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Active Power Distribution Scheme in a Hybrid AC/DC Microgrid Integrated with Composite Energy Storage Devices
No full textThe growing power requirement and the limited availability of fossil fuels make it necessary to use renewable energy resources (RERs) as a substitute. The penetration of renewable sources in the existing distribution system becomes a big challenge for the safe and predictable operation of the microgrid. In this work, a solar photovoltaic (PV) system is integrated because of its low cost and high efficiency. However, the intermittent characteristics of RESs along with the arbitrary load deviations greatly affect the quality of power supplied to the consumers and the steadiness of the system operation. Hence, it necessitates the inclusion of energy storage systems with both high energy and high power handling capability to coexist in microgrids. Here, by considering the complementary characteristics of supercapacitors with a high power density (500 − 5000 /) and batteries with high energy density (50 − 80 ℎ/), a combination of these two storage devices is used with renewable sources as a composite energy storage devices (CESDs). The purpose of CESD is to lessen the power disparity produced by the intermittency of renewable sources and varying load demands. Optimal utilization of storage devices is very important in microgrid applications as a backup power source to enhance the resiliency and reliability of the system for critical loads. Hence, the power distribution in the composite energy storage system is a major concern and also it remains a challenging issue in conventional techniques. The problem is resolved by implementing an improved mixed droop technique (IMDT) with optimized steady-state along with momentary performances of CESDs in this research. With the proposed technique, the supercapacitor compensates all the fast varying power oscillations appeared in the system, whereas the battery supplies only the average power at steady-state. This control strategy advances the consistency of the system, dynamic restoration of the DC link voltage, and reduces stress of current from the battery units. The microgrid performance is dependent on the parameters of the IMDT, hence proper design guidelines are also defined in this work to get better performance. Also, a robust sliding mode nonlinear controller (SMC) is implemented instead of the conventional PI controller for the switching regulation of the DC/DC bidirectional converters connected across the CESDs. Sliding mode contro is mainly intended to maintain the required performance of the microgrid despite any changes in system parameters or model inaccuracies and any external disturbances. SMC is effective in compensating any disturbances, ensuring that the system remains stable and follows the desired trajectory or maintains its position. Hence, a hybrid control algorithm is developed in this work by combining both IMDT and SMC for the distribution of active power between the battery and supercapacitor units. The inclusion of RESs and energy storage devices in the conventional power grid necessitates rigorous study of the power equilibrium and microgrid stability. Hence, this research work introduces an active power distribution scheme (APDS) for both isolated DC microgrid systems and grid interactive hybrid AC/DC microgrid (GIHM) systems. The power-sharing technique is designed by checking the power disparity between the PV generation and load requirements and the available state of charge () of energy storage units. The APDS helps to utilize the PV and energy storage devices optimally by reducing the utility grid dependency and also maintains the of the storage devices within the safe limit to enhance their lifetime. This power-sharing scheme provides improved performance by maintaining the unity power factor grid operation, faster restoration of DC link voltage, and reduced harmonic. Also, the small-signal modeling of the system using a double-loop control scheme is presented to analyse the stability of the proposed system and to obtain the accurate estimation of the PI parameters by calculating the proper bandwidth and phase margin of both current and voltage loops in the system. The obtained open-loop transfer functions of each loop are provided with their individual Bode response. Also, a PV-integrated electric vehicle charging microgrid (EVCM) along with combined storage systems and a conventional single-phase utility grid is proposed in this research to facilitate both grid-to vehicle (G2V) and vehicle-to-grid (V2G) functions. The bidirectional power flow of the EV supports the microgrid in peak load hours and during low PV generation periods. For charging of EV battery (EVB), an innovative dynamic charging current-constant voltage (DCC-CV) method is planned to minimize the transient in the system and to avoid the overcharging of EVB. For the discharging of EVB, a fixed power supply concept is employed. To estimate the performance and feasibility of the designed APDS in isolated DC microgrid, hybrid AC/DC microgrid, and EVCM, the respective system models are tested in MATLAB/Simulink, developed prototype in the laboratory using DS1103, and OPAL- RT simulator with an extensive analysis of obtained results
Wavelets and related Functions on Cantor Dyadic Group and Vilenkin group
No full textThe purpose of our work is to study properties of orthonormal wavelets, and the related concepts of frame wavelets and Riesz wavelets, for both Cantor dyadic group and Vilenkin group. At first, we have given the theory of wavelet sets. We have characterized wavelet sets for Cantor dyadic group. All the wavelets originating from wavelet sets are not necessarily associated with a multiresolution analysis (MRA). We have also established relation between wavelets obtained from MRA and wavelets determined by wavelet sets. Scaling and generalized scaling sets provide wavelet sets and hence wavelets. We have given characterization of scaling sets and its generalized version along with relevant examples for Cantor dyadic group. Further, we have studied properties of generalized scaling sets, and relation between wavelet sets and generalized scaling sets. Results related to these sets are also given for the Vilenkin group. Frame multiresolution analysis (FMRA) is an extension of the concept of MRA, and can be used to generate frames. By using properties of shift invariant spaces, relation between FMRA and MRA is established. Further, in a particular case, conditions are given for the existence of frame wavelets associated with FMRA. For Cantor dyadic group generalizations of lowpass filters and scaling functions are introduced, and existence of generalized Parseval frame wavelets is proved. At the end, association between MRA and Riesz wavelets is given along with the construction of frame and Riesz multiwavelets
Principle and Topology Synthesis of Integrated Single-input Multi-output and Multi-input Single-output DC-DC Converters
No full textRenewable energy sources (RESs) such as Photovoltaic (PV) and wind dominate total renewable power generation. Since both sources are intermittent in nature, effective solutions are needed for reliable operation. However, due to the erratic nature of RESs, a battery and grid are always incorporated with the RES system to maintain an uninterruptable power supply to load and improve system reliability. Conventionally, separate DC-DC converters are connected among RESs and batteries to the DC bus and load. However, using several SISO converters increases the overall system component count, size, and implementation cost. Therefore, this work has introduced a topology synthesis technique to reduce the costs of synthesizing an integrated three-port converter with a reduced component count. The principle of topology synthesis states that an integrated three-port converter can be easily developed from a conventional SISO converter by replacing a diode with a basic cell inclusive of an additional bidirectional port. This three-port converter is compared with the conventional strategy, which employs two separate DC-DC Cuk converters to generate dual-output voltages. The three-port converter can operate in three operating modes: single input dual output (SIDO), dual input single output (DISO), and SISO, depending on the power transfer among the three ports. The MIMO converter controller structure has multiple interacting control loops to maintain the power balance between source and load demand. With multiple control loops, it is challenging to design closed-loop control algorithm for individual output ports without a proper decoupling method. Therefore, this thesis presents a detailed approach by utilizing the state-space averaging method to obtain the converter model under different modes of operation. Then a decoupling network is introduced to allow separate controller designs. The proposed control structure is composed of a decoupling network to address the inevitable cross-coupling effect of multiport converters present due to various interacting control loops. In addition, a PI-Lead compensator is designed to achieve improved steady-state and transient performance in each operating mode of the three-port Cuk Converter (TPCC). Furthermore, an autonomous mode selection (AMS) technique is proposed to achieve a seamless transition between different operating modes. The AMS technique automatically shifts the operating modes of TPCC by comparing the availability of instantaneous power at each port to maintain an uninterruptable power supply to the load. The proposed TPCC uses to interface solar, EV and utility grid. This system comprises two major parts. The first one is TPCC, which is connected to Solar PV generation, Electric vehicles and DC links. The second one is the secondary side of the DC link, which is connected to the utility grid with the help of a single-phase voltage source converter (VSC). This VSC is a bidirectional converter allowing power flow between the grid and TPCC. An ANF-based phase error minimization technique is implemented to improve system reliability during grid synchronization. Moreover, Power sharing among solar, EV and grid effectively handles both grid-connected and islanded modes. The TPCC controller controls the charging of the EV from PV and the grid. Finally, the feasibility and effectiveness of the proposed control algorithm are validated with the help of a laboratory prototype
Roles of KDM5A and MLLs in Modulating Cellular Processes with Respect to Reversible H3K4me3 Status
No full textDifferential expression of genes involved in certain processes is a collaborative outcome of crosstalk between signalling molecules and epigenetic modifiers, which together dictate the regulation of genes in response to environmental stimuli. Epigenetic mechanisms involve changes in gene expression by modulating the chromatin configuration. Epigenetic modifiers that set in a euchromatin led to gene activation and those that participate in heterochromatinization will repress gene expression. These changes in nucleosome architecture are due to addition or removal of small chemical groups which either increase the affinity of DNA and histones or weaken their interactions. Here, in this study, we attempt to understand the dynamics of one such modification – the H3K4me3, which is an activation signal. The expression of its writer – MLL and eraser – KDM5A protein, was varied using siRNA and overexpression constructs. To strengthen our study, we utilized both knockdown and transient overexpression approaches to decode the exact mechanism by which H3K4me3 modification regulates different cellular processes. EMT is a multistage process and many transcriptional factors and co-factors play a role in regulating this process. MLLs and KDM5A are functionally antagonistic proteins as one acts as writer and the other erases the active chromatin mark, i.e., H3K4me3. KDM5A promotes EMT by occupying promoters of both epithelial and mesenchymal markers. Through this work, we show that when bound to E-cadherin promoter, KDM5A acts as a classical repressor by demethylating H3K4me3, but on mesenchymal marker promoters, it acts as a transcriptional activator by inhibiting the activity of HDACs and increasing H3K18ac. Further we report that when enzymatically inactive, KDM5A occupancy on E-cadherin enhances either MLL1 or MLL2 by physically interacting with them and that signalling pathways like ITG-FAK may regulate the enzymatic activity of KDM5A by phosphorylation. We further show that KDM5A is a part of COMPASS complex as it interacts with MLL1, MLL2 and WDR5. Metabolic plasticity is a key for tumor survival in the dynamic microenvironment, and this process involves shifting gene expression from a certain phenotype to one that supports better adaptability. Epigenetic regulation is one way of attaining this transformation. Here, we investigated if glucose metabolic gene regulation is dependent on KDM5A and MLL1, and if targeting the H3K4me3 would help in modulating the resilience of cancer cells. We present that KDM5A modulates most of the metabolic genes in a demethylase dependent manner as assesses by H3K4me3 occupancy on G6PD and catalase promoters. Chemo-preventive active compounds found in medicinal plants were shown to epigenetically alter cancer cells without affecting normal cells, thus we tested if phytochemicals rewire the epigenetic state of cancers cells to regulate metabolic genes. From our investigation, we understood that curcumin could enhance KDM5A and reduce MLL2 expression in both cancer cell lines (HeLa and PC3) leading to a state of silencing on metabolism related genes. In HaCaT cells, curcumin treatment reduced KDM5A and enhanced MLL2 thus setting a state of activation. When HeLa cells were treated with curcumin, KDM5A mediated reduction of TCA, ATP, PPP related genes was noted. Also, KDM5A mediated increase in ROS mediated apoptotic cell death was observed in HeLa, but HaCaT cells remained unaffected. Thus, we could conclude that targeting KDM5A/MLLs expression would indeed transpire cancer cells metabolism and help in sensitizing cancer cells to ROS dependent apoptotic cell death. Cell cycle progression is regulated by many extracellular stimuli and intracellular signaling, all of which converge in the nucleus. Inside the nucleus, interaction between different epigenetic modifiers and transcription factors regulate the expression of proteins involved in cell cycle control. Along with the cyclin-CDK complexes that direct the cell passage through different stages of cell cycle, the chromatin configuration also dictates the progression by monitoring the attainment of correct chromatin compaction. Here, in this study we analyzed how modulation of H3K4me3 by MLL1 and KDM5A affect cell cycle progression. Slow and fast cycling cell lines exhibited diverse mechanisms of regulation, from our in-silico screening, we understood that the expression of the MAPK effector – RAS controls the activity of KDM5A and MLL proteins to balance H3K4me3 throughout cell cycle. In fast cycling cell lines like HeLa and HaCaT, which are characterized by high RAS expression, we understand that KDM5A is active and MLL is inactive, so when KDM5A is overexpressed, it leads to an S-phase arrest due to reduced global H3K4me3 associated heterochromatinization. In contrary to this, slow cycling, low RAS expressing PC3 cell line exhibits inactive KDM5A and active MLLs, thus leading to enhanced H3K4me3 mediated loose chromatin configuration that blocks cell cycle at G2/M phase. To confirm that KDM5A/MLL catalyzed changes in global H3K4me3 was downstream effect of growth factor (GF) signaling mediated regulation of their enzyme activity, we performed KDM5A overexpression in serum deprived HeLa cells. In these conditions, we observed a G2/M arrest instead of S-phase block (as observed in normal cultured cells), proving that absence of GF mediated signaling led to inactive KDM5A and active MLLs. Further, we also tested if transient overexpression of RAS in PC3 cells could activate KDM5A thereby leading to an S phase arrest, so we overexpressed RAS and KDM5A together and noted an S-phase block instead of G2/M arrest as observed in KDM5A overexpressing PC3 cells. Concluding the study, as KDM5A is downregulated in cervical and prostate cancers, mechanisms that enhance its expression would lead to cell cycle arrest and metabolic rewiring which ultimately aid in targeting the hallmarks of cancer – i.e., high metastatic, proliferative, and metabolic adaptability phenotypes
Meshless Computational Techniques for Solving Fractional Partial Differential Equations Arising in Certain Physical Systems
No full textStarting from fluids flow in nature, from waves and winds to blood and lava to the diffusion in a tokamak, partial differential equations (PDEs) describe almost every nonlinear phenomenon in the real world. However, the physical behavior of many scientific processes, such as anomalous diffusion, fluid dynamics, plasma physics, mechanics, and chemical kinetics, is better characterized using a non-integer order dynamic model based on fractional calculus. Solving fractional PDEs (FPDEs) is crucial to enhance the understanding of these processes. In this dissertation, meshless computational techniques are developed to solve the FPDEs with applications in shallow water waves, plasma physics, nonlinear optics, fluid mechanics, and chemotaxis. Methods based on radial basis functions (RBFs) are emphasized due to their higher accuracy, simpler extension to higher dimensions, and ability to deal with complex geometries. This dissertation mainly implements Kansa’s global RBF and local RBF partition of unity (LRBF-PU) techniques to simulate FPDEs. In some cases, analytical approaches, such as the Kudryashov method and the tanh method, have been used to obtain explicit solutions for comparison with the numerical results. The Kansa RBF approach has been applied to solve the fractional Gilson Pickering equation and fractional Schamel–KdV equation with applications in plasma physics and the fractional Newell–Whitehead–Segel equation with applications to binary fluid mixtures. Also, the fractional Dullin–Gottwald–Holm equation, fractional coupled KdV–mKdV system, fractional Oskolkov–Benjamin–Bona–Mahony–Burgers equation, and fractional Ito equation describing surface waves in shallow water have been numerically solved. Higher dimensional FPDEs in mathematical physics: fractional Nizhnik–Novikov–Veselov equations and fractional modified Konopelchenko Dubrovsky equations are also investigated numerically. Moreover, the LRBF-PU method has been employed to solve the fractional Benjamin–Ono equation describing long internal waves in deep stratified fluids and the fractional Keller–Segel model for chemotaxis. The stability and convergence of the numerical schemes are theoretically established, and numerical experiments are performed. Numerical simulations and graphical comparisons manifest that the proposed methods are promising in handling FPDEs. Also, the findings are helpful in understanding various physical systems occurring in the real world
Studies on the Electrocatalytic Activity, Electrical Conductivity, and Oxygen Transport Properties of La0.5Sr0.5Co0.8Fe0.2-xBxO3- [B = Cu, Ni, & Al; x = 0 – 0.2] Perovskite Oxides
No full textA series of oxygen-deficient Co-rich La0.5Sr0.5Co0.8Fe0.2-xBxO3-δ (B = Cu, Ni, & Al: x = 0 - 0.2) perovskite oxides were synthesized and systematically characterized to study the electrocatalytic activity, electrical conductivity, and oxygen transport properties. The characterization focused on crystal structure, oxygen non-stoichiometry, surface morphology, oxygen evolution reaction (OER), and electrical transport behaviour. XRD study revealed that all studied powder oxides crystallized in a single phasic cubic structure. B-site cation substitution enhanced oxygen non-stoichiometry (δ) in the studied oxides. The change of surface oxygen vacancies and oxidation state of the B-site with substitution favours hand in hand with the weighty enrichment of OER activity, electrical conductivity, and oxygen transport properties The electrochemical study of La0.5Sr0.5Co0.8Fe0.2-xCuxO3-δ (x = 0 - 0.2) perovskite oxides using KOH electrolyte indicated a decrease in OER overpotential and the Tafel slope with increasing Cu substitution level which is associated with an increase in the mass and specific activity. The study confirms the attainment of the lowest OER overpotential and the Tafel slope of 500 mV and 60.5 mV dec-1 for La0.5Sr0.5Co0.8Cu0.2O3-δ. The enhancement in electrocatalytic activity is correlated to the increase in oxygen non-stoichiometry of the oxides with increasing substitution levels. The study predicts La0.5Sr0.5Co0.8Cu0.2O3-δ may have potential as an OER electrocatalyst for water-splitting applications. The high-temperature electrical transport behavior study on the dense sample indicated an enhancement of electrical conductivity, oxygen diffusion coefficient (Dchem), and surface charge transfer coefficient (Kchem) with increasing Cu-substitution levels. Enhancement in electrical transport characteristics is correlated to the defects in the sample and grain size. Among the investigated oxides, the highest conductivity value was observed for the La0.5Sr0.5Co0.8Cu0.2O3-δ oxide, which is near about 1250 S cm-1. The La0.5Sr0.5Co0.8Cu0.2O3-δ oxide was found to show superior Dchem (1.1×10-4 cm2 s-1) and Kchem (8.5×10-5 cm s-1) values at 900 ℃ compared to the other compositions. Further, an inclusive study focused on La0.5Sr0.5Co0.8Fe0.2-xNixO3-δ (x = 0 - 0.2) perovskite oxides investigate their electrocatalytic activity, electrical conductivity, Dchem, and Kchem. The electrocatalytic activity of the catalysts in an alkaline solution for the OER was evaluated. The results showed that increasing the Ni-substitution level reduced the OER overpotential and the Tafel slope. The observed behaviour is associated with an increase in mass and specific activity. Significantly, the La0.5Sr0.5Co0.8Ni0.2O3-δ oxide displayed a lower overpotential and the Tafel slope of 508 mV and 54.9 mV dec-1 among the studied oxides. This result was attributed to the increased oxygen non-stoichiometry, which generated more active sites for the electrocatalyst. Furthermore, a study of the electrical transport behaviour of the studied oxides revealed an increase in electrical conductivity, Dchem, and Kchem with increasing Ni-substitution levels. The enrichment in electrical transport properties can be ascribed to defects within the oxide and grain size variation. The La0.5Sr0.5Co0.8Ni0.2O3-δ oxide exhibited the highest conductivity value of 1595 S cm-1 among the studied oxides. The La0.5Sr0.5Co0.8Ni0.2O3-δ oxide outperformed the other oxides in terms of Dchem (1.50 × 10-4 cm2 s-1) and Kchem (2.34 × 10-5 cm s-1) values at 900 °C. Similarly, the electrocatalytic activity, electrical conductivity, Dchem, and Kchem of La0.5Sr0.5Co0.8Fe0.2 xAlxO3-δ (x = 0 - 0.2) perovskite oxides were studied thoroughly. The electrocatalytic activity of La0.5Sr0.5Co0.8Fe0.2-xAlxO3-δ perovskite oxides with KOH electrolyte reduced OER verpotential and the Tafel slope. Moreover, the Al substituted level increased, which enhanced the mass and specific activity. A lower overpotential and the Tafel slope of 490 mV and 50.6 mV dec-1 are displayed by the La0.5Sr0.5Co0.8Fe0.1Al0.1O3-δ electrocatalyst than all other investigated oxides. The improved activity is likely ascribed to the combination of oxygen non-stoichiometry and larger surface area, which increases the active sites of the electrocatalyst for OER. The electrical transport properties of the prepared oxides were studied, and it was found that electrical conductivity and oxygen transport parameters enhanced with increasing Al-substitution levels. The electrical conductivity and oxygen transport parameters, specifically Dchem and Kchem depend strongly on the oxygen non-stoichiometry and change in grain size in the samples. The La0.5Sr0.5Co0.8Fe0.1Al0.1O3-δ oxide exhibited the lowest conductivity value of 690 S cm-1. On the other hand, La0.5Sr0.5Co0.8Fe0.1Al0.1O3-δ oxide showed greater Dchem (5.5×10-5 cm2 s-1) and Kchem (2.32×10-5 cm s-1) value among the studied oxides at 900 °C
Vehicular Mobility Analysis Leveraging Historical Spatio - Temporal Data
No full textThe intelligent and efficient urban transportation system of a country is considered a mark of its progress. It plays a backbone role in a country’s development by facilitating trade between regions, reducing travel time costs, and improving accessibility. A gradual increase in vehicles due to the population explosion engenders several issues in the urban transportation system, such as traffic congestion, pollution, and integration among different modes of transportation. To address these issues, analyzing vehicular mobility becomes an essential aspect of understanding and improving the transportation system. Vehicular mobility analysis involves collecting, processing, and analyzing large datasets related to various aspects of transportation systems to identify patterns and trends in data. Many techniques are developed to analyze vehicular mobility using various data sources from domains, including mobile phone data, taxi trajectories data, and social media data. The insufficiency of data mining techniques for handling and processing mobility data, the lack of integrating heterogeneous data, and the lack of an intelligent transportation system are a few important issues that make vehicular mobility analysis challenging in many scenarios. The vehicular mobility analysis broadly involves data modeling and data analysis. Five major contributions are made under these sub-phases in this thesis to address the issue of the lack of data mining techniques for handling, processing, and analyzing trajectory datasets, the integration of heterogeneous data, and the lack of intelligent systems in vehicular mobility analysis. The data modeling phase ensures an efficient representation of the trajectory data for accurate analysis and effective decision-making in vehicular mobility analysis. In the first contribution of this thesis, a new segmentation method is proposed using bearing measurement for trajectory data. The proposed segmentation eliminates multiple waypoints localized over a straight segment(road) to represent it efficiently. The data analysis phase of vehicular mobility analysis involves examining and interpreting the preprocessed data to gain insights into vehicle movement patterns, behaviors, and characteristics in a given area. In this direction, the second contribution proposes an evolutionary multi-objective based clustering algorithm called CLUSTMOSA in the first chapter of the thesis. It is proposed to group similar trajectories, exploiting the proposed segmentation technique for traffic monitoring and analysis. The proposed segmentation technique is further utilized in various data analysis tasks in other chapters also. The third contribution of this thesis proposes another data analysis task, which involves identifying the modes of transportation. It is helpful to extract information on travel time on various routes using different modes. In the proposed work, various GPS point-level characteristics, such as speed, acceleration/deceleration, jerk, and bearing angle, along with a generative model, are exploited for detecting modes of transportation. Another vital task in the data analysis phase is outlier detection, which is explored as the fourth contribution in this thesis. In this thesis, outlier detection is explored using supervised and unsupervised ways. The classification-based anomaly detection is proposed using one-shot learning with a temporal feature-based Siamese capsule network for the GPS trajectory dataset. The temporal feature is extracted using a recurrence plot of chaos theory, and the Siamese capsule network is applied for outlier detection in trajectory. It detects with limited labeled trajectory data. Although the proposed supervised method is capable of detecting outliers efficiently, it has a limitation in using labeled data. Therefore, a spatial-temporal aware variational graph auto-encoder (ST-VGAE) neural network is proposed in the unsupervised category. The proposed method involves encoding the spatial-temporal characteristics of vehicle trajectories into a graph structure to capture the dynamics of trajectories. The proposed approach utilizes the power of graph convolutional networks (GCN) and variational autoencoders (VAEs) to seize the spatial and temporal dependencies for identifying outliers in GPS trajectories without any labeled data. Further, vehicle mobility analysis plays a significant role in developing various applications related to transportation systems. The fifth contribution of this thesis proposes a framework that intelligently identifies accidental hotspots, profiles driving paths, and recommends safer driving locations. It analyzes traffic scenarios using crowd-sourced data from X (formerly (2006–23) Twitter) and employs aspect-based keyword generation to enhance the dataset. The framework mines potential hotspots from Tweets and uses the BERT-BiLSTM model for sentiment analysis on accident-related tweets of accidents in a location. It conducts probabilistic modeling to evaluate the risk at each accident hotspot, considering factors such as the intensity of opinions in the tweets, historical accident data, and GPS data characteristics. A general recommendation framework is introduced to suggest the alertness required for a driver while passing through the hotspot or nearby regions. The performances of the proposed techniques are evaluated using multiple performance metrics and datasets of GPS trajectory data. The proposed techniques perform better against various state-of-the-art methods, and experimental results favor incorporating them into the urban transportation system
Development of Functionalized Coatings on Ti6Al4V through Surface Modification to Enhance the Corrosion Resistance and Antibacterial Activity
No full textTitanium alloy-based implants are among the most widely used biomaterials in orthopedic and dental applications. Many researchers created various surface structures using surface modification methods to improve the interaction of biomaterial surfaces with tissues. Still, the utilization of implantable metals presents several significant challenges that need to be addressed such as corrosion resistance, antibacterial activity, and bone-implant interaction. Biomedical metallic materials, generally corrode and the ions released from their surfaces are toxic and allergenic to tissues. Implant loosening is a condition that is caused by the wear particles released into body fluid from an implant, which evokes undesired immune responses and inflammatory responses resulting in osteolysis in the bone implant interface. As a result, good corrosion resistance is required to achieve satisfactory osseointegration and inflammatory responses. Bacterial infection remains a major impediment to the utility of medical implants. Implants related to bacterial infections involve multiple surgical procedures; removal of the implant, continuous use of antibiotics, and patient rehabilitation. Coating is an effective method that can be used to enhance the biological, antibacterial, and electrochemical properties of orthopedic and percutaneous implants. Keeping this in view, the present research work aims to enhance the corrosion property and antibacterial ability of Ti6Al4V through surface modification and coating. The primary focus of this research was to create the TiO2 (titanium dioxide) highly ordered nanotube arrays on a Ti6Al4V surface to improve surface roughness, antibacterial activity, and biocompatibility for its use in biomedical applications. In this approach, the anodic oxidation process was carried out in the organic bath solution, which is composed of ethylene glycol, NH4F, and ultrapure water. The process was carried out at a constant voltage of 30 V under different anodic oxidation time durations of 3 h, 4 h, and 5 h. Surface roughness of polished Ti6Al4V, TiO2 30 V 3 h, TiO2 30 V 4 h, and TiO2 30 V 5 h are 2.77 nm, 16.92 nm, 19.75 nm, and 22.01 nm respectively. The early-stage assessment of the antimicrobial efficacy of oxidized specimens was conducted quantitatively against Bacillus subtilis and Escherichia coli after a 24 h period of growth. MG-63 human osteoblast-like cells were employed to investigate cell studies. Cell viability on various surfaces was assessed through 3-(4,5- dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and adhesion assays, demonstrating an enhanced in vitro response to crystalline nanotubes. Overall, this work demonstrates the importance of using multifunctional TiO2 nanotubes to provide a synergistic impact on antibiofilm, antibacterial, and enhanced osseointegration. Furthermore, the investigation introduces a novel approach involving a chitosan-coated Ag-loaded TiO2 nanotubular surface, specifically designed for medical implant applications. In the first phase, Ag-loaded TiO2 nanotubular surfaces with different weight percentages of silver were fabricated at a constant voltage of 2 V under varied time durations of 1 min, 2 min, and 3 min. In the second phase, cathodic electrophoretic deposition (EPD) was used to coat the samples with chitosan by applying 10 V for 5 min as a constant process parameter for coating all the samples. The composition and morphology features of in-house fabricated chitosan- coated Ag-loaded TiO2 nanotubular surfaces were studied by different techniques. Corrosion resistance of the functionalized coated samples was assessed through open circuit potential (OCP), potentiodynamic polarization (PDP), and electrochemical impedance spectroscopy (EIS) techniques. The results evidenced that chitosan-coated Ag-loaded (2 V 2 min) TiO2 nanotubular surface (TNT-Ag2.2/Ch) showed the best performance as a coating system when compared to an uncoated surface. Overall, the TNT-Ag2.2/Ch coated sample showed 5 times better results when compared with icorr values. The biological studies also suggested the TNT- Ag2.2/Ch sample has better antibacterial activity and biocompatibility compared to the other samples. Additionally, the research introduces a copper to incorporate into the TiO2 nanotubular surface. In this, Cu-loaded TiO2 nanotubular surfaces with different weight percentages of copper were fabricated at a constant voltage of 2 V under varied time durations of 30 s, 60 s, and 90 s through electrochemical deposition (ECD). Then chitosan was deposited over the Cu-loaded TiO2 nanotubular surfaces through cathodic electrophoretic deposition (EPD) by applying 10 V for 5 min as a constant process parameter for coating all the samples. The structural and corrosion properties are characterized by various techniques. The scanning electron microscope (SEM) and an energy-dispersive X-ray spectrometer (EDXS) characterizations suggest that the deposition of the copper amount is elevated with the extension of the coating duration. The contact angle measurements confirmed the hydrophilic nature of all working samples. Contact angle values for polished Ti6Al4V, TiO2 30 V 4 h, TNT-Cu2/30/Ch, TNT-Cu2/60/Ch, and TNT-Cu2/90/Ch were 61.63°, 18.48°, 76.58°, 73.95°, and 68.30°, respectively. Corrosion rates, as determined by PDP curves, The TNT-Cu2/90/Ch sample exhibited a remarkably low corrosion rate of 0.0611 mm per year and a high corrosion protection efficiency of 79.81%. The biological studies also suggested the TNT-Cu2/90/Ch sample has better antibacterial activity and biocompatibility compared to the other samples. Finally, comparative studies are carried out to suggest the overall better anticorrosive and antibacterial surface among all the treated surface samples the corrosion and antibacterial studies are conducted. The samples polished Ti6Al4V, TiO2 30 V 4 h, TNT-Ag2.2/Ch, and TNT-Cu2/90/Ch are analyzed to optimize the best anticorrosive and antibacterial activity surface. The results evidenced that the TNT-Ag2.2/Ch sample showed better corrosion resistance and antibacterial activities
Inference on Powers of Scale Parameters under Common Parameter Setup
No full textThe thesis deals with the problems of point estimation, interval estimation and hypothesis testing on the powers of scale parameters for normal and exponential model setups with a common parameter assumption. In the case of point estimation, some decision-theoretic results are derived. Further, the problems of interval estimation and hypothesis testing about the powers of scale parameters are also addressed. Chapter 1 introduces the model problem and discusses in detail the related literature. Further, the summary of the results obtained in the thesis is also discussed. In Chapter 2, we provide some basic definitions, fundamental results, and methodologies on point estimation, interval estimation, and hypothesis testing problems that help to frame the rest of the chapters. In Chapter 3, the problems of inference on the powers of scale parameters have been considered when samples are available from two normal populations with a common mean. In particular, we derived the maximum likelihood estimators (MLEs) and several plug-in estimators using some of the popular estimators of the common mean. A sufficient condition for improving affine equivariant estimators using the quadratic loss function is derived. Moreover, we propose several interval estimators, such as the asymptotic confidence interval, bootstrap confidence intervals, highest posterior density intervals, and intervals based on generalized pivot variables. Further, several test procedures are derived, such as the likelihood ratio test, a parametric bootstrap approach test, two computational approach tests, and tests based on the generalized p-value method. A simulation study has been conducted to assess and compare the performances of all the suggested intervals in terms of average length, coverage probability, and a new measure called - the probability coverage density. The test procedures are compared in terms of their sizes and powers. Real-life examples have been considered to demonstrate the potential applicability of all the suggested inferential procedures. In Chapter 4, we consider the model discussed in Chapter 3 and aim to estimate the powers of scale parameters when they follow certain simple ordering. Maximum-likelihood estimators and several plug-in type estimators using some popular estimators of the common mean have been proposed. Sufficient conditions for improving equivariant estimators for the powers of the scale parameters under order restriction have been derived. Consequently, several improved estimators have been proposed. A numerical comparison among all the proposed estimators in the special cases (c = 0.5 and c = 1) has been made in terms of risk values using the quadratic loss function, and recommendations are given for the use of the estimators. Finally, a real-life example has been considered to show the potential application of the model problem. In Chapter 5, we discuss the problems of interval estimation and hypothesis testing on the powers of the ratio of scale parameters for two normal populations with a common mean. We derive several confidence intervals, such as the asymptotic confidence interval, bootstrap confidence interval (bootstrap-p, bootstrap-t), and the generalized intervals. The generalized confidence intervals are constructed utilizing some of the existing estimators of the common mean. We discuss several test methods for hypothesis testing, such as the computational approach test, the asymptotic likelihood ratio test, the parametric bootstrap likelihood ratio test, and tests based on the generalized p-value approach. Numerical comparisons have been made to compare all the suggested confidence intervals and test procedures. Chapter 6 addresses the problems of point estimation, interval estimation, and hypothesis testing on the powers of scale parameters for two exponential populations with a common location. In the case of point estimation, various point estimators are derived, such as the maximum likelihood estimator (MLE), the uniform minimum variance unbiased estimator (UMVUE), and two plug-in estimators using modified MLE and the UMVUE of the common location parameter. An Inadmissibility result is proved for the class of affine equivariant estimators. In the realm of interval estimation, several approaches are discussed, such as approximate intervals utilizing the asymptotic normality of MLE, bootstrap intervals, and intervals using the generalized variable method. Several hypothesis testing procedures are developed, namely, the parametric bootstrap likelihood ratio test (PBLRT), computational approach tests (CAT), and tests based on the generalized p-value approach. Simulation studies are conducted to compare the performances of point estimators, interval estimators and test procedures. The chapter concludes with a real-life application. In Chapter 7, we consider the model discussed in Chapter 6 and estimate the powers of scale parameters under order restriction. The chapter introduces several classical estimators, such as the maximum likelihood estimators, plug-in type restricted maximum likelihood estimators, and uniform minimum variance unbiased estimators. Sufficient conditions for constructing improved estimators have been derived under the scale and affine group of transformations. Consequently, several improved estimators for the powers of the scale parameters under order restriction have been proposed. A simulation study has been conducted using the quadratic loss function to compare these estimators in terms of risk values, and recommendations are given for the use of the estimators based on our simulation study. Chapter 8 discusses inference about the powers of the common scale parameter when samples are available from two exponential populations with different location parameters. It mainly focuses on hypothesis testing and interval estimation procedures. A parametric likelihood ratio test is proposed using artificial bootstrap samples to test the null hypothesis against an appropriate alternative. Further, the study suggests two computational approach tests and several generalized test procedures to test the hypothesis. Moreover, the chapter presents various interval estimation techniques for the powers of the common scale parameter. These include bootstrap intervals, the highest posterior density interval, and certain generalized intervals. A comprehensive simulation study is conducted to assess and compare the performance of all the proposed tests and intervals. Finally, the practical applicability of the proposed model problem is illustrated through real-life examples
Unconventional Umpolung of Bromocations in the Accelerated Organocatalytic Dibromination of C⚌C/C≡C Bonds Alongside Kinetic Studies to Establish the Structure-Reactivity Relationship of C⚌C Bonds
No full textChapter 1. A Short Review on Umpolung Strategy: Advances in new chemical bond Formation This chapter gives an overview of umpolung activity of carbon atoms alongwith rarely reported polarity reversal of halogens. Additionally, it gives concise information about organocatalytic dibromination of C—C unsaturated bonds. Chapter 2. Study Towards Organocatalyzed Umpolung of Bromocation Species An elaborate investigation into the umpolung of the never reported bromocationic source has been addressed. In this chapter a detailed study of the interaction of various halogen sources with amine catalyst has been discussed. Furthermore, the pole reversal of the bromocations has been well supported by the experimental and computational evidences. Chapter 3. Accelerated Organocatalytic Dibromination of Unsaturated C-C bonds In this chapter, the elaborated protocol paved the way for the direct syntheses of the dibromo compounds using the polarity reversal technique, which was achieved tactically in-situ and catalytically by employing simple amine organocatalysts. This environment benign methodology would be an alternate for the age old methods of dibromination. Chapter 4. Structure-Reactivity relationship of olefins as Electrophiles and Nucleophiles: Factors Influencing In this short study we have shown real-time experiments of how the reactivity of the olefins varies when the electron density over the olefinic bond is varied. Also, it has been showcased how the planar orientation of the olefin could nullify these substitution effects. Chapter 5. Effort Towards Synthesis of Chiral N-Halosuccinimides: Potential Reagents for Asymmetric Cohalogenation Transformations In this chapter, an effort towards synthesis of chiral NBS was achieved until the N-protected imide with good to excellent yields. Although there are some challenges in the deprotection of the N-protected imides, but optimization of the deprotection is currently undergoing in our laboratory. Additionally, a successful mimicking synthetic procedure has been developed for the bromination of imides to N-bromo imides. Chapter 6. Conclusion and Future Scope In the last chapter, the present work's overall summary and future scopes have been Described