Beyond a "woman's problem" : the role of relationship processes in female genital pain

Female genital pain is a prevalent condition that can disrupt the psychosexual and relational well-being of affected women and their romantic partners. Despite the intimate context in which the pain can be elicited (i.e., during sexual intercourse), interpersonal correlates of genital pain and sexuality have not been widely studied in comparison to other psychosocial factors. This review describes several prevailing theoretical models explaining the role of the partner in female genital pain: the operant learning model, cognitive-behavioral and communal coping models, and intimacy models. The review includes a discussion of empirical research on the interpersonal and partner correlates of female genital pain and the impact of genital pain on partners’ psychosexual adjustment. Together, this research highlights a potential reciprocal interaction between both partners’ experiences of female genital pain. The direction of future theoretical, methodological, and clinical research is discussed with regard to the potential to enhance understanding of the highly interpersonal context of female genital pain

Modelling of Geochemical Processes in Mangrove Ecosystem

The mangrove ecosystem is one of the earth’s most endangered ecosystems. In this study, geochemical features of three mangrove ecosystems, Mangalavanam, Vypeen and Nettoor were compared. Water, sediment and core samples were collected from these stations for a period of one year. Nutrients, organic compounds orgnic carbon and hydrographical parameters of the samples were estimated. The present study revealed higher concentration of carbon in the surface sediments. The major temporary or ultimate sink for various pollutants in estuaries is the sedimentary reservoir, including intertidal areas. In the present study, higher values for dissolved nutrients, POC and carbohydrates were observed during low tide.

Optimization of pH and Direct Imaging Conditions of Complexed Methylene Blue Sensitized Poly(vinyl chloride) Films

Significant results of our experimental investigations on the dependence of pH on real time transmission characteristics on recording media fabricated by doping PVC with complexed methylene blue are presented. The optimum pH value for faster bleaching was found to be 4×5. In typical applications, the illumination from one side, normal to the surface of this material, initiates a chemical sequence that records the incident light pattern in the polymer. Thus direct imaging can be successfully done on this sample. The recorded letters were very legible with good contrast and no scattering centres. Diffraction efficiency measurements were also carried out on this material.

Optimization of pH and Direct Imaging Conditions of Complexed Methylene Blue Sensitized Poly(vinyl chloride) Films

Significant results of our experimental investigations on the dependence of pH on real time transmission characteristics on recording media fabricated by doping PVC with complexed methylene blue are presented. The optimum pH value for faster bleaching was found to be 4×5. In typical applications, the illumination from one side, normal to the surface of this material, initiates a chemical sequence that records the incident light pattern in the polymer. Thus direct imaging can be successfully done on this sample. The recorded letters were very legible with good contrast and no scattering centres. Diffraction efficiency measurements were also carried out on this material.

Optimization of pH and direct imaging conditions of complexed methylene blue sensitized poly(vinyl chloride) films

Significant results of our experimental investigations on the dependence of pH on real time transmission characteristics on recording media fabricated by doping PVC with complexed methylene blue are presented. The optimum pH value for faster bleaching was found to be 4 . 5. In typical applications, the illumination from one side, normal to the surface of this material, initiates a chemical sequence that records the incident light pattern in the polymer. Thus direct imaging can be successfully done on this sample. The recorded letters were very legible with good contrast and no scattering centres. Diffraction efficiency measurements were also carried out on this material.

Supply response and Cost of production of natural rubber- an econometric study

The study deals with the short and long term supply response of the natural rubber in India and to analyse the macro economic environment of NR industry and causative factors of the rubber price crash. It determines the minimum cost of production of natural rubber and to forecast the potential production of NR in India. There is positive response of short run and long run supply to prices. Since correlation analysis show close association between international and domestic price level, international price changes will have its domestic echo. Production and consumption will sustain its rising trend. This makes plans for increasing production estimates show that a mid way level i.e. the range between Rs.32-Rs.38 will give a fair enough profit to the grower in the present situation and provide for the viable sustenance of rubber cultivation. Identification of the SWOT of rubber cultivation would help in supporting rubber cultivation if remedial measures are undertaken with the true spirit. This would help Indian rubber to attain global competitiveness. Then the inflow of valuable foreign exchange will overcome the other economic drawbacks of rubber cultivation

Optimization of Preparation Techniques and Dielectric Study of Polyanilines in the Microwave & High Frequency Field

The thesis deals with the preparation and dielectric characterization of Poly aniline and its analogues in ISM band frequency of 2-4 GHz that includes part of the microwave region (300 MHz to 300 GHz) of the electromagnetic spectrum and an initial dielectric study in the high frequency [O.05MHz-13 MHz]. PolyaniIine has been synthesized by an in situ doping reaction under different temperature and in the presence of inorganic dopants such as HCl H2S04, HN03, HCl04 and organic dopants such as camphorsulphonic acid [CSA], toluenesulphonic acid {TSA) and naphthalenesulphonic acid [NSA]. The variation in dielectric properties with change in reaction temperature, dopants and frequency has been studied. The effect of codopants and microemulsions on the dielectric properties has also been studied in the ISM band. The ISM band of frequencies (2-4 GHz) is of great utility in Industrial, Scientific and Medical (ISM) applications. Microwave heating is a very efficient method of heating dielectric materials and is extensively used in industrial as well as household heating applications.

Optimization of Process Parameters for the Extraction of Gelatin from the Skin of Freshwater Fish and the Evaluation of Physical anal Chemical Characteristics

Faculty of Marine Sciences,Cochin University of Science and Technology

Queueing Theory And Other Applications Of Stochastic Processes Queueing And Inventory Models With Rest Periods

In this thesis we study the effect of rest periods in queueing systems without exhaustive service and inventory systems with rest to the server. Most of the works in the vacation models deal with exhaustive service. Recently some results have appeared for the systems without exhaustive service.

Short-Term Load Forecast Of A Low Loadfactor Power System For Optimization Of Merit Order Dispatch Using Adaptive Learning Algorithm

Short term load forecasting is one of the key inputs to optimize the management of power system. Almost 60-65% of revenue expenditure of a distribution company is against power purchase. Cost of power depends on source of power. Hence any optimization strategy involves optimization in scheduling power from various sources. As the scheduling involves many technical and commercial considerations and constraints, the efficiency in scheduling depends on the accuracy of load forecast. Load forecasting is a topic much visited in research world and a number of papers using different techniques are already presented. The accuracy of forecast for the purpose of merit order dispatch decisions depends on the extent of the permissible variation in generation limits. For a system with low load factor, the peak and the off peak trough are prominent and the forecast should be able to identify these points to more accuracy rather than minimizing the error in the energy content. In this paper an attempt is made to apply Artificial Neural Network (ANN) with supervised learning based approach to make short term load forecasting for a power system with comparatively low load factor. Such power systems are usual in tropical areas with concentrated rainy season for a considerable period of the year

GA-based Optimization of a Fourth-order Sigma-delta Modulator for WLAN

Over-sampling sigma-delta analogue-to-digital converters (ADCs) are one of the key building blocks of state of the art wireless transceivers. In the sigma-delta modulator design the scaling coefficients determine the overall signal-to-noise ratio. Therefore, selecting the optimum value of the coefficient is very important. To this end, this paper addresses the design of a fourthorder multi-bit sigma-delta modulator for Wireless Local Area Networks (WLAN) receiver with feed-forward path and the optimum coefficients are selected using genetic algorithm (GA)- based search method. In particular, the proposed converter makes use of low-distortion swing suppression SDM architecture which is highly suitable for low oversampling ratios to attain high linearity over a wide bandwidth. The focus of this paper is the identification of the best coefficients suitable for the proposed topology as well as the optimization of a set of system parameters in order to achieve the desired signal-to-noise ratio. GA-based search engine is a stochastic search method which can find the optimum solution within the given constraints.

Optimization of parameters of chemical spray pyrolysis technique to get n and p-type layers of SnS

SnS thin films were prepared using automated chemical spray pyrolysis (CSP) technique. Single-phase, p-type, stoichiometric, SnS films with direct band gap of 1.33 eV and having very high absorption coefficient (N105/cm) were deposited at substrate temperature of 375 °C. The role of substrate temperature in determining the optoelectronic and structural properties of SnS films was established and concentration ratios of anionic and cationic precursor solutions were optimized. n-type SnS samples were also prepared using CSP technique at the same substrate temperature of 375 °C, which facilitates sequential deposition of SnS homojunction. A comprehensive analysis of both types of films was done using x-ray diffraction, energy dispersive x-ray analysis, scanning electron microscopy, atomic force microscopy, optical absorption and electrical measurements. Deposition temperatures required for growth of other binary sulfide phases of tin such as SnS2, Sn2S3 were also determined

Soft Computing Approach for Optimization of siRNA Efficiency Prediction for Post-transcriptional Gene Silencing

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.

Micro-electromechanical structural design and optimization of vertical cavity photonic devices with wide continuous tuning

Diese Arbeit umfaßt das elektromechanische Design und die Designoptimierung von weit durchstimmbaren optischen multimembranbasierten Bauelementen, mit vertikal orientierten Kavitäten, basierend auf der Finiten Element Methode (FEM). Ein multimembran InP/Luft Fabry-Pérot optischer Filter wird dargestellt und umfassend analysiert. In dieser Arbeit wird ein systematisches strukturelles Designverfahren dargestellt. Genaue analytische elektromechanischer Modelle für die Bauelemente sind abgeleitet worden. Diese können unschätzbare Werkzeuge sein, um am Anfang der Designphase schnell einen klaren Einblick zur Verfügung zu stellen. Mittels des FEM Programms ist der durch die nicht-lineare Verspannung hervorgerufene versteifende Effekt nachgeforscht und sein Effekt auf die Verlängerung der mechanischen Durchstimmungsstrecke der Bauelemente demonstriert worden. Interessant war auch die Beobachtung, dass die normierte Relation zwischen Ablenkung und Spannung ein unveränderliches Profil hat. Die Deformation der Membranflächen der in dieser Arbeit dargestellten Bauelementformen erwies sich als ein unerwünschter, jedoch manchmal unvermeidbarer Effekt. Es zeigt sich aber, dass die Wahl der Größe der strukturellen Dimensionen den Grad der Membrandeformation im Falle der Aktuation beeinflusst. Diese Arbeit stellt ein elektromechanisches in FEMLAB implementierte quasi-3D Modell, das allgemein für die Modellierung dünner Strukturen angewendet werden kann, dar; und zwar indem man diese als 2D-Objekte betrachtet und die dritte Dimension als eine konstante Größe (z.B. die Schichtdicke) oder eine Größe, welche eine mathematische Funktion ist, annimmt. Diese Annahme verringert drastisch die Berechnungszeit sowie den erforderlichen Arbeitsspeicherbedarf. Weiter ist es für die Nachforschung des Effekts der Skalierung der durchstimmbaren Bauelemente verwendet worden. Eine neuartige Skalierungstechnik wurde abgeleitet und verwendet. Die Ergebnisse belegen, dass das daraus resultierende, skalierte Bauelement fast genau die gleiche mechanische Durchstimmung wie das unskalierte zeigt. Die Einbeziehung des Einflusses von axialen Verspannungen und Gradientenverspannungen in die Berechnungen erforderte die Änderung der Standardimplementierung des 3D Mechanikberechnungsmodus, der mit der benutzten FEM Software geliefert wurde. Die Ergebnisse dieser Studie zeigen einen großen Einfluss der Verspannung auf die Durchstimmungseigenschaften der untersuchten Bauelemente. Ferner stimmten die Ergebnisse der theoretischen Modellrechnung mit den experimentellen Resultaten sehr gut überein.

Many-electron relativistic calculation and interpretation of atomic processes in time dependent heavy-ion scattering

The time dependence of a heavy-ion-atom collision system is solved via a set of coupled channel equations using energy eigenvalues and matrix elements from a self-consistent field relativistic molecular many-electron Dirac-Fock-Slater calculation. Within this independent particle model we give a full many-particle interpretation by performing a small number of single-particle calculations. First results for the P(b) curves for the Ne K-hole excitation for the systems F{^8+} - Ne and F{^6+} - Ne as examples are discussed.