Signatures of a Collective Self: A Study of Select Contemporary Women Artists from South India

This article attempts to reclaim the status of women artists of South India by a process of recovery and inclusion. The aspect of their marginalisation from mainstream art and subsequent disappearance from the annals of Indian art history has been examined. Further, the reasons for this disappearance are investigated in terms of the overarching notion of gender, embedded in social and cultural parameters. The article locates the manner in which these women artists are affected by familial, institutional and social systems and explores the experiences of the women artists in terms of their multiple roles. This can lead to an understanding of the negotiated spaces of private and public domains, which form the paradigms of art practice and are crucial to the expression of women artists. The critique seeks to register the presence of women artists in South India (which is comprised of four states, Tamil Nadu, Karnataka, Andhra Pradesh and Kerala) from the twentieth century and their contributions. It essentially offers insights into the roles played by the artists and their status not only in terms of gender but also culture and identity and examines the transformations achieved by women artists in South India over the years and the position they occupy. Though Indian Art has grown in international stature and has gained a global visibility today, women artists remain underrepresented in many areas such as major curated shows, international expositions, triennales, and wards of international, national and regional prizes and scholarships. At the national level, South India continues to register minimally in the mainstream of modern Indian art. The study observes how the women artists’ existence in the art world has largely been shown as secondary to that of their male counterparts and that their expressions were not considered ‘good enough’ to be included in mainstream art

Stable Expression Of Tuberculosis Vaccine Antigen In Lettuce Chloroplasts

Tuberculosis (TB) is caused by Mycobacterium tuberculosis and is one of the leading reasons of death by an infectious bacterial pathogen. The development of TB vaccines has been recognized as a major public health priority by the World Health Organization. In this study, a potential candidate antigen, ESAT-6 (6 kDa early secretory antigenic target) was fused with cholera toxin B subunit (CTB). Transplastomic lettuce plants were generated expressing these fusion proteins. Site-specific transgene integration into the chloroplast genome was confirmed by polymerase chain reaction and Southern blot analysis. In transplastomic leaves, expression levels of fusion protein (CTB-ESAT6) varied depending upon the developmental stage and time of leaf harvest with highestlevel of accumulation in mature leaves harvested at 6PM. Transplastomic CTB-ESAT6 lettuce plants accumulated up to 0.75% of total leaf protein. Lyophilization increased CTB-ESAT6 protein content per gram of leaf material by 22 fold. Western blot analysis of lyophilized lettuce leaves showed that the CTB-ESAT6 fusion protein was stable and can be stored for prolonged period at RT. Hemolysis assay with purified CTB-ESAT6 protein showed partial hemolysis of red blood cells and confirmed functionality of ESAT-6 antigen. GM-1 binding assay demonstrated that the CTB-ESAT6 fusion protein formed pentamers to interact with GM1 ganglioside receptor. The expression of functional Mycobacterium tuberculosis antigens fused to CTB in transplastomic plants should facilitate development of a cost-effective and orally deliverable TB vaccine with potential for long term storage at room temperatur

Attribute-Based Encryption Scheme for Secured data Storage in Cloud Computing

This a storage security model in Cloud Computing and making a considerable measure of convincing purposes behind organizations to convey cloud-based storage. For another business, start-up costs are fundamentally decreased in light of the fact that there is no compelling reason to contribute capital in advance for an inner to help the business. By a long shot, the main inquiry customers considering a move to cloud storage ask is regardless of whether their data will be secure. Stored data offsite doesn't change data security necessities; they are the same as those confronting data put away on location. Security ought to be based on business prerequisites for particular applications and data sets, regardless of where the data is stored. We trust that data storage security in Cloud Computing, a zone brimming with challenges and of fundamental significance, is still in its earliest stages now, and numerous examination issues are yet to be distinguished. In this paper, we examined the issue of data security in cloud data storage, to guarantee the rightness of customers' data in cloud data storage. We proposed a Hierarchical Attribute-Based Secure Outsourcing for moldable Access in Cloud computing which likewise guarantees data storage security and survivability accordingly giving put stock in condition to the customers. To battle against unapproved data spillage, delicate data must be encoded before outsourcing in order to give end-to-end data confidentiality affirmation in the cloud and past. It upgrades the security in the proposed model successfully.

Modeling and Simulation of Soft Switching in Traction Inverter

In this thesis, two soft switching inverter topologies the Active Clamped Resonant DC Link Inverter (ACRDCLI) and theAuxiliary Resonant Commutated Pole Inverter (ARCPI) are designed. Their performance is compared with the Hard Switched Inverter (HSI) in simulations. In order to ensure the balance of the soft switching resonant circuit and to achieve a certain reference current, the parame ters of the circuit components are selected according to the references and modified appropriately. The load is modelled as a Permanent Magnet Synchronous Machine (PMSM) equivalent circuit and the parameters are taken from the Finite Element Method (FEM) data based on a fixed operating point. The total power losses in the switches are calculated based on the loss profile in Piecewise Linear Electrical Circuit Simulation (PLECS). Hysteresis current control and Space Vector Pulse Width Modulation (SVPWM) are used to control the current of the ACRDCLI and the ARCPI respectively. Two different state machines have also been designed to ensure the proper operation of the two soft switching topologies. The same control method is used for two HSIs as a control group to have a fair comparison. By simulating each topology under the similar conditions it can be concluded that each topology can output similar power and the total losses in two soft switching topologies are reduced by 18% compared to HSI, especially in switching losses by 98% at 33 kHz switching frequency. Due to the circuit complexity and poor Total Harmonic Distortion (THD) perfor mance of the ACRDCLI only the ARCPI is further analysed for different switching frequencies and current operating points. At high switching frequency of 80 kHz the THD value for the ARCPI is 0.286 % and for the HSI the THD is 0.366 %. With increasing switching frequency the THD for the ARCPI is smaller than the HSI and the ACRDCLI. The ARCPI gives the maximum efficiency of 97.57 % at 25 kHz switching frequency. Compared to the HSI there is an efficiency improvement of 1.71 % with the ARCPI at high switching frequency

Real Time Tele Health Monitoring System

Now a day’s providing healthcare to people anywhere in the world is not economical and patient should visit the doctor to take up the treatment, which is a difficult task in many situations. So the developed model will integrate the patients' medical records with their daily measurements of physiological parameters (including the last checkup records) by making use of ARM processor and RS 232 etc. This can be used as a diagnosis reference for physicians, reducing the time required to modify prescriptions and enabling the nursing staff to fully understand the patients' physiological conditions. By using video conferencing, healthcare practitioners and patients can reduce the costs associated with regular office visits. To provide remote patient monitoring in which electronic devices will transmit patient health information to doctor’s computer and android mobile, enabling them to monitor the patient's condition without being physically present near to the patient's bed

A review of current practices on lead ions removal from different aqueous streams

Toxic heavy metals like Lead are destructive to humans and the environment when existing above their threshold limits. Several conventional lead abatement methods are used in wastewater treatment plants to restore the ecology, food supply, and human and animal health. Many tactics are used to remove harmful Pb metals, like ion exchange, chemical precipitation, membrane filtration, and coagulation. These have a few principal approaches for removing metal ions from used water. Rapid developments in tailor-made materials science have proved to remove Lead metal using ion exchange resins, zeolite, polymeric membranes, and ionic liquids due to their low cost, surface accessibility, and unique benefits. This review paper has studied the detailed benefits and shortcomings of removing lead ions from wastewater using numerous materials, processes of production, possibly destructive properties on public health, and potential hybrid routes. In addition, this work observes the present advancements and developments in lead mitigation tools using different techniques for the past five years. Furthermore, this research review opens up to study of other materials' diverse applications in removal processes

Adaptive Bayesian contextual hyperband: A novel hyperparameter optimization approach

Hyperparameter tuning plays a significant role when building a machine learning or a deep learning model. The tuning process aims to find the optimal hyperparameter setting for a model or algorithm from a pre-defined search space of the hyperparameters configurations. Several tuning algorithms have been proposed in recent years and there is scope for improvement in achieving a better exploration-exploitation tradeoff of the search space. In this paper, we present a novel hyperparameter tuning algorithm named adaptive Bayesian contextual hyperband (Adaptive BCHB) that incorporates a new sampling approach to identify best regions of the search space and exploit those configurations that produce minimum validation loss by dynamically updating the threshold in every iteration. The proposed algorithm is assessed using benchmark models and datasets on traditional machine learning tasks. The proposed Adaptive BCHB algorithm shows a significant improvement in terms of accuracy and computational time for different types of hyperparameters when compared with state-of-the-art tuning algorithms