Women Liberation Politics Explained in Kaalakkanavu – Modern Drama

Ideas like Women’s Liberation, Women’s rights, Women’s Development, Feminism, Women’s Law, Equality for women, resistance against male chauvinism are sounding all over the world. Women are voicing everyday to attain her independent space. But her voices are chocked by male chauvinistic voices. Even after all her voices for liberation, her revolutionary history has been denied and dissembled. Women’s history of liberation has been constructed by men here. Periyarist and Feminist researcher V. Geetha has collected Women’s history and she has written this as a play under the title of “KAALAKKANAVU”.  Professor A. Mangai direct this play and she published this text as a book. This research paper has been pertaining to women liberation thoughts highlighted in this kaalakkanavu modern Drama

Web-Based Customer Relationship Management

The aim of this project is to develop a prototype of Web-based Customer Relationship Management (CRM) application for an e-commerce company. This application will help to assist in meeting the information requirements of the sales agents in e-commerce business to automate sales, marketing, customer service and support. CRM or more specifically eCRM is basically the infrastructure for creating customer loyalty and ultimately, establishing and maintaining a one-to-one relationship with customers. If implemented appropriately, CRM can have a profound impact on an organization's survival and growth in this competitive business world. Hence, GainKnowledge.com, an e-commerce based company was virtually created to demonstrate on how CRM can help in selling e-book devices efficiently by retaining the old customers and attracting new customers. This application has been developed using User Centered Design and CRM Web based development methodologies. In order to build this system, two platforms were used; there are customer information platform and customer interaction platform. Finally, this project discusses some fulfillments, constraints and recommendations for future development of CRM system

Morbidity following Surgical Management of Vulval Cancer.

The objective of this study was to know the complications following vulvectomy and inguinofemoral lymphadenectomy including the time taken to complete wound healing. 42 patients who were subjected to either radical or modified radical vulvectomy for primary and inguinofemoral lymphadenectomy (80 groins) for groin metastases were analysed retrospectively. The complications analysed were wound breakdown, wound cellulitis or infection, lymphocyst, limb edema and the time to wound healing. In a total of 80 inguinofemoral lymphadenectomies 55% had wound breakdown, 17.5% had wound infection/cellulitis, lymphocyst in 31%, limb edema in 36% and time taken for complete wound healing ranged from 10-134 (average 46 days). Overall post operative morbidity was 85%

Master of Science

thesisthey need to reconstruct the underlying neural circuitry. The neural circuit, which consists of the neuron cells and synapses in a three-dimensional (3D) volume of tissue are scanned slice-by-slice at very high magnifications using an electron microscope. From the electron microscopy images, the neurons and their connections (synapses) are identified to lay out the connections of the neural circuitry. One of the necessary tasks in this process is to segment the individual neurons in the images of the sliced volume. To effectively carry out this segmentation we need to delineate the cell membranes of the neurons. For this purpose, we propose a supervised learning approach to detect the cell membranes. The classifier was trained using decision stumps boosted using AdaBoost, on local and context features. The features were selected to highlight the curve like characteristics of cell membranes. It is also shown that using features from context positions allows for more information to be utilized in the classification. Together with the nonlinear discrimination ability of the AdaBoost classifier there are clearly noticeable improvements over previously used methods. We also detail several experiments conducted for identification of synapse structures in the microscopy images

Proposed energy efficient clustering and routing for wireless sensor network

Wireless sensor network (WSN) is considered a growing research field that includes numerous sensor nodes used to gather, process, and broadcast information. Energy efficiency is considered one of the challenging tasks in the WSN. The clustering and routing are considered capable approaches to solve the issues of energy efficiency and enhance the network’s lifetime. In this research, the multi-objective-energy based black widow optimization algorithm (M-EBWOA) is proposed to perform the cluster-based routing over the WSN. The M-EBWOA-based optimal cluster head discovery is used to assure an energy-aware routing over the WSN. The main goal of this M-EBWOA is to minimize the energy consumed by the nodes while improving the data delivery of the WSN. The performance of the M-EBWOA is analyzed as alive and dead nodes, dissipated energy, packets sent to base station, and life expectancy. The existing research such as low-energy adaptive clustering hierarchy (LEACH), hybrid grey wolf optimizer-based sunflower optimization (HGWSFO), genetic algorithm-particle swarm optimization (GA-PSO), and energy-centric multi-objective Salp Swarm algorithm (ECMOSSA) are used to evaluate the efficiency of M-EBWOA. The alive nodes of the M-EBWOA are 100 for 2,500 rounds, which is higher than the LEACH, HGWSFO, GA-PSO, and ECMOSSA

Magneto-convection of water-based nanofluids inside an enclosure having uniform heat generation and various thermal boundaries

AbstractInvestigation of two-dimensional steady laminar magneto-convection heat transfer of (Ag,TiO2) water based nanofluids with variable properties inside a heat generating square enclosure having different thermal boundaries is done numerically in this paper. The governing equations are solved utilizing the finite volume method with power-law scheme and SIMPLE algorithm is used for handling the pressure-velocity coupling. The algorithm and the computer code have been also compared with numerical results in order to verify and validate the model. By using the developed fortran code, the effects of Hartmann number, heat generation (or absorption), Reyleigh number and solid volume fraction on the flow and thermal fields and heat transfer inside the enclosure are studied. Results are demonstrated in the form of streamlines, isotherms and average Nusselt number

LARVICIDAL ACTIVITY OF ESSENTIAL OIL OF GLIRICIDIA SEPIUM LEAF

Objective: This study focus at the larvicidal activity of essential oil of Gliricidia sepium leaf Methods: Pharmacological evaluation of leaf was carried out for larvicidal activity. Household mosquitoes of fourth instar larvae were used for the study. The study was carried out for 5 different concentrations for aqueous extract. Results: The aqueous extract shown dose-dependent activity with the maximum larvicidal potential was seen with leaf of essential oil (250 mg/ml). Conclusion: The study is designed to evaluate the larvicidal activity of essential oil of leaf of G. sepium. The relationship between the chemical composition and biological activity of essential oil of G. sepium is confirmed by lethal effect

PREVALENCE OF EXTENDED SPECTRUM BETA LACTAMASES AMONG ENTEROBACTERIACEAE AND THEIR ANTIBIOGRAM PATTERN FROM VARIOUS CLINICAL SAMPLES

Objective: This study was attempted to evaluate the prevalence of extended spectrum beta-lactamase (ESBL) among Enterobacteriaceae from different clinical samples from a tertiary care hospital in Puducherry.Methods:  A total of 204 gram negative isolates from different clinical samples were studied. All isolates were identified, and antimicrobial susceptibility testing was done by standard microbiological procedures. ESBL production was detected by phenotypic confirmatory disc diffusion test (PCDDT).The test was carried according to CLSI guidelines.Results: Out of 204 isolates, 78 (38.2%) tested positive for ESBL production. Klebsiella pneumoniae (50.9%) showed the maximum ESBL positivity. Amikacin, piperacillin- tazobactam and imipenem are the most effective drugs for the treatment of infections caused by ESBL producing organisms.Conclusion: High prevalence of ESBL producing Enterobacteriaceae in hospitals, with a tendency for multi drug resistance, suggests that routine detection is mandatory as this may help in regulating hospital antibiotic policy.Keywords: Extended spectrum beta-lactamase, Phenotypic confirmatory disc diffusion test, antimicrobial resistance, Enterobacteriaceae

Advancing Healthcare Service Efficacy by Optimizing Pharmaceutical Inventory Management: Leveraging ABC, VED Analysis for Trend Demand

Background: The modern world has witnessed significant advancements across various industries such as food, healthcare, fashion, economics, and education. Among these sectors, healthcare is essential, given its critical role in promoting the well-being of individuals and communities. Purpose: Pharmaceuticals are a significant part of the healthcare system, as they are a crucial factor in increasing life expectancy and are often considered the heart of the health industry. Maintaining effective inventory management for drugs is essential for pharmacists to provide efficient and reliable services to their patients. Methodology: The study thoroughly analyzes the cost and consumption data for each type of demand, to develop a well-suited review and issuance policy for the apothecary. Research Limitations/Implications: The paper delves into the ABC analysis, VED analysis, and trend demand for medical stores, making it a valuable resource for pharmacy stores seeking to optimize their operations and inventory management. Originality/Value: A total of 564 drugs were included in this study, and data were collected from random strip sales between October 2022 and Mar 2023. The study's findings can be used to make informed decisions about inventory planning and classification strategies. The model utilized in this study is based on three categories of medicines: high priority, medium priority, and low priority. By analyzing the demand for these medicines, they can be categorized based on their priority within the three core groups. Pharmacists can use the model to detect shortages and take proactive measures to avoid them by analyzing demand patterns and inventory levels