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Adaptive filtering and control algorithms for grid integration of photovoltaic systems
No full textAmong several renewable energy sources, power generation from Photovoltaic (PV) systems has achieved a tremendous growth in the last few years due to diminishing costs of PV modules in addition to their increased efficiency. Usually, most of the largely powered PV systems are configured to be operated in grid-connected mode to achieve effective usage of solar PV power. PV System connected to Utility Grid (PVS-UG) can either be operated in single-stage or double-stage mode depending upon the power electronic conversion stages involved. In a single-stage PVS-UG, power loss is less compared to a double-stage mode due to absence of dc-dc converter stage. Therefore a single-stage mode of operation is preferred and is considered in the current research work. However, a number of control challenges are encountered while synchronizing a PVS-UG. The rise in use of nonlinear loads has resulted in harmonics injection and other power quality (PQ) issues in the distribution system. Further, the intermittent nature of solar energy is also a major challenge for a PVS-UG. In face of handling dynamic conditions related to load and environment along with the PQ issues, this dissertation focuses on developing adaptive filter based multi-functional control schemes for efficient functioning of a three-phase single-stage PVS-UG. Firstly, an adaptive filter based Modified Leaky Least Mean Square (MLLMS) control scheme has been developed for a PVS-UG. In the proposed MLLMS-based control scheme, an Incremental Conductance (InC) Maximum Power Point Tracking (MPPT) algorithm is used for maximum power extraction, MLLMS algorithm for extraction of fundamental active and reactive components of the load current, delivering PV power to the grid, balancing the grid current and compensating harmonics of the connected loads at the Point of Common Coupling (PCC). By introducing a leakage factor and selection of sum of exponential of the adaptation error in the cost function, the MLLMS algorithm overcomes the problem of drifting, low convergence and oscillations in weights encountered by some popular adaptive algorithms, e.g., Least Mean Square (LMS) and Least Mean Fourth (LMF) algorithms. The proposed MLLMS based control scheme is simulated in MATLAB/Simulink under load unbalance and irradiance change conditions. Subsequently, the said control scheme is realized on a prototype PVS-UG developed in the laboratory. From both the simulation and experimental results, it is observed that the proposed MLLMS based control algorithm outperforms LMS and LMF based control schemes in terms of reduced values in mean square error, oscillation in weights and Total Harmonic Distortions (THDs) of the grid currents. It is necessary to design robust controllers to achieve the grid connected PV system to perform even better during sudden changes in load and environmental conditions. A novel Variable Step Size Robust Least Mean Least Square (VSS-RLMLS) algorithm based control scheme is then designed for a PVS-UG. By implementing a generalized logarithmic cost function which combines higher and lower order measures of error in the weight update function, the proposed VSS-RLMLS algorithm achieves superior performance. In this control scheme, the VSS-RLMLS algorithm estimates the fundamental components of the nonlinear load currents accurately even during dynamic conditions thus allowing efficient functioning of the Voltage Source Converter (VSC) thereby delivering high quality power to the grid and mitigating the harmonics of the loads. From the simulations and experiments performed the proposed VSS-RLMLS based control scheme is seen to outperform control schemes employing LMF, variable leaky LMS and MLLMS in terms of better convergence, less steady state error, robustness during dynamic conditions and less oscillations in weights. The improvement in PQ is confirmed from lower grid current THD which is well within the IEEE-519 standards. Another robust adaptive filter based on the logarithmic cost function is the Least Logarithmic Absolute Difference (LLAD) algorithm. By embedding the conventional cost function of LLAD algorithm into the sigmoidal framework, the Sigmoid LLAD (SLLAD) algorithm is developed which further improves the performance of logarithmic cost function based robust adaptive filters. This new cost function based on the sigmoidal framework exploits the saturation characteristics of the nonlinearity of sigmoid function to achieve the improvement in performance. In the proposed control scheme, the SLLAD control algorithm estimates the fundamental components of nonlinear load currents accurately during dynamic conditions which results in generation of accurate reference grid current. From the simulation and experiments performed the proposed SLLAD based controller is seen to outperform controllers that employ LMF, MLLMS and LLLAD in terms of improved robustness, faster convergence, less steady state deviations and less oscillations in weights. The improvement in PQ is confirmed from lower grid current THD which is well within the IEEE-519 standards. From the comparative assessment it is found that all the proposed control schemes perform well during dynamic changes in the load and environmental conditions maintaining the grid currents sinusoidal, balanced and at unity power factor with THD of grid currents within the IEEE-519 standards. However, it is found that the SLLAD based control scheme performs the best among the above three control schemes during sudden changes in load and environmental conditions with less oscillations in weights and less steady state deviations. As a result, the THD of the grid currents using SLLAD based control scheme is also found to be the lowest among all control schemes. Thus, it is concluded that the SLLAD based control scheme exhibits superior performance among all the aforesaid proposed control schemes
Detailed Study on Molecular Mechanism of Pluripotency and Reprogramming in Testicular Stem Cells – In Silico Approach
No full textTestis-derived male germ-line stem (GS) cells are the in vitro counterpart of spermatogonial stem cell (SSC). Under appropriate culture conditions, GS cells can acquire pluripotency to become multipotent GS or Germ-line pluripotent stem (GPS) cells with the loss of spermatogenic properties. The molecular mechanism of GS niche and, the origin and reprogramming into GPS is elusive. This study hypothesize that, analysis and annotation of high-throughput omics data of GS and GPS cells, by computational methods, may provide insight in drawing the landscape of regulatory network involved in maintenance of stemness in GS cells and their reprogramming into GPS cells. In the first part of the study, the RNA-seq data of both GS and GPS cells were retrieved and subjected to Tuxedo protocol and Network analysis. A novel approach was adopted for the prediction of novel pluripotent genes. Five clusters were identified and ranked according to their score. Novel pluripotent genes like Cdh5, Cdh10 were predicted. The co-expression, clustering of the transcriptome and variation of the transcriptome of GS and GPS cells was studied using fuzzy clustering by AutoSOME. Transcriptome analysis using the proposed approach intuitively and consistently characterized the variation in cell-cell significantly. The study also analyzed the Alternative Polyadenylation (APA) pattern and 3' Untranslated Regions (3'-UTR) length in differentially expressed mRNAs during the reprogramming of GS cells to GPS cells using APADetect. Obtained results suggest that 3'-UTR is longer in GS cells compared to GPS cells The APA-regulated genes were found to be involved in the regulation of mRNA processing and RNA splicing with shortened 3'-UTR. In the next part of the study, CellNet analysis and Boolean models were used to study the relationship of Gene Regulatory Networks (GRNs) between the GS and GPS cells. The GRNs involving all the genes from integrated methods and literature were constructed and qualitative modelling for reprogramming of GS to GPS cells were done by considering the discrete, asynchronous, multivalued logical formalism using the GINsim modeling and simulation tool. Result suggests that reprogramming of GS cells to GPS cells involves signaling pathways namely LIF, GDNF, BMP4, and TGF-β along with some novel pluripotency genes. The study also predicted miRNAs among GS and GPS cells to construct miRNA synergistic networks (MSN) and identify regulatory miRNA modules. Synergistic network involving mmu miR-200b-3p, mmu-miR-429-3p and mmu-miR-141-3p, mmu miR-200a-3p and mmu-miR-200c-3p was found to conjecture and control the pluripotency and reprogramming by promoting Mesenchymal to Epithelial Transition (MET). These data may be useful in analyzing the regulatory network in acquiring pluripotency by male GPS cell, and predicting novel cocktails (mRNA, miRNA, transcription factors (TFs)) that may collectively target the members of regulatory network to induce pluripotency
Machine learning based sensor fault detection schemes for plasma position control in tokamak
No full textThe Tokamak is a device that facilitates nuclear fusion via magnetic confinement of Deuterium and tritium plasma. Circular arrays of magnetic flux sensors are employed outside the vacuum vessel to measure the position of the hot plasma. There are many sources of faults that can affect the readings of these magnetic sensors, namely, stuck-at-zero fault, offset faults, and noise faults. Similarly, the sensors can be influenced by other active or passive currents in the neighboring superconducting coils. Thus, it is essential to detect any faults and recover the faulty sensor to be used for plasma position control inside a Tokamak. In this work, the use of Machine Learning (ML) techniques for sensor fault detection is explored to utilize the knowledge of the experts to automate the sensor fault detection tasks. Since sensor responses are highly non-linear and the exact mathematical model of a sensor is unavailable, data-driven methods are preferred. Therefore, this work targets to explore the effectiveness of ML algorithms to classify the sensor faults. A sensor fault database was made from the simulated and experimental sensor measurement data from the ‘Aditya’ Tokamak situated at the Institute of Plasma Research, Gandhinagar, Gujarat. The three most occurring fault types in a Tokamak, namely Stuck-at-Zero fault, Offset fault, and Noise Faults, were simulated and added to the expected/ideal measurements to create the fault signature database. The ML models were trained using this database. The work reported in this thesis describes the development of algorithms for the detection of various types of sensor faults that occur in plasma position sensors in a Tokamak. Firstly various ML algorithms, namely, Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Gaussian Naive Bayes (GNB), Bernoulli’s Naïve Bayes (BNB), Ridge Classifier, Linear Support Vector Classifier (LSVC), Radial Basis Function Support Vector Classifier (RBFSVC), Nearest Centroid (NC), Radius Neighbor (RN), K-Nearest Neighbor (KNN), Multi-Layer Perceptron (MLP) Neural Network, and Decision Tree (DT) are evaluated for the fault classification. The ML algorithms were compared in terms of classification accuracy and execution time. The Decision Tree method was found to generate the highest scores in classifying the sensor faults, with minimum classification time. Furthermore, a weighted majority voting-based Ensemble Classifier (ECF) was designed constituting Four different ML classifiers, namely, Logistic Regression based Multi-layer Perceptron Classifier (MLP), Support Vector Classifier (SVC), K-Nearest Neighbor (KNN), and Decision Tree (DT). Improvement in overall accuracy was observed with the ECF for correctly identifying and classifying the faults. ML algorithms necessitate significant computational resources, i.e., Central Processing Unit (CPU) and Random Access Memory (RAM), during their training period. Therefore, Graphics Processing Units (GPU) acceleration of the ML models was investigated, as they contain a large number of floating-point processors. A Dense Neural Network (DNN) and a stacked ensemble classifier were evaluated for sensor fault classification. Since the Decision tree algorithm was found to provide the best classification accuracy and classification time, it was chosen to be implemented in FPGA for real-time sensor fault classification. A CPU+FPGA implementation method was used to realize the fault classifier on a Digilent Xilinx PYNQ FPGA platform. Finally, a real-time Hardware-in-Loop (HIL) simulation was designed to evaluate the ML models for sensor fault detection and classification tasks. It consisted of an Android application for user input, a Single Board Computer (SBC) to generate the simulated sensor measurement data, an FPGA board with the ML classifier implementation. A Graphical User Interface (GUI) was developed in ‘Python + Tkinter’ to display the sensor status, with an audible alarm and data-logging system. The application of machine learning algorithms for sensor fault detection for plasma position control in Tokamak shows promising results in automated identification and classification of faults. Automatic fault detection will help reduce the downtime of the Tokamak to search and replace the faulty sensor and improve the overall efficiency of the nuclear fusion process for the generation of electricity
Donor-π-acceptor based push-pull organic chromophores: chemosensing applications through modulation in intramolecular charge transfer
No full textSensing of various targeted analytes including cations, anions and neutral molecules both qualitatively and quantitatively has been receiving growing attention amongst scientist working in diverse areas viz. environmental science, chemical and biochemical science, agricultural science, food processing, medicinal chemistry, pharmacy and health sciences. Several small cations and anions are functionally connected to a wide range of bio-chemical processes within organisms and in the external environment. Further, some small ions are also highly toxic to organisms bringing biological malfunction when present above their permissible limit. Consequently, early detection of these analytes is advantageous and of great concern to the scientific community.
Compared to classical methods for ion detection, chemosensors and especially optical chemosensors (including fluorescent and colourimetric chemosensors) demonstrate many advantages, such as easy and visual detection, high sensitivity, low background interference, and convenient applications in bio-imaging. Investigation of naked-eye colour change and change in UV-Vis absorption and fluorescence spectral behavior of chromogenic and fluorogenic receptors are the most versatile and simple means of analyzing molecular recognition. Among several chromogenic and fluorogenic chemosensors, compounds with Donor--Acceptor (D-π-A) push-pull molecular systems with inherent intramolecular charge transfer (ICT) character are gaining wide interest. The combination of a dipolar D--A signaling moiety with a polar ion recognition unit tends to increase the aqueous solubility of an organic chromophore, which is an essential property of a chemosensors for environmentally and biologically important ions. Presence of ICT may also possibly make them chromogenic and fluorogenic dual responsive chemosensors and provide diverse optical signals favorable for simultaneous detection of multiple analytes.
Although a large number of studies on optical chemosensors are found in the literature, the efficacy of most of these sensors is inadequate because of factors such as complex synthetic procedures, strong interferences, feeble sensitivity and low aqueous solubility. Further challenges for chemosensors are to make the transition from research tools into practically useful portable systems for on-site real time qualitative and quantitative detection of required analyte. It is difficult to make predictions regarding selective interaction between the species of interest (analyte) and receptors in a particular medium when several interfering species are present. Multifaceted behaviour is often observed as a function of receptor structures, mode of binding, mechanism of optical response, medium composition, presence of interfering ions (if any). Therefore, comprehensive investigations are usually required to fully understand the sensing mechanism, to test the feasibility of a particular chemosensor for a specific analyte, and to utilize their potentials to fabricate efficient dual-responsive chromo-fluorogenic chemosensors for specific applications.
Owing to the importance of D-π-A push-pull molecular systems to act both as chromogenic and fluorogenic dual-responsive chemosensors, and the fact that structurally different probes can unveil different aspects of receptor-analyte interactions in aqueous and semi-aqueous solvent systems, the present dissertation entitled “Donor--Acceptor Based Push-Pull Organic Chromophores: Chemosensing Applications through Modulation in Intramolecular Charge Transfer” aims at employing three different simple D-π-A push-pull dipolar chromophores, namely: (E)-4-(4-N,N-bis-(2-hydroxyethylthioethylamino)styryl)-1-methylpyridinium iodide (L1), 2-hydroxy-5-((4-nitrophenyl)diazenyl)benzaldehyde (L2), and N-((4-N,N-diethylamino)-2-hydroxybenzylidene) isonicotinohydrazide (L3) containing cyanine dye, azo dye and hydrazide Schiff base respectively as chromophores. These chromophores are proposed to transduce the event of molecular recognition of metal ions and anions to an readable optical signal. In this thesis attempt has been made to propose possible binding mode and mechanism of signal transduction based on experimental studies as well as theoretical calculations.
The designed D-π-A chromophores are synthesized in good yields and purified by simple procedures. These chromophores are found to be either soluble in pure aqueous or water-rich aqueous-organic binary solvent mixtures and are appropriate for sensing within environmental and biological samples. These chromophores exhibit very intense ICT absorption bands in the visible region. Further, these molecules are found to be weakly fluorescent, assigned to photo electron transfer (PET) due to the presence of non-bonding electrons. However this property became an advantage, as it facilitated a turn-on fluorescence response upon binding to the metal centre; the mechanism of which is believed to be chelation enhanced fluorescence (CHEF) through inhibition of PET. Selective ion recognition by these chemosensors is monitored through investigation of naked-eye colour change and a change in UV-Vis absorption and fluorescence spectral behaviour. Styrylpyridinium (cyanine) dye based D-π-A chromophore (L1), which is attached to a NS2O2 binding unit in its donor site is found to exhibit Hg2+ selective turn-off colourimetric response from orange to colourless. This is accompanied by a turn-on fluorescence response along with a blue shift of emission peak ascribed to the arrest of ICT and PET, through the formation of a conformationally rigid stable 1:1 L1+Hg2+ adduct. Similar Hg2+ selective turn-off colourimetric sensing behaviour is also observed for azo dye based chemosensor (L2) ascribed to the arrest of ICT through the formation of a 1:1 L2-Hg2+ adduct. As expected from the structure of the hydrazide-Schiff base based chemosensor (L3), it demonstrated both cation and anion selective chemosensing behaviour. Out of several metal ions and anions tested, L3 showed a selective response to Al3+ and AsO2-. The obvious colour change of L3 in the presence of these analytes is primarily due to the modulation of ICT upon ion complexation. Conversely, a combined effect of PET, ICT, and excited state intramolecular proton transfer (ESIPT) modulation is proposed to be responsible for prominent fluorescence enhancement.
Reversible selective molecular recognition events with turn-on or turn-off optical signal are used to construct different combinational molecular logic gates. The turn-on fluorescence responses of L1 and L3 in association with their appreciable cell membrane permeability are utilized for the intracellular detection of ions in living cells i.e. Hg2+ by using L1 and Al3+ and AsO2- by using L3. All the three chemosensors are successfully utilized to prepare disposable test paper strips, which can track the presence of targeted metal ions in aqueous media by simple naked-eye detection. This feature makes these test strips practical for the real time on-site detection of targeted analytes.
Therefore, the D--A based organic chromophores with simple chemical architectures can be promising candidates for chemosensing applications. It is worth mentioning that chromogenic and fluorogenic dual responsive chemosensing in combination with multiple interplaying sensing mechanisms can provide diverse optical signals, favourable for the simultaneous detection of multiple analytes. A good understanding of the factors affecting the sensing mechanism, mode of binding in different type of receptors, and the mechanism of signal transduction can lead to the design of novel probe molecules. A proper choice of donor, acceptor and -bridge are expected to deliver targeted properties i.e. better selectivity, sensitivity, aqueous solubility, NIR emission properties for practical applications in areas of molecular chemosensors
New Insights into the Regulatory Functions and Mechanisms of Action of MicroRNA-197 Duo in the Pathophysiology of Human Fibrosarcoma
No full textMicroRNAs (miRNAs) are vital regulators of biological pathways by reinforcing transcriptional programs and moderating transcripts. The abnormal expression of miRNAs is involved in the pathophysiology of many human diseases, including cancer. Among miRNAs, miR-197 plays a dynamic role either as an oncogene or tumor suppressor in different types of carcinomas by modulating apoptosis, angiogenesis, migration, and drug resistance pathways. However, its role in fibrosarcoma, a highly aggressive and malignant soft tissue sarcoma that originates from the mesenchymal tissues, has not yet been elucidated. Therefore, in the current thesis, we studied two mature miRNAs, miR-197-5p and miR 197-3p, which originated from two arms of miR-197 precursor in fibrosarcoma to decode mechanistic insights into their functions by executing several molecular biology assays in vitro. We found from the qRT-PCR study that both the miRNAs are significantly underexpressed in HT1080 fibrosarcoma cells compared to IMR90-tert cells, overexpression of which inhibited viability and proliferation of the cells in both concentration and time-dependent manner. Functional studies of miR-197-5p revealed that miRNA inhibits metastatic properties like migration, invasion, and anchorage independent growth and induce cellular senescence in fibrosarcoma instead of apoptosis via repression of its target KIAA0101, which is a proliferating cell nuclear antigen-associated factor overexpressed in this malignancy. While investigating miR-197-3p, we observed miRNA significantly inhibits viability, colonyforming, and migratory ability of fibrosarcoma cells similar to that of miR-197-5p but triggers G2/M cell cycle phase arrest and autophagy, unlike cellular senescence in the earlier case. We discovered RAN (ras-related nuclear protein) as a target through which miR-197-3p represses tumorigenesis by binding to its 3´ UTR, validated by luciferase reporter assay. Seeing tumorsuppressive functions played by these two miRNAs, we intended to study whether they modulate chemosensitivity of Doxorubicin in fibrosarcoma. Doxorubicin resistance is an obstinate issue in chemotherapy, mainly responsible for tumor recurrence and metastasis and, finally, treatment failure. Intriguingly, we found miR-197 5p increases the sensitivity of fibrosarcoma cells for Doxorubicin through an additive mechanism. However, miR-197 3p did not sensitize the effect of the drug. Overall, we found that both miRNAs inhibit tumor growth in fibrosarcoma but by different mechanisms and targets. Hence, these findings raise the possibility of miR-197 as a novel RNA based therapeutic intervention to treat this malignancy
Synthesis and Characterization of Transition Metal-main Group Cluster for Their Potential in Nanoparticle Synthesis and Catalytic Applications
No full textA large variety of organometallic transition metal clusters with various unique structural architectures are known to contain homo or hetero transition metal atoms joined together by substantial metal-metal bonds and containing a range of terminal and bridging ligands. Cluster compounds have been of immense interest for their structural variety and interesting applications in the field of biology, catalysis, and material chemistry. Recently, the chemistry of transition metal clusters with main group atoms acting as a bridge between two metal atoms has undergone rapid development due to their extra stability and facile synthetic methods. Some synthetic methodologies for obtaining transition metal–main group clusters of unique structural and reactivity features have been explored in current years. A major challenge in the area of transition metal cluster chemistry is the stability of the metal-metal bonds, in which the polar metal-metal bonds in high-nuclear clusters are prone to disintegration or decomposition. Our primary interest has been focused on the synthesis and reactivity of a variety of transition metal clusters by using chalcogen elements as clamps and bridging ligands. The thesis describes the synthesis and characterization of antimony based triiron clusters supported by chalcogenide main group atoms as bridging ligand. To our knowledge phosphine ligated triiron chalcogenide clusters have been well studied, while the stibine analog has so far remained unexplored. Furthermore, transition metal clusters containing both chalcogen and heavier pnictogens have been of interest to study their stability, electronic properties, structural framework, etc to understand their potential in relevant applications. The interest in the field of single source precursors has prompted us to synthesize different iron chalcogenide nanoparticles from predesigned molecular precursors by facile and simple reaction conditions to obtain pure phases of iron selenide and telluride and for different properties study and application purposes
Investigation of Performance and Stability of Organic Solar Cells Fabricated by Incorporating Carbon Nanostructures in both Hole Transport and Active Layers
No full textPhotovoltaic technology is the best solution for supporting humankind to face the alarming energy concerns mounting all over the world, and the organic solar cells (OSCs) which belong to the latest generation photovoltaic technology are of substantial research interest due to their plentiful advantages. However, in a race to take strong control over the global markets, the OSCs are still far behind commercialization due to their low power conversion efficiency (PCE), and degradation of organic materials. The incorporation of materials with exceptional physical properties in the device architecture can significantly improve the performance of the OSCs, and in this regard, applications of carbon nanostructures such as carbon nanotubes (CNTs) and graphene have been considered. Carbon nanostructures and their composites with conductive polymers have been synthesized by simple techniques for their applications in the hole transport layer and the active layer of OSCs. The remarkable modifications observed in the physical properties of the composites have resulted in a significant enhancement in the PCE of composites based OSCs. Periodical measurements of electrical properties of the OSCs performing under different environments have revealed substantial improvement in the stability of the composites based OSCs, despite the degradation of device materials. The effects of temperature on device parameters have been investigated and the composites based OSCs have been noticed to be performing better. The reproducibility of both the performance and the stability of all the OSCs has also been carefully investigated. The brief comparative study presented in this research can substantially motivate scientific communities to consider the remarkable applications of carbon nanostructures in advancing not only OSCs but also other organic optoelectronic devices for the benefit of future generations
Role of Nanomaterials on Retromer Complex and its Consequences on the Development and Maintenance of Sensory Organ of Drosophila
No full textThe current era utilizes nanomaterials in several branches of science including many dayto- day applications. With the wide application, toxic reports are also coming from several studies. There are many open questions associated with nanoparticle trafficking. It includes (1) does the oral intake of nanoparticle (NP) causes developmental and behavioral toxicity? (2) Does the toxicity is a function of defective molecular machinery? (3) Does the toxicity depend on the shape and size of the NP? (4) Does the in vivo toxicity is linked with the malformed gene which occurs during the transportation? These questions are answered in this thesis. The first objective estimated the oral toxicity of different concentrations (10 mg.L-1, 20 mg.L-1, 40 mg.L-1, and 80 mg.L-1) of rod-shaped hydroxyapatite NP (HApNP) on the first instar larva of Drosophila. HApNP affects the development and behavior associated with the eye and mechanosensory organ throughout the development. The eye and mechanosensory organ defects start at the larval stage and persist till adult. All the phenotypic defects were further correlated due to the downregulation of the retromer complex involved in the transportation. The second objective checks the oral toxicity of spherical-shaped silica nanoparticles (SiO2NP) on Drosophila. The 1st instar larvae were fed with different concentrations (5 mg.L-1, 10 mg.L-1, 20 mg.L-1, and 40 mg.L-1) of SiO2NP. The defects were seen from larvae to adults. The defects were seen in the redox pathway, eye, and mechanosensory organs. SiO2NP binds strongly to the actin and thus forms a pore in the membrane. Like HApNP, SiO2NP also causes downregulation of the retromer complex. Since both the nanoparticle affects the retromer during transportation it is worthy to check how the retromer mutant affects the development and behavior associated with the eye and mechanosensory organ. The third objective aims to generate the clone of one of the key components of the retromer complex i.e. Vps35. The photoreceptor and mechanoreceptor clones were generated and the structure, as well as behavior associated with the mechanosensory organs, was investigated. The defects were seen in the antennae, haltere, and ocelli of the clones. The size of the third segment of the antennae was smaller in clones in comparison to the control. Extra bristles were seen in clone heads than that of control. In association with structural deformities, the antennal behavior was also getting interrupted in clones like aggressive, geotaxis, courtship behavior, etc. The simple eye ocelli were also being affected in clones with some overgrowth unlike the control and intra ocellar bristles were also being altered in clones. The circadian rhythm was also being affected in clones which in turn disturbed the light sensitivity in clones suggesting the role of Vps35 not in the development but also in the other cellular pathways associated with the social life of the fly. The number of campaniform sensilla is reduced in the haltere structure of clones. Down regulation of the Iav, Pyx, Nan, NompC suggested a defect in the transportation of antennal signaling molecules in Vps35 mutants
Strengthening of Reinforced Concrete Members Using BFRP Composites
No full textThe fiber reinforced polymer (FRP) has emerged as an encouraging material to either rehabilitate the damaged/partially deteriorated/weakened structures or strengthen a sound structural member to fulfill the load requirements due to change in the mode of use of structures or meet the requirements of the updated design guidelines because of their various advantages like superior strength-to-weight ratio, lightweight, excellent durability etc. The available research on the rehabilitation of reinforced concrete (RC) flexural members using externally bonded FRP composites is primarily based on the application of synthetic fibers such as carbon fiber or glass fiber. It may not always be economically viable to use carbon fiber for the strengthening of RC members due to their very high cost. Although the strengthening schemes comprising of glass fiber sheets are economical than that of carbon fiber sheets, the increasing environmental awareness has encouraged engineers to explore more environment friendly materials such as natural fibers as an alternative to the synthetic fibers in the strengthening of RC members. On the other hand, basalt fiber, a mineral-based natural fiber, is getting a lot of attention from the industrial and academic communities. As basalt fibers are comparatively newer to civil engineering concerning the other synthetic fibers and only a few experimental investigations have been documented in the literature on the strengthening of RC beams with basalt FRP (BFRP) composites, an attempt has been made to explore the efficacy of the BFRP composites as an external shear strengthening material for RC flexural members. Total thirty-nine RC beams were examined under the four-point loading system. Thirty nine RC beams were primarily partitioned into two groups depending on the specimen’s cross section, i.e. R and T beams. Out of 39 RC beams, seven RC beams were tested in unstrengthened conditions and recognized as control beams, while the remaining thirty-two RC beams were strengthened with externally bonded fiber sheets in different configurations. The test parameters include shear span to effective depth ratio, type of strengthening scheme, width of BFRP strips, fiber types and orientations, effect of pre-damage level and the effect of end-anchorage schemes. In addition, the impact of six different types of end-anchorage systems, including one novel end anchorage system comprising of wooden plates, on the efficacy of U-jackets was investigated. The experimental outcomes have revealed that the failure load of strengthened beams improved by 5-89%, whereas the toughness enhanced up to 5 times in comparison to the reference specimen. It has been noticed that the degree of enhancement in shear capacity of strengthened RC beams significantly rests on the considered parameters. The overall effectiveness of basalt fiber sheets in increasing the shear capacity is 20% higher than that of the glass fiber sheets, while the pre-loading level has an adverse effect on the efficacy of external strengthening schemes. Although the endanchorage systems positively influenced the shear contribution by postponing or averting the debonding of fiber sheets from the web surface, their effectiveness varies with their location and type. The efficacy of end-anchorage system placed at the web-flange junction was highest among the considered anchorage schemes, followed by the mechanical anchorage system and the anchorage system comprising of wooden plates. The obtained shear contribution of FRP composites was compared with the predictions made by twelve widely used design guidelines. Besides this, a soft- computing tool, i.e. adaptive neurofuzzy inference system (ANFIS), has been explored to predict the shear contribution of FRP composites towards the shear resistance of RC beams. It is evident from the present study that there is a fine concurrence among the ANFIS estimations and the experimental shear contribution of FRP composites as the average ratio of the ANFIS estimations to the experimental outcomes and the R2 value were observed to be nearly equal to one
Investigation of the Structural, Magnetic, Ferroelectric Properties and their Correlations in YFeO3 and its Modified Systems
No full textIn the search of an efficient magnetoelectric material other than the rare earth orthomanganates, (in which the magnetic transitions and magnetoelectric coupling is at very low temperatures), rare earth orthoferrites has gained considerable attention for their high temperature paramagnetic to canted antiferromagnetic transitions 640-740K for RFeO3 (R=Y, La-Lu). Yttrium orthoferrite (YFeO3) is a simplest of its class for having a non-magnetic Y3+ ion. Since spin reorientation in RFeO3 mainly arises from the magnetic R3+ -Fe3+ interactions, the weak ferromagnetism in YFeO3 apparently arises from the Fe-Fe interactions alone. No evidence of spin reorientation either at low or at high temperatures are found to be present in it. Previous studies have shown that the TN of this system can be markedly reduce below by suitable doping of other transition metal ions such as Cr or Mn in place of Fe. In the present thesis, the various physical properties such as structural, surface morphology, electrical, magnetic, ferroelectricity and magnetoelectric effects have been thoroughly investigated in the modified YFeO3 systems. This includes the investigation on parent YFeO3 through Raman spectroscopy and magnetization measurements that revealed the existence of spin-lattice (phonon) coupling, which influences its ac electrical response. With doping of low percentage Cr (10 at. %), the system exhibited weak ferroelectricity above liquid N2 temperatures while the weak ferromagnetic ordering retained. The magnetization studies at high temperatures also revealed the ordering from Fe-Fe nearest neighbour interactions at T nearly at TN of YFeO3 in this composition. The doped specimen also revealed unusual cluster glass states for T<200K as probed from the ac and dc magnetometry at low temperatures. Astonishingly, a strong magnetoelastic coupling at TN and an isostructural transition is revealed from the high temperature XRD studies. Low temperature XRD also highlighted substantial lattice anomalies at the spin freezing transitions validating the associated magnetoelastic coupling at low temperatures. Temperature dependent Raman spectroscopic studies reveals significant spin –phonon interaction in the medium also which suggests the relaxor like dielectric anomaly can produce the weak ferroelectricity in YFe0.9Cr0.1O3. Similar studies on the codoped specimen Sm0.5Y0.5Fe0.58Mn0.42O3 reveals multiple magnetic transitions at around room temperature, ferroelctricity, strong spin-phonon and electron phonon interactions in the specimen. Further high temperature SXRD studies reveals the anisotropic negative thermal expansion in the Sm0.5Y0.5Fe0.58Mn0.42O3, but absence of magnetostriction. Our study suggests that the parent and modified systems of YFeO3 can be envisaged in multiple technologically enhanced applications