28 resultados para soft lens


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The wavelength dependence of thermal lens signal from organic dyes are studied using dual beam thermal lens technique. It is found that the profile of thermal lens spectrum widely differ from the conventional absorption spectrum in the case of rhodamine B unlike in the case of crystal violet. This is explained on the basis of varying contribution of nonradiative relaxations from the excited vibronic levels.

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Two-photon absorption spectrum of aniline is recorded using thermal lens effect with optical parametric oscillator as the pump source. Studies show that the two-photon absorption spectrum observed corresponds to I Al -. I B2 transition of aniline.

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In this paper we report the use of the dual beam thermal lens technique as a quantitative method to determine absolute fluorescence quantum efficiency and concentration quenching of fluorescence emission from rhodamine 6G doped Poly(methyl methacrylate) (PMMA), prepared with different concentrations of the dye. A comparison of the present data with that reported in the literature indicates that the observed variation of fluorescence quantum yield with respect to the dye concentration follows a similar profile as in the earlier reported observations on rhodamine 6G in solution. The photodegradation of the dye molecules under cw laser excitation is also studied using the present method.

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Dual beam thermal lens tecbnique is successfully employed for the determination of absolute Fluorescence quantum yield of rhodamine 6G lnser dye in different solvents. A 532 nm radiation from a Q-switched Nd:YAG laser was used for the excitation purpose. The fluorescence quantum yield values are found to be strongly influenced by environmental effects. It has been observed that fluorescence yield is greater for rhodamine 6G in ethylene glycol system than in water or in methanol. Our results also indicate that parameters like concentration of the dye solution, aggregate formation and excited state absorption affect the absolute values of fluorescence yield significantly.

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Nano structured noble metals have very important applications in diverse fields as photovoltaics, catalysis, electronic and magnetic devices, etc. Here, we report the application of dual beam thermal lens technique for the determination of the effect of silver sol on the absolute fluorescence quantum yield (FQY) of the laser dye rhodamine 6G. A 532 nm radiation from a diode pumped solid state laser was used as the excitation source. It has been observed that the presence of silver sol decreases the fluorescence quantum efficiency. This is expected to have a very important consequence in enhancing Raman scattering which is an important spectrochemical tool that provides information on molecular structures. We have also observed that the presence of silver sol can enhance the thermal lens signal which makes the detection of the signal easier at any concentration.

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The fluorescence spectrum of the schiff base obtained from salicylaldehyde and 2-aminophenol is studied using an argon-ion laser as the excitation source and its fluorescence quantum yield (Qf) is determined using a thermal lens method. This is a nondestructive technique that gives the absolute value of Qf without the need for a fluorescence standard. The quantum-yield values are calculated for various concentrations of the solution in chloroform and also for various excitation wavelengths. The value of Qf is relatively high, and is concentration dependent. The maximum value of Qf obtained is nearly 0.78. The high value of the fluorescence quantum yield will render the schiff base useful as a fluorescent marker for biological applications. Photostability and gain studies will assess its suitability as a laser dye.

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Dual beam transient thermal lens studies were carried out in rhodamine 6G methanol solutions using 532 nm pulses from a frequency doubled Nd:YAG laser. Analysis of thermal lens signal shows the existence of different nonlinear processes like two photon absorption and three photon absorption phenomena along with one photon absorption. Concentration of the dye in the solution has been found to influence the occurrence of the different processes in a significant way.

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Measurement of thermal lensing signal as a function of laser power made in Rhodamine B solutions in methanol give clear evidence of two photon absorption process within certain concentration ranges when 488 nm Ar+ laser beam is used as the pump source. Only one photon process is found to occur when 514 nm and 476 nm beams are used as the pump.

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International School of Photonics, Cochin University of Science and Technology

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Vibrational overtone spectroscopy of X-H (X=C,N,O) containing molecules is an area of recent interest. The spectroscopic studies of higher vibrational levels yield valuable informations, regarding,the molecular structure, intra- and inter-molecular interactions, radiationless transitions, intra-molecular vibrational relaxations, multiphoton excitations and chemical reactivities, which cannot be z obtained by other spectroscopic methods. This thesis presents the results of experimental investigations on the overtone spectra of some organic compounds in the liquid phase for the characterization of CH bonds. The spectra in the fifth overtone region (1fiV=6) are recorded using a dual beam thermal lens setup and the lower overtones (.AV=2-5) are recorded spectrophotometrically.The thesis is presented in six chapters.

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Microarray data analysis is one of data mining tool which is used to extract meaningful information hidden in biological data. One of the major focuses on microarray data analysis is the reconstruction of gene regulatory network that may be used to provide a broader understanding on the functioning of complex cellular systems. Since cancer is a genetic disease arising from the abnormal gene function, the identification of cancerous genes and the regulatory pathways they control will provide a better platform for understanding the tumor formation and development. The major focus of this thesis is to understand the regulation of genes responsible for the development of cancer, particularly colorectal cancer by analyzing the microarray expression data. In this thesis, four computational algorithms namely fuzzy logic algorithm, modified genetic algorithm, dynamic neural fuzzy network and Takagi Sugeno Kang-type recurrent neural fuzzy network are used to extract cancer specific gene regulatory network from plasma RNA dataset of colorectal cancer patients. Plasma RNA is highly attractive for cancer analysis since it requires a collection of small amount of blood and it can be obtained at any time in repetitive fashion allowing the analysis of disease progression and treatment response.

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A nanocomposite is a multiphase solid material where one of the phases has one, two or three dimensions of less than 100 nanometers (nm), or structures having nano-scale repeat distances between the different phases that make up the material. In the broadest sense this definition can include porous media, colloids, gels and copolymers, but is more usually taken to mean the solid combination of a bulk matrix and nano-dimensional phase(s) differing in properties due to dissimilarities in structure and chemistry. The mechanical, electrical, thermal, optical, electrochemical, catalytic properties of the nanocomposite will differ markedly from that of the component materials. Size limits for these effects have been proposed, <5 nm for catalytic activity, <20 nm for making a hard magnetic material soft, <50 nm for refractive index changes, and <100 nm for achieving superparamagnetism, mechanical strengthening or restricting matrix dislocation movement. Conducting polymers have attracted much attention due to high electrical conductivity, ease of preparation, good environmental stability and wide variety of applications in light-emitting, biosensor chemical sensor, separation membrane and electronic devices. The most widely studied conducting polymers are polypyrrole, polyaniline, polythiophene etc. Conducting polymers provide tremendous scope for tuning of their electrical conductivity from semiconducting to metallic region by way of doping and are organic electro chromic materials with chemically active surface. But they are chemically very sensitive and have poor mechanical properties and thus possessing a processibility problem. Nanomaterial shows the presence of more sites for surface reactivity, they possess good mechanical properties and good dispersant too. Thus nanocomposites formed by combining conducting polymers and inorganic oxide nanoparticles possess the good properties of both the constituents and thus enhanced their utility. The properties of such type of nanocomposite are strongly depending on concentration of nanomaterials to be added. Conducting polymer composites is some suitable composition of a conducting polymer with one or more inorganic nanoparticles so that their desirable properties are combined successfully. The composites of core shell metal oxide particles-conducting polymer combine the electrical properties of the polymer shell and the magnetic, optical, electrical or catalytic characteristics of the metal oxide core, which could greatly widen their applicability in the fields of catalysis, electronics and optics. Moreover nanocomposite material composed of conducting polymers & oxides have open more field of application such as drug delivery, conductive paints, rechargeable batteries, toners in photocopying, smart windows, etc.The present work is mainly focussed on the synthesis, characterization and various application studies of conducting polymer modified TiO2 nanocomposites. The conclusions of the present work are outlined below, Mesoporous TiO2 was prepared by the cationic surfactant P123 assisted hydrothermal synthesis route and conducting polymer modified TiO2 nanocomposites were also prepared via the same technique. All the prepared systems show XRD pattern corresponding to anatase phase of TiO2, which means that there is no phase change occurring even after conducting polymer modification. Raman spectroscopy gives supporting evidence for the XRD results. It also confirms the incorporation of the polymer. The mesoporous nature and surface area of the prepared samples were analysed by N2 adsorption desorption studies and the mesoporous ordering can be confirmed by low angle XRD measurementThe morphology of the prepared samples was obtained from both SEM & TEM. The elemental analysis of the samples was performed by EDX analysisThe hybrid composite formation is confirmed by FT-IR spectroscopy and X-ray photoelectron spectroscopyAll the prepared samples have been used for the photocatalytic degradation of dyes, antibiotic, endocrine disruptors and some other organic pollutants. Photocatalytic antibacterial activity studies were also performed using the prepared systemsAll the prepared samples have been used for the photocatalytic degradation of dyes, antibiotic, endocrine disruptors and some other organic pollutants. Photocatalytic antibacterial activity studies were also performed using the prepared systems Polyaniline modified TiO2 nanocomposite systems were found to have good antibacterial activity. Thermal diffusivity studies of the polyaniline modified systems were carried out using thermal lens technique. It is observed that as the amount of polyaniline in the composite increases the thermal diffusivity also increases. The prepared systems can be used as an excellent coolant in various industrial purposes. Nonlinear optical properties (3rd order nonlinearity) of the polyaniline modified systems were studied using Z scan technique. The prepared materials can be used for optical limiting Applications. Lasing studies of polyaniline modified TiO2 systems were carried out and the studies reveal that TiO2 - Polyaniline composite is a potential dye laser gain medium.

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Post-transcriptional gene silencing by RNA interference is mediated by small interfering RNA called siRNA. This gene silencing mechanism can be exploited therapeutically to a wide variety of disease-associated targets, especially in AIDS, neurodegenerative diseases, cholesterol and cancer on mice with the hope of extending these approaches to treat humans. Over the recent past, a significant amount of work has been undertaken to understand the gene silencing mediated by exogenous siRNA. The design of efficient exogenous siRNA sequences is challenging because of many issues related to siRNA. While designing efficient siRNA, target mRNAs must be selected such that their corresponding siRNAs are likely to be efficient against that target and unlikely to accidentally silence other transcripts due to sequence similarity. So before doing gene silencing by siRNAs, it is essential to analyze their off-target effects in addition to their inhibition efficiency against a particular target. Hence designing exogenous siRNA with good knock-down efficiency and target specificity is an area of concern to be addressed. Some methods have been developed already by considering both inhibition efficiency and off-target possibility of siRNA against agene. Out of these methods, only a few have achieved good inhibition efficiency, specificity and sensitivity. The main focus of this thesis is to develop computational methods to optimize the efficiency of siRNA in terms of “inhibition capacity and off-target possibility” against target mRNAs with improved efficacy, which may be useful in the area of gene silencing and drug design for tumor development. This study aims to investigate the currently available siRNA prediction approaches and to devise a better computational approach to tackle the problem of siRNA efficacy by inhibition capacity and off-target possibility. The strength and limitations of the available approaches are investigated and taken into consideration for making improved solution. Thus the approaches proposed in this study extend some of the good scoring previous state of the art techniques by incorporating machine learning and statistical approaches and thermodynamic features like whole stacking energy to improve the prediction accuracy, inhibition efficiency, sensitivity and specificity. Here, we propose one Support Vector Machine (SVM) model, and two Artificial Neural Network (ANN) models for siRNA efficiency prediction. In SVM model, the classification property is used to classify whether the siRNA is efficient or inefficient in silencing a target gene. The first ANNmodel, named siRNA Designer, is used for optimizing the inhibition efficiency of siRNA against target genes. The second ANN model, named Optimized siRNA Designer, OpsiD, produces efficient siRNAs with high inhibition efficiency to degrade target genes with improved sensitivity-specificity, and identifies the off-target knockdown possibility of siRNA against non-target genes. The models are trained and tested against a large data set of siRNA sequences. The validations are conducted using Pearson Correlation Coefficient, Mathews Correlation Coefficient, Receiver Operating Characteristic analysis, Accuracy of prediction, Sensitivity and Specificity. It is found that the approach, OpsiD, is capable of predicting the inhibition capacity of siRNA against a target mRNA with improved results over the state of the art techniques. Also we are able to understand the influence of whole stacking energy on efficiency of siRNA. The model is further improved by including the ability to identify the “off-target possibility” of predicted siRNA on non-target genes. Thus the proposed model, OpsiD, can predict optimized siRNA by considering both “inhibition efficiency on target genes and off-target possibility on non-target genes”, with improved inhibition efficiency, specificity and sensitivity. Since we have taken efforts to optimize the siRNA efficacy in terms of “inhibition efficiency and offtarget possibility”, we hope that the risk of “off-target effect” while doing gene silencing in various bioinformatics fields can be overcome to a great extent. These findings may provide new insights into cancer diagnosis, prognosis and therapy by gene silencing. The approach may be found useful for designing exogenous siRNA for therapeutic applications and gene silencing techniques in different areas of bioinformatics.