Abstract

Metallic and polymeric nanomaterials have been at the forefront of variousstudies and applications for a long time. Development of new, greener, fast, scalable, and controlled synthesis methods, understanding their structures and properties, and exploration of new uses and futuristic applications of these nanomaterials have been the major goals of the researchers recently. The thesis work involves the studies of selected nanoparticle systems of the metal,gold and a conducting polymer (CP), polypyrrole.Gold nanoparticles are one of the most extensively studied nanomaterials systems due to their stability, tunable optical properties, and facile surface chemistry as well as wide-ranging promising applications in nanomedicine, catalysis, electronics, and so on. Among various kinds of polymers, conducting polymersare especially important because the unique structure-dependent conducting propertysupplements the other useful properties ofa polymeric substance. Since the properties of nanomaterials depend on their size, dimensional anisotropy, structure, and crystallinity, there is a constant effort to develop ways to tune these features and hence their properties. Though substantial progress has been made in the size and shape-controlled synthesis of metal nanoparticles, on the contrary, the post-synthesis tuning of the size and morphology of the nanomaterials has been less explored. However, such post synthesis size- and morphology-tuning of nanomaterials can offer novel materials-features that may be difficult to obtain otherwise. New facile, faster, greener, and economical methodologies to manipulate materials at the nanoscale are the need of the day.We discuss various chemical and photochemical methodologies that we have explored and developed for the controlled post-synthesis tuning of the size and morphology of diverse kinds of gold nanoparticles. We have demonstrated a simple, rapid, and practical chemical method that allows post-synthesis tuning of the size and surface morphology of three different kinds of gold nanoparticles under mild conditions. We have employed aqueous KI3as a chemical etching agent and have studied the effects of I3- concentration on the tuning process. I2 is a mild oxidizing agent and allows controlled tuning of the particles at room temperature. This method does not involve any hazardous chemicals, sophisticated equipment, or tedious process such as heating, continuous oxygen bubbling, maintenance of pH, etc. The change in the particle size, surface structure, and morphology during the post-synthesis tuning has been followed by the UV-visible and surface-enhanced Raman scattering (SERS) spectroscopies and transmission electron microscopic (TEM) studies. Excellent surface-enhanced Raman scatteringsubstrates have been prepared by the tuning of the gold nanoparticles. We have studied thephotochemical post-synthesis modifications of three different kinds of nanoparticles. UV-C light (254 nm wavelength) has been used for the photochemical etching of gold nanoparticles. The roles of the etchant ferric chloride, the particle-surface capping agent CTAB, particle number density, and light intensity have been explored. The mechanisms of the etching reactions have been investigated. We have demonstrated that one can easily and controllably modify the morphologies of the preformed gold nanoparticles by using photochemical and chemical etching methods by tuning the exposure of UV-light and other reaction parameters. The photochemical method is very fast, straight forward and does not need any tedious process or sophisticated equipment. The effects of the post-synthesis treatments of three different kinds of gold nanoparticles on their catalytic and SERS properties, which are known to be highly sensitive to the surface characteristics of the nanomaterials, have been investigated. We have demonstrated that the surface modifications produce large differences in the catalytic and SERS properties of gold nanostars, which have extremely complex morphologies, compared to gold nanorods and nanospheres. We have explored an oxidative photo-polymerization technique for the synthesis of polypyrroles (PPYs).The photochemical method of PPY synthesis is rapid, versatile, inexpensive, and technologically simple to implement. The method is a one-step surfactant-free method that does not use any external semiconductor photo-catalyst nanoparticles or chiral dopants. We have studied the effects of the light energy and the period of light irradiation on the photo-polymerization of pyrrole by using different UV and visible light sources. For a comparative study, we have also used an oxidative chemical polymerization by using ferric chloride oxidant. The synthesized polypyrroles have been characterized by various techniques including UV-Vis spectroscopy, scanning electron microscopy (SEM), thermogravimetry, and CD spectroscopy. The level of doping, morphology, and chiral conformation of the PPYs can be varied by us

Abstract

Metallic and polymeric nanomaterials have been at the forefront of various studies and applications for a long time. Development of new, greener, fast, scalable, and controlled synthesis methods, understanding their structures and properties, and exploration of new uses and futuristic applications of these nanomaterials have been the major goals of the researchers recently. The thesis work involves the studies of selected nanoparticle systems of the metal, gold and a conducting polymer (CP), polypyrrole. Gold nanoparticles are one of the most extensively studied nanomaterials systems due to their stability, tunable optical properties, and facile surface chemistry as well as wide-ranging promising applications in nanomedicine, catalysis, electronics, and so on. Among various kinds of polymers, conducting polymers are especially important because the unique structure-dependent conducting property supplements the other useful properties of a polymeric substance. Since the properties of nanomaterials depend on their size, dimensional anisotropy, structure, and crystallinity, there is a constant effort to develop ways to tune these features and hence their properties. Though substantial progress has been made in the size and shape-controlled synthesis of metal nanoparticles, on the contrary, the post-synthesis tuning of the size and morphology of the nanomaterials has been less explored. However, such post synthesis size- and morphology-tuning of nanomaterials can offer novel materials-features that may be difficult to obtain otherwise. New facile, faster, greener, and economical methodologies to manipulate materials at the nanoscale are the need of the day. We discuss various chemical and photochemical methodologies that we have explored and developed for the controlled post-synthesis tuning of the size and morphology of diverse kinds of gold nanoparticles. We have demonstrated a simple, rapid, and practical chemical method that allows post-synthesis tuning of the size and surface morphology of three different kinds of gold nanoparticles under mild conditions. We have employed aqueous KI3 as a chemical etching agent and have studied the effects of I3- concentration on the tuning process. I2 is a mild oxidizing agent and allows controlled tuning of the particles at room temperature. This method does not involve any hazardous chemicals, sophisticated equipment, or tedious process such as heating, continuous oxygen bubbling, maintenance of pH, etc. The change in the particle size, surface structure, and morphology during the post-synthesis tuning has been followed by the UV-visible and surface-enhanced Raman scattering (SERS) spectroscopies and transmission electron microscopic (TEM) studies. Excellent surface-enhanced Raman scattering substrates have been prepared by the tuning of the gold nanoparticles. We have studied the photochemical post-synthesis modifications of three different kinds of nanoparticles. UV-C light (254 nm wavelength) has been used for the photochemical etching of gold nanoparticles. The roles of the etchant ferric chloride, the particle-surface capping agent CTAB, particle number density, and light intensity have been explored. The mechanisms of the etching reactions have been investigated. We have demonstrated that one can easily and controllably modify the morphologies of the preformed gold nanoparticles by using photochemical and chemical etching methods by tuning the exposure of UV-light and other reaction parameters. The photochemical method is very fast, straight forward and does not need any tedious process or sophisticated equipment. The effects of the post-synthesis treatments of three different kinds of gold nanoparticles on their catalytic and SERS properties, which are known to be highly sensitive to the surface characteristics of the nanomaterials, have been investigated. We have demonstrated that the surface modifications produce large differences in the catalytic and SERS properties of gold nanostars, which have extremely complex morphologies, compared to gold nanorods and nanospheres. We have explored an oxidative photo-polymerization technique for the synthesis of polypyrroles (PPYs). The photochemical method of PPY synthesis is rapid, versatile, inexpensive, and technologically simple to implement. The method is a one-step surfactant-free method that does not use any external semiconductor photo-catalyst nanoparticles or chiral dopants. We have studied the effects of the light energy and the period of light irradiation on the photo-polymerization of pyrrole by using different UV and visible light sources. For a comparative study, we have also used an oxidative chemical polymerization by using ferric chloride oxidant. The synthesized polypyrroles have been characterized by various techniques including UV-Vis spectroscopy, scanning electron microscopy (SEM), thermogravimetry, and CD spectroscopy. The level of doping, morphology, and chiral conformation of the PPYs can be var

Abstract

Rice is a major staple food for half the world’s population. With the completion of rice genome sequencing projects and the availability of several high-throughput experimental platforms, a large amount of data is now available in the public domain. However, there still exists a gap between data generation and effective bioinformatic analyses of such data in the scientific community. In the era of Big Data, network-based approaches have made great strides in the field of biomedical research, personal therapeutics as well as in evo-devo studies. Taking cues from these studies, in this thesis, we use a network biology approach to get a systems-level understanding of the rice stress transcriptome, using microarray and RNA-seq data. In the first part of the study, we considered transcriptome data from a drought tolerant rice genotype and constructed a weighted condition-dependent gene co-expression network. Based on differential gene expression analysis, we identified tissue and stage-specific co-expressed modules harbouring differentially expressed genes that are induced or repressed due to stress. Network topological properties such as degree along with fold-change information is used to identify “hub” genes. Unannotated genes that are topologically important in the network and co-clustered with known stress-responsive genes are selected for functional characterization. Network-based concepts such as conserved network neighbourhood and guide-gene approach for the annotation of these novel drought-responsive genes together with promoter analysis led to the annotations of 26 uncharacterized genes. We also used alternate network construction methods to confirm the associations of the uncharacterized genes with their conserved neighbours. In the second part of the thesis we present a meta-analytic study combining gene-expression data from seven drought-tolerant genotypes to identify various drought-adaptive processes in leaf tissue using network-based approach. Here, we propose an integrated approach that incorporates protein-protein interactions with co-expression of genes to construct networks of up and down-regulated genes and identify tightly-coupled gene clusters. Based on the processes/pathways represented by these clusters, we identified some important drought adaptive processes exhibited by these genotypes. Key transcription factors, viz., bZIPs, ABA signalling machinery and interaction of its signalling components with metabolic pathways playing a role in stress adaptive pathways was highlighted. In tandem do this, stomatal regulation and photosynthesis were observed to be important among the down-regulated processes. In the final part of the thesis we present our analysis of RNAseq data to analyze stress responsive processes in rice under different abiotic stress conditions, namely, drought, cold, flood, salinity, etc. For this study, publicly available large-scale mRNA sequencing data of rice(Oryza sativa L. cv. Nipponbare) obtained under uniform experimental conditions for different abiotic stress conditions and time-points was considered. A weighted co-expression network was constructed across four stress conditions and two hormone treatments using differentially expressed genes (DEGs). Co-expressed modules enriched with DEGs with respect to different stress/treatment conditions were identified. Two type of analyses are presented: (i) module-based analysis to identify metabolic pathways that are affected under a given stress condition, and (ii) time-course analysis of the signalling pathways involved in stress response

Abstract

Water is one of the most essential resources on this planet, of which the potable water for human consumption and use is quite limited. This valuable resource is distributed around to the population though a system of interconnected pipelines, mostly situated underground. There is a high possibility of leaks in such pipelines, which is difficult to detect, given that the system is mostly underground. Since water is a very scarce resource and has to be used judiciously, leaks in the pipeline system will prove detrimental to the world. Thus, there is a pressing need to devise solutions that can help detect leaks in such underground pipelines. Though impossible for the naked eye, advancements in technology have paved the way for development of effective monitoring mechanisms. With the advancements in sensor technologies, flow parameters can be measured without manual intervention even when these are relatively small. Leakage in pipes, however minor can cause huge loss of water if not detected early. Since a leak causes change in the flow rate and pressure in the pipeline, these changes, however small, can be picked up by some of these advanced sensors. While monitoring systems help in the identification of changes and there might be ways at addressing it, it is important to devise methods that can help detect and identify the location of water pipeline leaks. The proposed method takes inputs from water flow sensors for a given water distribution network to estimate changes to the hydraulic conditions, if any, at equilibrium and leak induced conditions. This method leverages the electronic sensor data to detect anomalies and flags the corresponding pipeline in the network. The sensors are installed as part of the water distribution network. The entire network is loaded in a Geospatial platform, like QGIS, to help visualize both the distribution network and leak locations. From a users ease point of view, a plugin was developed over the open source GIS platform of QGIS. The plugin helps trigger leak detection based on the sensor input over the spatial water distribution network. The proposed method has been tested over two lab-scale test beds of water distribution network with varying number of joints and pipes. In addition, using these two networks, the system performance was evaluated for different leak locations and varying number of leaks. Overall these cases consisted of different sensor locations, variable number of sensors, different leak locations and variable number vi vii of leaks. The leak detection system can be run in two modes - one being the on-demand mode and the other being the continuous monitoring mode. In both the modes the accuracy of the calibrated flow rate was compared with the sensor data at equilibrium and was found to be satisfactory. It is expected that the method proposed in this work will help water-pipeline managers to detect and locate the leaks in the pipeline networks, enabling them to take necessary measures to avoid wastage of water.

Abstract

Identifying Multiword Expressions (MWEs) is quite an important task when they compose almost 40 percent of the language, as in Hindi. Yet, the serious work on this started only during the last couple of decades. This is quite a challenging task as the multiword expressions do not follow any set of syntactic, semantic or lexical rules which could make them unique or different from any of the other expressions. The apparent vagueness in defining of MWEs is at the core of this problem. They have been defined in several ways by the researchers, one of them even going as far as calling them “A pain in the neck for NLP” for their idiosyncratic interpretations that cross word boundaries [Sag et al., 2002]. In this work, we try to come up with ways to semi-automatically identify the multiword expressions occurring in Hindi language. We focus our work on MWEs that can be defined on the basis of syntactic type of their constituents. Moreover, we also look at ways to identify collocations in the language that form a subset of the MWEs. We make use of some of the existing resources in Hindi, MWE extraction tools and word similarity tools to help us navigate through our problem. In a major work here, we propose a technique to identify Noun+Verb MWEs using Hindi Dependency Treebank [HDTB] as the existing knowledge base. The criteria of word similarity has been used to find an association between the test expression (a potential MWE) and an existing MWE. We hypothesize that the words which are similar tend to be part of similar idiosyncratic constructions and such expressions generally occur in sentences which has similar syntactic construction (karaka and vibhakti similarity). Thus there is a relatively higher possibility for these expressions to be MWE. We also prepare what we call a karaka chart from the HDTB knowledge base which has karaka frame details for the MWEs. Each MWE has a karaka frame, which is a list of potential karakas that the Noun+Verb expression takes for the construction of a valid and meaningful sentence. It is used to see how similar are the karaka labels of the test expression to that of its most similar MWE present in the karaka chart. The similarity is calculated using a popular word similarity tool. This work is done in an effort to get a deeper understanding of a correlation between word similarity and the karaka frame similarity. Our work on collocations delves into identifying adjective-noun bigrams using a technique proposed by us. The criteria of non-substitutability of the constituent within a collocation is a major parameter in the algorithm for collocation identification. The two commonly used methods of automatic collocation extraction, namely, t-score test and pointwise mutual information test, have also been used to perform the experiments on the same data set.

Abstract

In early stage of any building design, the design team has to probe several building models to analyze the building energy consumption. This requires simulation of numerous different models using building energy modelling software. The number of combinations increase exponentially with increasing parameters. This requires a lot of computation to simulate energy consumption for all the input combinations. In a scenario considering five building variables, with ten design choices for each variable, the design team will be required to simulate a hundred thousand different models using building energy management software. This study presents a machine learning based solution to estimate energy consumption of a building in the early phase. The existing research in this domain doesn’t focus on determining the best sample to train the regression models. This study uses a clustering based sampling method to identify the training data. Using clustering, top characteristic feature vectors are derived. The annual energy consumption is simulated for the extracted samples using EnergyPlus. A relationship is then established between the input samples and their corresponding energy consumption through various regression models. These regression models are in turn used to estimate the energy consumption for the large input data sets. This method of surrogate modeling saves a lot of computation by reducing the number of computations by a 100-fold. This method is tested for data from Jaipur and Hyderabad cities of India. Approximately hundred thousand simulations are performed for each location using cloud based parallel computation. By simulating approximately one percent of the input combinations, annual energy consumption for the large set of combinations are estimated using SVR and k-means clustering for Jaipur with accuracy greater than 93% for 99.8% of the input combinations. When the same model is trained for Hyderabad, it produced accuracy greater than 93% for 98% of the input combinations. Using a python based REST framework, an open source REST based web API service - FASTSIM API is developed which can be integrated into any existing software using HTTP requests. The data that we generated for Hyderabad and Jaipur cities is also made publicly available for the research community.

Abstract

Technology is rapidly changing the face of the world by digitizing our experiences from mobile interfaces to affective computing to immersive/ non-immersive 360-degree field of view (FOV). Despite growing importance of the 360-degree FOV, very few studies have evaluated the effectiveness of user-interface (UI) design and individual differences, such as gaming experience, in such interactions. Further, these studies lack the evaluation of time-induced stress during such complex interactions specifically during demanding situations like military operations or reconnaissance.The current thesis focuses on identifying the cognitive challenges with 360-degree 2D remote visual display interface. The studies have two main objectives: 1. Identify necessary display characteristics and cognitive issues related to, specifically, spatial perception and cognitive mapping for 360-degree 2D virtual display interface design 2. Evaluation of Stimulus-Response compatibility as 360-degree virtual environment differs from real world settings We conducted series of experiment to assess the effect of gaming experience under timer vs. no-timer condition, on the navigation, direction estimation, and spatial memory while using various 360-degree 2D interface designs. Participants’ tasks were to navigate in the 3D virtual terrain, locate the targets with perceived egocentric direction, and later place the targets on the overhead map of the terrain. In a follow up study, participants were asked to draw a cognitive map of the virtual environment (VE) post navigation. Interface display designs, gaming experience, and timer (inducing stress) were compared based on navigation time, egocentric direction estimation, target placement and mapping accuracy. Behavioural results showed an advantage of gaming experience in navigation and in direction estimation. Though non-timer condition favoured the gamers in direction estimation, the timer condition did not show any gain based on gaming experience. Interface display designs with visual boundaries showed an advantage in direction estimation. However, no effect of interface display design and gaming experience was observed on target placement task, indicating feeble mental map development during the exploration phase. Results show better cognitive mapping with two split screens 360-degree view compared to other UI designs, indicating a better spatial compatibility. Further, gamers scored better than non-gamers across the interfaces in 360-degree 2D virtual display. In addition, the data indicates that it’s not only the UI designs, but also the individual capabilities such as gaming experience and gender that can influence the task performance. Results from current research will give us an insight into effective 360-degree 2D UI display designs that might be used in security and safety, entertainment, surveillance, or driving simulation purposes

Abstract

In this thesis, we investigate the competency of LHC data to constrain the RD(∗) favored parameter space in a charged scalar leptoquark (S1 ) model. We consider some scenarios with one large free coupling to accomodate the RD(∗) annomalies. As a result, some of them dominantly yield nonresonant ττ and τν events at the LHC through the t-channel S1 exchange. So far, no experiment has searched for leptoquarks using these signatures and the relevant resonant leptoquark searches are yet to put any strong exclusion limit on the parameter space. We recast the latest ττ and τν resonance search data to obtain new exclusion limits. The nonresonant processes strongly interfere (destructively in our case) with the Standard Model background and play the determining role in setting the exclusion limits. To obtain precise limits, we include non-negligible effects coming from the subdominant (resonant) pair and inclusive single leptoquark productions systematically in our analysis. To deal with large destructive interference, we make use of the transverse mass distributions from the experiments in our statistical analysis. In addition, we also recast the relevant direct search results to obtain the most stringent collider bounds on these scenarios to date. These are independent bounds and are competitive to other known bounds. Finally, we indicate how one can adopt these bounds to a wide class of models with S1 that are proposed to accommodate the RD(∗) anomalies. In the first chapter, we study the subject of high energy physics with a brief introduction to the Standard Model and some cases which it cannot explain. In the second chapter, we look at the experimentation involved at the LHC, majorly at the ATLAS and CMS experiments there. In the next chapter, we introduce leptoquarks and describe its productions. In the fourth chapter, we look at the anomalies which exist in B physics. The next few chapters deals with analysis of our study. In chapter eight, we present the results of the study. We finish with the summary and conclusions of our study in chapter nine.

Abstract

Transmission tower is a 3-D truss and indeterminate structure, which plays key role in the operation of a reliable electrical power system. Transmission line tower has to support conductors carrying heavy electrical power and more than one ground wires at appropriate distancesfrom each other above the ground level. Also transmission tower are more commonly used in telecommunication for broadcasting purpose. The total cost of transmission line towers is about 35 to 45 % of the total cost of the transmission line. Apart from conductor load it has to sustain all kinds of natural disaster. So transmission tower designing is an important engineering aspect where knowledge of various engineering fields viz, civil, mechanical and electrical engineering is required. Depending on the purpose and location, transmission towers are designed by varying the shape and size of the tower member.The change in shape and size of diagonal bracesof transmission tower leads to unconventional results like buckling and uplifting.These effects are significant when soil -structure –interactions are considered. Several past studies have shown that large number of structures mainly tall structures damages has been occurred during earthquake due to behaviour of underlying soil and foundation because of geotechnical properties of different landscape units will change dynamic state and greatly influence on the response super structure.Large number of transmission tower and telephonic tower were failed during landers earthquake(1992), Kobe earthquake (1995),chi-chi earthquake(1999),Wenchuan earthquake(2008) etc. In all these earthquake there is one thing common apart from other parameters like earthquake magnitude and frequency, design of structure as per conventional design, ductility of structure and construction quality, there is great influence of interaction between soft and medium soils with the structure which greatly affect the behaviour of the transmissions tower. Therefore it is essential to study the effect soil-structure-interaction on Transmissions tower. Numerical analysis has been performed by two methods i.e., sub-structure (using soil springs at the base) and other one direct method for analysis of SSI. In direct method integrated structure-foundation-soil system is analysed by finite element software ABAQUS. Numerical simulations have been carried out on transmission tower with fixed base, isolated footing, isolated pile foundation, raft foundation and raft pile foundation on soft and medium soil conditions. The aim of this study is to find how soil and foundations behaviour influences the behaviour of transmission tower during earthquake loading. After considering SSI effects in to analysis, In case of soft soil, isolated foundation cannot be used because of excessive lateral deflection, instead of that raft foundation or isolated foundation should be used. Raft foundation would me more economical than the other foundation types. In case of medium soil (density > 1700kg/m3), no need to opt for deep foundation and raft foundation. Isolated foundation would be economical for transmission tower using SSI help. In other words, consideration of SSI in case of medium soil is beneficial as base shear stress reduced as compare to fixed base and also maximum lateral deflection is in the limit. Whereas in case of soft soil base shear stress is reduced but lateral deflection is problem, which leads to failure. So if SSI is not taken in to consideration accuracy in assessment of transmission tower safety could not be reliable.

Abstract

Carbon and gold nanomaterials occupy unique places among the nanomaterials due to the photo/chemical stability, biocompatibility, ease of manipulation, and diverse structures and properties leading to their numerous studies and applications. The advancement in the fields of studies and applications of these novel materials depends mainly on their availability. Therefore, there is a continuous effort towards both the improvement of the existing methods of synthesis and the development of effective facile methods of synthesis of these materials by the scientific community. In this work, we have tried to explore the possibility of developing a rapid, one-pot, room temperature wet chemical synthesis method for producing composite nanocarbon/Au nanoparticles starting from commonly available carbon-containing precursors. We have chosen sucrose as the simple carbon-containing precursor and HAuCl4 as the precursor for the Au nanoparticles and ascorbic acid or hydrazine as the reducing agent with an aim to synthesize nanocarbon-Au nanoparticle composites. Raman and UV-Vis Spectroscopies and Dynamic Light Scattering techniques have been employed for the characterizations of the synthesized composites.