to the homogeneous Poisson generalized gamma process (HPGGP). A lifetime of a system a↵ected by a shock process from this class is represented by the convolution of inter-arrival times of shocks. This class contains many popular shock models, namely, the extreme shock model, the generalized extreme shock model, the run shock model, the generalized run shock model, specific mixed shock models, etc. For systems operating under shocks, we derive and discuss the main reliability characteristics and illustrate our findings by the application that considers an optimal mission duration policy. Counting processes based on heavy-tailed distributions (namely, the fractional homogeneous Poisson process (FHPP), the renewal process of matrix Mittag-Leffler type (RPMML), etc.) have not yet been considered in the literature for modeling the occurrences of shocks. Thus, we study some general shock models under the assumption that shocks occur according to a renewal process with the matrix Mittag-Leffler (MML) distributed inter-arrival times. As the class of MML distributions is wide and well-suited for modeling the heavy tail phenomena, these shock models can be very useful for analysis of lifetimes of systems subject to random shocks with inter-arrival times having heavier tails. Some relevant stochastic properties of the introduced models are described. Moreover, two applications, namely, the optimal replacement policy and the optimal mission duration are discussed. Lastly, we consider coherent systems subject to random shocks that can damage a random number of components of a system. Based on the distribution of the number of failed components, we discuss three models, namely, (i) a shock can damage any number of components (including zero) with the same probability, (ii) each shock damages, at least, one component, and (iii) a shock can damage, at most, one component. Moreover, the arrivals of shocks are modeled using three important counting processes, namely, the PGPP, the Poisson phase-type process (PPHP) and the RPMML. For the defined shock models, we study some reliability properties of coherent systems. At the end, we discuss the optimal replacement policy as an application of the proposed models.Item On Some Important Reliability Aspects of General Coherent Systems(Indian Institute of Technology Jodhpur, 2023-11) Hazra, Nil KamalIn practice, we use di?erent kinds of systems that are structurally equivalent to various well-established systems available in the literature, namely, ordinary coherent systems, ordinary r-out-of-n systems, sequential r-out-of-n systems, fixed weighted coherent systems, fixed weighted r-out-of-n systems, random weighted coherent systems, random weighted r-out-of-n systems, etc. In this thesis, we study di?erent reliability aspects of these systems under various scenarios. In most real-life scenarios, the components of a system work in the same environment and share the same load. As a consequence, there may exist two di?erent types of dependencies between the components of a system, namely, interdependency and failure dependency. The interdependency structure between the components of a system is usually modeled by a copula. The family of Archimedean copulas is commonly used to serve this purpose as it describes a wide spectrum of dependence structures. On the other hand, the failure dependancy for a system means that the failure of one component has an e?ect on the lifetimes of the remaining components of the system. This failure dependency is often modeled by assuming distributional changes in the lifetimes of the remaining components, upon each failure, of the system. The sequential order statistics (SOS) and the developed sequential order statistics (DSOS) are two models that are commonly used to describe the failure dependency of a system. There is a one-to-one relationship between order statistics and the lifetimes of systems. For example, the lifetime of an ordinary r-out-of-n system is the same as the (n ? r + 1)-th order statistic of the lifetimes of the components of the system. Similar relationships exist for SOS and DSOS. Thus, the study of order statistics is the same as the study of the lifetimes of systems. In this thesis, we study various ordering and ageing properties of ordinary r-out-of-n systems formed by dependent and identically distributed components, where the dependence structure is described by an Archimedean copula. Further, we study the ordering properties of the developed sequential order statistics (DSOS) with the dependence structure described by the Archimedean copula. Similar to the DSOS model, we introduce the notion of developed generalized order statistics (DGOS) which is an extended generalized order statistics (GOS) model formed by dependent random variables. This model contains all existing models of ordered random variables. We study various univariate and multivariate ordering properties of the DGOS model governed by the Archimedean copula. Further, we consider the SOS model with non-identical components and study several univariate and multivariate stochastic comparison results. The basic structures of many real-life systems match with random weighted coherent systems. The performance of a random weighted coherent system is usually measured by its total capacity. However, the major drawback of this measure is that it does not take into account the structure of a system. To overcome this drawback, we introduce a new structure-based performance measure, namely, the survival capacity. Based on this measure, we define three survival mechanisms (namely, Types-I, II and III) for random weighted coherent systems. We develop a methodology to evaluate the reliability of a random weighted coherent system, and provide a signature-based reliability representation for this system. Further, we study di?erent reliability importance measures for the components of a random weighted coherent system. We study the optimal allocation strategy of active redundancies and the optimal assembly method of random weights in a random weighted coherent system. By developing the results for random weighted coherent systems, we generalize many well-established results available for ordinary coherent systems and weighted coherent systems in the literature.Item Study of Organic and Quantum Dots-Based Resistive Memory and Synaptic Devices(Indian Institute of Technology Jodhpur, 2023-09) Sahu, SatyajitThe data storage requirement in the digital world is increasing day by day with the advancement of the Internet of Things (IoT). The current generation of silicon-based memory technology is facing serious problems in terms of performance, data storage density, power consumption, data processing time, cost-effectiveness, and so on. Conventional flash memory is one type of non-volatile memory that relay on tunneling through the oxide layer, consumes high power, and response time is high. The hard disk drive (HDD) is a widely used memory in the current era, but the main disadvantage is finding the particular magnetic domain where the data is saved, which leads the memory response time to a few milliseconds. The limitations of conventional memories can be tackled by next-generation memories. Ferroelectric random access memory (FERAM), Phase change memory (PCM), Magnetic random access memory (MRAM) and Resistive random access memory (RRAM) are considered as next-generation memory and have the potential to solve the problem. Among the other memories, non-volatile RRAM is an option that provides high-density and low power data storage capabilities. The information is stored in terms of resistance, where the high resistance state (HRS) is 0 bit, and the low resistance state (LRS) is 1 bit. The computers are based on von Neumann architecture, where processor units are separated from the memory unit and connected via a data bus. This causes a delay in response time and cannot go beyond a certain size limit, called von Neumann bottleneck. The current resistive memory has the capability to solve the von Neumann bottleneck, where the memory can simultaneously process and store data similar to the biological brain. The small molecule-based RRAM device is a point of interest because of its capability to be used in high-density data storage devices. A small organic molecule 5-Mercapto-1-methyl tetrazole (MMT) has been used with a polymer poly (4-vinyl pyridine) (PVP) matrix for the active layer of RRAM device. The MMT molecule with a different weight ratio in PVP was studied for RRAM application which reveals the invariant RRAM property. The maximum on?off current ratio for all the devices is 105, suggesting that the MMT molecule does not show any change in its characteristic properties when surrounded by an insulating material. When the device was fabricated without the polymer matrix, the surface morphology of the device completely changed as it was filled with large holes. These holes provide short-circuited pathways for the current by forming the direct metal contact between the top and bottom electrodes. Size miniaturization of the electronic device can be done using organic small molecules as well as inorganic nanoparticle QDs. The synthesis of CdS QDs and the study of RRAM properties has been studied. Al/CdS+PVP/ITO like MIM structured device was fabricated which shows extremely good switching properties. The data retention capability of 60000 seconds and 300 endurance cycles were studied. The charge-trapping mechanism is associated with the RS property. With the development of artificial intelligence and ultra-high speed computing the solution of von Neumann bottleneck is needed. In this regards, resistive memory can provide solution as RRAM has the capability to act as biological synapse that can store, process and transfer data. This attracts researchers to study resistive memory devices. Here fabrication of a small organic molecule Trimesic acid (TMA) and PVP composite-based resistive memory device. It shows excellent resistive switching with a high on-off ratio, excellent stability and data storage capability. Pulse transient measurements on the device demonstrated the capability of neuromorphic computation. The gradual set and reset process and change of conductance with an applied pulse confirmed the neuromorphic application. Paired pulse facilitation shows that the device can behave like the human brain. The redox active molecule and its change in conformation are the reasons for the switching behaviour of the device th led to the neuromorphic application of the device. For an important application like RRAM, it is crucial to understand the mechanism in nanoscale and control the Resistive switching (RS) by various means. Different models have been proposed to explain the RS behaviour of the material. First, the electrode effect on the switching, which includes contact type, and charge trapping/de-trapping near the electrodematerial interface. The other mechanisms are conducting filament formation, electrochemical metallization, ionic diffusion, and oxidation-reduction of the materials. So, there are many disagreements on the proposed models of RS, and it requires understanding using different experimental techniques. STM is one of the best tools for understanding the surface property, as well as studying the local density of states (LDOS) of the material. So, using the scanning tunnelling microscopy (STM) technique to understand the RS in materials in the nanoscale range would be very helpful. The RS properties and capabilities of neuromorphic computing of single AgInS2 quantum dot with the help of STM and scanning tunnelling spectroscopy (STS) have been studied in this chapter. The bandgap of the material and its temperature dependency has been studied and it suggests a nonlinear and linear variation at lower and higher temperature than the Debye temperature respectively. The STS shows the change of conducting states after applying localized pulses. The devices made from the quantum dots replicate these properties as well. The neuromorphic application of the device was tested by using the pulse transient measurement that mimics the learning and forgetting of information through the gradual set and reset process. The localized ionic transport is involved in the RS mechanism.Item Tin Oxide Based Nanomaterials for Gas/VOC Sensing(Indian Institute of Technology Jodhpur, 2023-09) Gupta, RituExtensive usage of toxic, flammable, and explosive Volatile Organic Compounds (VOCs)/ gases in industry induces tremendous environmental pollution leading to a threat to living organisms. Therefore, there is a requirement for continuous monitoring of VOCs/gases using cost-effective, highly selective, sensitive, environmentally stable sensors. So, our work focuses on different approaches to modify the SnO2 for developing low-temperature operable humidity tolerant VOCs/gases sensors. NO2, the most common toxic gas, induces various respiratory diseases even for short-term exposure at a low concentration of 5 ppm. Thus SnO2-rGO is synthesized at optimized conditions by the solvothermal method. In the SnO2-rGO nanohybrid device identified through a combinatorial approach, optimum morphology and structure along with the intrinsic Sn-C bond exhibited a significant response of ~3 to a low concentration of 80 ppm NO2 at room temperature operation and fluctuating humidity (20-50% RH) at much faster speeds ~5.6 s and recovered quickly in 14.1 s without heating. Xylene, one of the components of cigarette smoke, is a major contributor to indoor pollution and induces various respiratory diseases. We synthesized Sn-SnO2 as a sensing material with unique mesoporous nano-spherical morphology, providing a high specific surface area for Volatile Organic Compounds (VOCs)/gases adsorption. The sensor exhibits a repeatable response of 255% at 60 ppm xylene at room temperature with unprecedented ultrafast response and recovery time of 1.5 s and 40 s, respectively. The concentration of NH3 in the exhaled breath of healthy persons is about 0.4–1.8 ppm, while that in end-stage renal disease patients is around 0.8–14.7 ppm. Hence, disease state monitoring and environmental exposure assessment applications demand highly sensitive, faster, and more selective NH3 sensors that can operate under various environmental conditions. In our study, we synthesized SnO2 nanosheets using a solvothermal method and carefully optimized the pH conditions of the precursor solution for tuning the size, crystallinity, and thickness. The sensors fabricated using these samples exhibited a selective response to ammonia at 25 ºC and relative humidity (RH) of 70%. The pH 14 device demonstrated the highest sensitivity to ammonia (150% at 100 ppm) with fast response (8 s) and recovery kinetics (55 s). A theoretical LOD of 64 ppt implies superior sensitivity to all previously reported SnO2-based chemiresistive sensors. Triethylamine becomes explosive at concentrations above 10 ppm in the air and can induce headaches and difficulty breathing as well. The optimized substitutional fluorine doping in SnO2 film results in high conductivity, hydrophobicity, transparency, reduction in oxygen defects, and excellent electrochemical stability. Consequently, the fabricated F-SnO2 sensor showed a humidity-resistant nature with the highest response of 52% towards triethylamine at a relatively low operating temperature. Thus, the gas and VOC sensors developed in this work can be deployed for real-time sensing after miniaturization and integration with the AIoT platform.Item Development of Computational Methods for Multi-omics Data Analysis(Indian Institute of Technology Jodhpur, 2022-07) Paul, SushmitaHolistic understanding of human health and disease demands interpretation of molecular complexity and variations at multiple levels such as the genome, epigenome, transcriptome, proteome, metabolome, and others. High-throughput technologies have revolutionized medical research. The field of biology has become increasingly dependent on data generated at the above mentioned levels, which together is called �multi-omics� data. An abundance of multi-omics data has transformed the discipline of biology and medicine and generated opportunities for integrated system-level approaches. Multi-omics studies are based on data-driven scientific interrogations that help analyze a wide range of multi-dimensional datasets at various levels that can be scaled to unravel cellular complexity. With the advancement in high-throughput technologies, cancer research has also observed a paradigm shift toward multi-omics approaches, expanding initiatives in comprehensive research collaboration and progression of computational pipes and algorithms. An in-depth understanding of cancer�s pathological phenotype can only be achieved by adequately integrating the myriad of related biological information. Cancer genomics programs like The Cancer Genome Atlas have generated a considerable amount of multi-omics data for multiple cancer types that can be utilized for the analysis. Therefore, the thesis aims to develop computational algorithms that utilize more than one omic data at a time to understand the etiology of cancer. The thesis�s two principal objectives are (1) To identify miRNA-mRNA regulatory modules in cancer and (2) To identify cancer subtypes. The computational objectives associated with these biological objectives are (1) Simultaneous clustering of miRNAs and mRNAs (clustering of features) whose expression is measured across the same set of cancer patients and (2) Clustering of cancer patients (clustering of samples) by integrating multiple levels of biological information coming from different omic platforms. Multi-omics ination and clustering have the potential to uncover subsequent systems-level knowledge but raise biological and computational challenges. The major challenges associated with multi-omics integration and clustering are (a) Selection of informative, appropriate, and meaningful omics (aligned to the biological objective) for the integration task. (b) Capturing the regulatory interactions between the multi-omics layers that can reflect the holistic nature of multi level data. (c) Careful handling of data heterogeneity across the omics having different distributions. (d) The problem of high-dimension low sample size, a situation where the variables significantly outnumber samples, leading to model overfitting. (e) Avoiding the transmission of redundant and noisy information from the individual omics while multi-omics integration. The computational approaches proposed in this thesis address the above issues and integrate multi-omics data for miRNA-mRNA regulatory module identification and cancer subtyping. The approaches designed in this study are based on four paradigms, specifically, Simultaneous clustering, Feature weighting-assisted information fusion, Subspace-based multi-kernel information fusion, and Latent space-based information fusion. The simultaneous clustering algorithm groups co-expressed miRNAs and mRNAs together into a module. An optimization function is designed to simultaneously maximize the relevance between a miRNA and an mRNA and the functional similarity between a module�s mRNAs. The feature weighting-assisted information fusion approach integrates transcriptomics data to identify cancer subtypes. The method assigns a weight to every biomarker prior to data integration and sample clustering. The weights take care of the inherent variance present in each transcriptomics data and are further utilized to calculate sample similarities. The impact of weights on the sample similarity network is observed during sample stratification when homogeneous groups of cancer patients are identified having distinished molecular characteristics. The subspace-based multi-kernel integration approach utilizes two graph-based representations for each omic data to capture the inherent data heterogeneity. It captures the best possible synergism between multiple representations using heuristics. Later, relevance-based integration of the synergistic graphs is performed to combine the multi-omics information and sample clustering. The recursive multi-kernel integration is performed to combine only the relevant and de-noised subspace. Here, relevant subspace refers to that subspace of the matrix that purely encodes the cluster information, which in the case of synergy matrix is its eigenspace corresponding to best eigenvalues. The latent space-based information fusion approach performs early integration of multi-omics data for sample clustering. Dimensionality reduction and simultaneous data integration are performed by learning neural networks in an unsupervised setting. It helps to create an information bottleneck by capturing the non-linear relationships in the data and denoising them simultaneously. The compressed integrated data representation holds the global cluster structure that is explored for sample clustering.Item Islanding and Faults Detection in Utility Grid Integrated With Solar Renewable Energy Source Using Signal Processing and Machine Learning Algorithms(Indian Institute of Technology Jodhpur, 2022-07) Yadav, Sandeep KumarThe interfacing of renewable energy sources (RES) with the utility grid due to the growing demand for clean and cost-effective energy poses new challenges like power quality disturbances, unintentional islanding, change in fault levels, and fault current directions. These unpredictable events pose a significant threat to the continuous supply of loads, the safety of the equipment and personnel involved and also cause considerable economic losses. Hence, the proposed schemes must be able to tackle these challenges and to detect faults and islanding conditions at the earliest. In addition to fault detection and classification, fault location in the distribution system is also a challenging task due to short feeders, complex topology, various laterals, unbalanced operation, and time-varying load profile. Various signal processing techniques such as Wavelet Transform and S-transform, have been employed to extract time-frequency information to detect islanding and fault diagnosis. Empirical Mode Decomposition (EMD) is reported to be adaptive and overcomes the limitations of Wavelet transform (suitable wavelet selection) and S-Transform (non-adaptive selection of Gaussian windows). This thesis proposes high-speed protection algorithms based on Empirical Mode Decomposition of three-phase current signals collected at the substation of a distribution network for detecting islanding and discriminating the same from faults. Fault classification and location have also been accomplished, followed by detection. The three-phase current signals collected at a substation over a moving window are decomposed using the EMD method to extract residues at various levels. These residues are utilized to detect the faults and classify them as LG, LL/LLG, and LLLG (L: line, G: ground). The discrimination between LL and LLG faults is achieved with the help of a neutral current. The first algorithm utilizes the absolute mean (AM) value and Standard deviation (SD) of the first-level residue obtained from EMD to compute fault indices to detect and classify various faults and islanding by comparing with a threshold value within a half cycle. After fault detection and classification, the features of SD and AM from first-level residues are fed to a decision tree (DT) machine-learning algorithm to locate the fault. This algorithm has been successfully tested on IEEE 13 and 34 bus systems with DG penetration in the presence of noise with 20 dB signal to noise ratio (SNR). The second algorithm proposed is based on a combination of EMD and Hilbert Transform (HT), widely known as Hilbert-Huang Transform (HHT), which extracts instantaneous features like instantaneous frequency (IF), instantaneous amplitude (IA), Standard deviation of instantaneous frequency (SDIF), and standard deviation of instantaneous amplitude (SDIA) from the first level residue. A fault index computed based on SDIF is proposed to detect and classify the faults within a quarter cycle by comparing it with a predefined threshold without DG penetration. A machine learning algorithm is proposed to avoid multiple thresholds in the event of DG penetration that requires islanding detection. The instantaneous features are fed to DT to classify faults and islanding. Also, the faulty zone is located using various ML models to evaluate their performance with varying capacities of DG using quarter cycle post-fault data (PFD) in the presence of noise. In third algorithm, image-based fault diagnosis is accomplished by generating unique symmetrical dot patterns (SDP) with the help of monotonic residue after EMD. A novel protection algorithm based on SDP has been proposed with the alienation coefficient of SDPs after a fault and normal conditions as fault index to achieve fault detection and classification. These SDPs, when fed to Convolutional Neural Network (CNN), removed the feature extraction process involved in distribution system fault diagnosis. The proposed algorithms have been successfully tested by varying the type of fault, fault incidence angle, fault resistance, and fault location in the presence of noise. The selectivity of the proposed algorithms has been established by testing with non-faulty transients such as transformer excitation and de-excitation, feeder energization and de-energization, load switching, capacitor switching, and DG tripping in the presence of noise. Thus, the proposed algorithms using a combination of signal processing and machine learning methods can be implemented efficiently for the online monitoring of distribution systems.Item From primary microcephaly-associated CPAP as centriole size/number regulator to microtubulestargeting novel chemotype(Indian Institute of Technology Jodhpur, 2023-07) Singh, PriyankaCentrioles are cylindrical microtubule-based structures, embedded in a proteinaceous matrix called pericentriolar material (PCM). Together, this structure is referred as the centrosome. In animal cells, the centrosomes play a crucial role in cellular functions such as cell division and motility. Abnormalities in centrosome-associated proteins have been linked to human diseases, including cancer and neurodevelopmental disorders. Mutations in the core centriole protein, Centrosomal P4.1-associated protein (CPAP), have been associated with primary microcephaly (MCPH6), a disorder characterized by reduced brain size and cognitive disability. This study focuses on understanding the impact of CPAP mutations on centrosome and spindle organization in primary microcephaly. Specifically, it investigates the effects of two MCPH-associated mutations, E1235V and D1196N, in the CPAP G-box domain. The study reveals that E1235V causes increased centriole length, while D1196N leads to an increase in centriole number. Interestingly, E1235V does not localize at the centriole, whereas D1196N maintains its centriolar localization despite reduced interaction with the upstream centriole protein, STIL, similar to E1235V. This suggests the involvement of an alternate route involving the proximal parent centriole protein, CEP152. Moreover, we demonstrate that centriole abnormalities result in multipolar spindle formation and decreased cell viability. These findings shed light on the importance of regions within CPAP outside the direct microtubule-interacting domains in influencing centriole organization, providing valuable insights into the molecular mechanisms underlying primary microcephaly. The second part of the thesis work explores the development of novel chemical scaffolds for chemotherapeutics. The cell division machinery, comprised of centrosomes and microtubules, is crucially regulated during the cell cycle. Dysregulation of these structures can lead to human diseases, including cancer. Paclitaxel, a microtubule-targeting anticancer drug, has clinical approval but faces challenges due to the development of resistance in many cancer types. Hence, there is a need to identify new chemical scaffolds for designing effective anticancer drugs. In this study, a novel S-aryl dithiocarbamate chemical scaffold is identified as a potent anticancer compound with promising pharmacophore properties. The lead compound exhibits an I*C_{50} of <0.5 µM in lung and cervical cancer cells. It stabilizes microtubules, resulting in p53-p21-dependent cell cycle arrest in the G_{2} / M stage and cellular apoptosis. Interestingly, the lead compound shows comparable docking parameters to paclitaxel in the taxol-binding pocket of ẞ-tubulin. These findings present a promising alternative scaffold that can be further modified to enhance efficacy and potency as an anticancer drug.Item Role of Scene text in Image Semantics(Indian Institute of Technology Jodhpur, 2022-08) Harit, GauravSince the advent of the printing press, text has slowly made inroads into the world we have built for us. The symbolic nature of text allows it to explain ideas more succinctly. Thus scene text content is often naturally occurring in images ( street or storefront images). Further, they are also embedded into images to drive home clear takeaway points (e.g., printed posters, advertisement images). In both cases, though, they bring in crucial contextual information that aids in interpreting such images. However, despite this pervasion of scene text in our everyday images [Dey et al., 2021] and the rich information source they entail, early works in visual understanding tasks like Image Classification, Captioning, and Visual Question Answering (VQA) [Antol et al., 2015] did not leverage the scene text content of images. This can be attributed to the challenges of detecting and recognizing scene text in the wild. However, maturing research in Scene text recognition has improved their ability to read the text in natural images, thus making the scene text content more accessible. This easy accessibility of scene text content, coupled with the recent advances in multimodal architecturesHu et al. [2020], provides a unique opportunity to incorporate scene text into visual understanding tasks. As our first point of the investigation [Dey et al., 2021], we propose to jointly use scene text and visual channels for robust semantic interpretation of images. We not only extract and encode visual and scene text cues but also model their interplay to generate a contextual encoding with rich semantics. The contextual encoding thus generated is applied to retrieval and classification tasks on multimedia images with scene text content, to demonstrate its effectiveness. In the retrieval framework, we augment the contextual semantic representation with scene text cues to mitigate vocabulary misses that may have occurred during the semantic embedding. To deal with irrelevant or erroneous scene text recognition, we apply query-based attention to the text channel. We show that our multi-channel approach, involving contextual semantics and scene text, improves upon the absolute accuracy of the current state-of-the-art methods on Advertisement Images Dataset by 8.9% in the relevant statement retrieval task and by 5% in the topic classification task. Our results confirm our initial hypothesis that scene text plays an essential role in the semantic understanding of images. These results encourage us to extend our framework to more challenging tasks, like Text-VQA Singh et al. [2019a], that explicitly require us to read and reason with the scene text of an image. However, the scene text words come from a long-tailed distribution, giving such tasks zero-shot characteristics. We hypothesize that the zero-shot nature of these tasks can benefit from leveraging external knowledge corresponding to the scene text. The open-ended question answering task of Text-VQA often requires reading and reasoning about rarely seen or completely unseen scene text content of an image. We address this zero-shot nature of the task by proposing the generalized use of external knowledge to augment our understanding of the scene text. We design a framework Dey et al. [2022] to extract, validate, and reason with knowledge using a standard multimodal transformer for vision language understanding tasks. Through empirical evidence and qualitative results, we demonstrate how external knowledge can highlight instance-only cues and thus help deal with training data bias, improve answer entity type correctness, and detect multi-word named entities. We generate results comparable to the state-of-the-art on three publicly available datasets under the constraints of similar upstream Optical Character Recognition (OCR) systems and training data. Through our experiments, we observe that this external knowledge not only provides invaluable information about unseen scene text elements but also augments the understanding of the text in general with detailed verbose descriptions. Our knowledge-enabled model is robust to novel text, predicts answers with improved entity type correctness, and can even recognize multi-word entities. However, the knowledge pipeline is susceptible to erroneous OCR tokens, which can lead to false positives or complete misses. This also explains how our performance on the datasets is correlated with the particular OCR systems used. Our investigation highlights the challenges and benefits of incorporating scene text into image understanding tasks. We validate our various hypotheses through empirical evidence across five different publicly available standard datasets. We conclude with a discussion on the implicit bias in these datasets for scene text, and propose data augmentation and a novel training scheme to deal with it.Item Secrecy Analysis and Performance Improvement of FSO Communication Systems(Indian Institute of Technology Jodhpur, 2023-10) Mathur, AashishOptical wireless communication (OWC) is a promising alternative solution to tackle the issues of spectrum scarcity and traffic congestion. The term OWC is defined as the transmission in an unguided propagation medium using optical carriers in the visible, infrared, and ultraviolet frequency bands. Outdoor terrestrial or free space optical (FSO) communication is one of the categories of OWC, which deals with the data transmission between two fixed points over several kilometers using optical carriers. FSO communication systems have many advantages, such as huge license-free bandwidth, high data rate, low latency, cost-effectiveness, and quick deployability. Despite the aforementioned merits, the performance of FSO systems is limited by atmospheric turbulence (AT), pointing errors (PEs), path loss, geometric loss, and background radiation. Conventionally, FSO systems utilize intensity modulation/direct detection (IM/DD) due to the low cost and ease of implementation; on the other hand, the heterodyne detection (HD) technique has a higher cost and is relatively difficult to implement, but it provides improved communication performance. FSO communication is inherently more secure than radio frequency (RF) communication because the optical beams are more directional than the RF beams, thus FSO communication systems are less subject to eavesdropping/intercepting. However, optical beams can still be intercepted particularly when the eavesdropper is close to the legitimate receiver or lies within the divergence angle. In recent years, the research on secrecy performance analysis has increased significantly. We evaluate the exact closed-form expression of the average secrecy capacity (ASC) and secrecy outage probability (SOP) under the composite effect of the generalized Malaga distributed AT and non-zero boresight PEs in this thesis. Through the detailed asymptotic analysis, it is revealed that the secrecy diversity order depends on the minimum of the main link parameters of the FSO system for the respective detection technique (HD or IM/DD). We incorporate hybrid-automatic repeat request (H-ARQ) in the FSO communication systems to improve their performance and communication link reliability. H-ARQ technique combines strong channel coding with retransmission request protocols to improve FSO system reliability. We derive novel closed-form expressions for the outage probability of the FSO systems under the combined impact of Gamma–Gamma distributed AT and PEs for HD and IM/DD techniques. We compare the FSO system performance for different H-ARQ protocols, such as at least once (ALO), chase combining (CC), and incremental redundancy (INR). Further, we calculate throughput for the FSO systems by utilizing outage probability expressions for the mentioned H-ARQ protocols. We also conduct an extensive asymptotic analysis for different H-ARQ protocols which reveals that the achieved diversity gain is the product of the number of transmission rounds and the minimum of the link parameters for the respective detection technique. To further enhance the FSO system coverage, we consider a mixed dual-hop FSO-RF communication system. The considered dual-hop FSO-RF communication system serves the end user via a decode and forward (DF) relay employing H-ARQ protocols on both hops. The intelligent reflecting surface (IRS) has been utilized on RF links for their merits, such as the capability to provide greater coverage, improved spectrum, and energy efficiency. We derive the outage probability and packet error rate (PER) of the proposed system by considering generalized detection techniques such as HD and IM/DD on the source-to-relay (S−R) link with H-ARQ protocol and IRS having phase error. The inclusion of IRS phase error in our analysis is essential for closely emulating a practical system model. To obtain more fruitful insights into the FSO communication systems, we develop an experimental setup of a 10 Gigabits/second (Gbps) FSO communication system in a laboratory-controlled environment. An AT chamber is designed to introduce the effects of turbulence, fog, and heat onto the transmitted signal. We experimentally evaluate the bit error rate (BER) and the received power profile fluctuations in the presence and absence of AT. Further, we also demonstrate the effect of heat and fog on the received power profile. Additionally, we exemplify the role of cyclic redundancy check (CRC) to mitigate the deteriorating effects of atmospheric conditions on the FSO link. We found that the BER values of approximately 4×10−8 at received powers of -19.29 dBm and -16.98 dBm are achieved for the framed and the unframed data, respectively, and the power gain is around 2.31 dB. This experimental result demonstrates that the BER performance of FSO systems can be improved with the use of CRC bits.Item Education for the Embodied Human: An Enquiry into Human Nature and Education(Indian Institute of Technology Jodhpur, 2023-02) Hari Narayanan VThe present work is a philosophical inquiry concerning the interconnection between theories of human nature and education. It is often argued that the current mainstream education has an underlying dualistic assumption that the mind-body and the human-world are distinct and, therefore, do not value embodied forms of knowing. This dualistic notion creates a rift between learners and their environments, substantially impacting their learning. It also results in an exam-oriented and achievement-based education system that is not conducive to developing children's critical thinking and an exploratory mindset. One major factor that gives rise to this condition is an inadequate understanding of human nature. It is evident that any educational activity presupposes one or another conception of human nature because a particular philosophy of human nature shapes and influences a particular philosophy of education. Therefore, understanding human nature is of paramount importance for designing or transforming education. An examination of several theories of human nature reveals that they are mostly the result of philosophical speculation and have underlying dualistic assumptions. However, recent empirical studies in cognitive science suggest that human beings are fundamentally embodied and embedded in the world. Being embodied means the mind is not separate from the body and the world, but it is dynamically coupled with both. Now, if human beings are fundamentally embodied, then education should also acknowledge this fact in its practices. But even though there is increasing evidence available in support of embodiment, we do not sufficiently appreciate it in our day-to-day lives or in educational discourse. This is the result of various psychological, neurological, and socio-factors. To address this problem, a two-way approach is presented, which is termed as the outer and inner curriculum. The outer curriculum employs an "outside-in" approach, in which pedagogies are designed and imparted as per embodied principles. However, only changing external pedagogies will not help much without realizing our own embodied nature. For this purpose, an inner curriculum is required to make changes "inside out". The inner curriculum fundamentally helps us to realize our own embodied nature, which has got significant salutary effects. Therefore, the inner curriculum is seen as complementary to the outer curriculum. The core content of the inner curriculum is mindfulness meditative practices, which help us to become self-aware of our thoughts and sensations, which in turn helps to embrace our own embodied nature and inextricable relationship with the world. This kind of embodied approach to education, having a focus on both outer and inner curricula, helps to create a more democratic, collaborative, and holistic learning environment, thereby fulfilling the vision of educational thinkers such as John Dewey, Paulo Freire, and Jiddu Krishnamurti.Item Development of Green Multicomponent Reactions, Cascade Reactions and Direct Oxidation: Efficient Strategies for the Synthesis of Biologically Active Organic Scaffolds(Indian Institute of Technology Jodhpur, 2023-11) Erande, Rohan DThe development of green multi-component reactions as an efficient synthetic methodology for the construction of biologically active molecules have received great attention in the last couple of decades. However, organic scaffolds such as 2,3-dihydrofurans and 2,3-dihydrofuro[3,2-c]coumarins (DHFC), despite possessing an extremely wide range of biological activities were yet to be succumb in greener way. Following the nature's footsteps, herein we reported an eco-friendly, inexpensive, and efficient one-pot green multicomponent approach to synthesize trans-2,3-dihydrofuro[3,2-c]coumarins (DHFC) catalyzed by imidazole in water under mild conditions. Applications of the developed catalytic process under a multicomponent strategy in a greener medium revealed the outstanding activity, productivity, and broad functional group tolerance, affording a series of newly designed DHFC in excellent yields. In addition, the biological study that was carried out by the collaborative group demonstrates the ability of the sthesized DHFC derivatives to bind to human serum albumin (HSA). Detailed in silico and in vitro structure-activity analysis has been performed, covering all the bases of this biological investigation. Furthermore, the developed strategy was implemented to synthesize bioactive heterocycles, namely dimedone fused 2,3-dihydrofuran derivatives, under mild conditions with excellent yields, using imidazole and water as green catalyst and solvent, respectively. The synthesized dimedone based 2,3-dihydrofuran derivatives have been found to inhibit SaTR in vitro at low to medium micromolar concentrations. On the other hand, the indole alkaloids are known as an epic family of natural products with structurally diverse architecture and a wide range of biological activities. In line, a BF3.OEt2 catalysed cascade strategy for the synthesis of highly substituted pyrrolo[1,2-a]indole core with high diastereoselectivity has been developed. Further, biological evaluation of synthesized derivatives was reflected in their excellent bioactivity. Further, oxidation of polycyclic aromatic hydrocarbons (PAHs) found to be an important area belongs to the biochemistry, astrochemistry, and chemical industries. In line, we have developed the one-pot oxidation of naphthalene, anthracene, pyrene and substituted PAHs in the presence of H2O2 and newly designed [CuIIL] complex derived from non-toxic transition metal and ligand based redox-active PLY backbone, that provided a route for their detoxification and conversion into industrially important compounds. Furthermore, transforming the alcohols and aldehyde groups to esters via oxidative coupling with alcohols has become an attractive target for organic chemists, due to the significance and omnipresence of ester group in chemistry. Thus, a new-designed V-catalyst [(L2)VIVO](ClO4) was synthesized and utilized for its potential catalytic activity towards direct oxidation of two different functionalities, alcohols and aldehydes to their corresponding esters in one-pot procedure using H2O2 and alcoholic medium. Moreover, cinnamate esters transformed to ester (via C=C bond breaking followed by oxidation of in-situ generated aldehyde) in single-step, which is found to be the first ever report to this end.Item Development of metal oxide based formaldehyde (HCHO) sensors using laser ablated nanoparticles(Indian Institute of Technology Jodhpur, 2023-07) Kumar, Mahesh; Singh, JitendraIn this thesis, first time, we reported a state-of the art method for the synthesis of metal oxide nanoparticles in atmospheric air using laser ablation techniques for the rapid prototyping of formaldehyde (HCHO) gas sensor. Formaldehyde gas is most common indoor air pollutants which causes various adverse human health problems if its limit goes above 0.75 ppm as per OSHA (Occupational Safety and Health Administration (OSHA), USA) guidelines. It is also noticed that some dishonest fish merchants are using formalin solution (formaldehyde gas dissolved in water) to preserve freshly caught fish during their transportation to the fish selling market to prevent the spoilage. So, various health issues have been occurred due to the ingestion of formalin contaminated fish. Thus, we need a miniature, low cost, ultra-low sensitive formaldehyde sensor for the development of smart or IoT enabled portable system for the measurement of formaldehyde gas level in indoor area and as well, their presence in fish. Micro hotplate is an essential part of any metal oxide based gas sensors. Hence, in the first part of the study, co-planner Au microheater based gas sensor platform was fabricated by laser micropatterning using a 355 nm Q-switched solid state laser source. The heat distribution profile of the fabricated micro hotplate was observed via IR thermal imaging camera. Furthermore, the long-term reliability, power versus operating temperature of the microhotplate were systematically studied. In addition with this, heat distribuiton profile of a Nichrome heater based gas sensor platform having a hollow alumina tube on which two gold electrodes had been printed at each end, was also investigated. The next set of analysis, the formaldehyde gas sensing performance was studied using pristine SnO2 and ZnO metal oxide materials. Formaldehyde gas sensing behaviour was studied by depositing thin film of SnO2 layer onto the external surface of alumina tube based gas sensor platform. The sputtered deposited SnO2 thin film sensor exhibited gas response of 1.2 towards 1 ppm of formaldehyde vapor with a response time of ? 32 s and a recovery time of ?72 s at 300°C. Next, to explore the formaldehyde sensing capabilities of nanoparticles, we have synthesized pristine ZnO nanoparticles by scanning a high power laser beam on the top surface of ZnO pellet in open air atmosphere and the laser-ablated ZnO NPs were directly deposited onto the alumina tube based gas sensor platform. The gas-sensing properties of the ZnO NPs has been carefully investigated in the presence of formaldehyde gas molecules. ZnO NPs-based sensor exhibited the response of about 1.8 towards 50 ppm formaldehyde gas at 350°C with response time 25 s and recovery time 12 s. To further enhance the sensitivity and selectivity towards formaldehyde gas, we have fabricated n-ZnO/n-SnO2 n-n heterojunction by combined processes of physical vapor deposition (PVD) by sputtering SnO2 thin film on the alumina tube based gas sensor platform and decorated it with ZnO nanoparticles. After decoratif laser ablated ZnO nanoparticles on thin film SnO2 sensor, it exhibited high response of 20 towards 50 ppm of formaldehyde with quick response (4 s) and recovery time (30 s) at lower operating temperature (250°C) compared to that of pure SnO2. After obtaining good results from the previous investigations with heterojunction, the present research has further been extended. The p-type NiO NPs were synthesized in atmospheric air by laser ablation of cylindrical shaped solid Ni pellet. We have fabricated p-NiO/n-SnO2 p-n heterojunction via decoration of laser ablated NiO nanoparticles over sputtered deposited n-type SnO2 thin film. We have explored the formaldehyde sensing behaviour of NiO/SnO2 sensor and compared with pristine SnO2 senso. The NiO/SnO2 sensor exhibited higher response of about 29.8 towards 50 ppm formaldehyde with fast response and recovery time (3 s and 90 s) at lower operating temperature (about 210°C) with good selectivity. In the last part of the thesis, enhanced formaldehyde sensing mecsm of ZnO/SnO2 and NiO/SnO2 sensors has been described. From the experimental gas sensing performance data of NiO/SnO2 sensors, we have also extracted the various gas sensing parameters such as response time (??res), recovery time (??rec), surface coverage (??), adsorption (Ka) and desorption rate constant (Kd) using Langmuir gas adsorption-desorption model via curve fitting method.