Method of complex paths and general covariance of Hawking radiation

We apply the technique of complex paths to obtain Hawking radiation in different coordinate representations of the Schwarzschild space-time. The coordinate representations we consider do not possess a singularity at the horizon unlike the standard Schwarzschild coordinate. However, the event horizon manifests itself as a singularity in the expression for the semi-classical action. This singularity is regularized by using the method of complex paths and we find that Hawking radiation is recovered in these coordinates indicating the covariance of Hawking radiation. This also shows that there is no correspondence between the particles detected by the model detector and the particle spectrum obtained by the quantum field theoretic analysis -- a result known in other contexts as well.Comment: 9 pages, uses MPLA Style file, Accepted for publication in Mod. Phys. Letts.

Flux Expulsion - Field Evolution in Neutron Stars

Models for the evolution of magnetic fields of neutron stars are constructed, assuming the field is embedded in the proton superconducting core of the star. The rate of expulsion of the magnetic flux out of the core, or equivalently the velocity of outward motion of flux-carrying proton-vortices is determined from a solution of the Magnus equation of motion for these vortices. A force due to the pinning interaction between the proton-vortices and the neutron-superfluid vortices is also taken into account in addition to the other more conventional forces acting on the proton-vortices. Alternative models for the field evolution are considered based on the different possibilities discussed for the effective values of the various forces. The coupled spin and magnetic evolution of single pulsars as well as those processed in low-mass binary systems are computed, for each of the models. The predicted lifetimes of active pulsars, field strengths of the very old neutron stars, and distribution of the magnetic fields versus orbital periods in low-mass binary pulsars are used to test the adopted field decay models. Contrary to the earlier claims, the buoyancy is argued to be the dominant driving cause of the flux expulsion, for the single as well as the binary neutron stars. However, the pinning is also found to play a crucial role which is necessary to account for the observed low field binary and millisecond pulsars.Comment: 23 pages, + 7 figures, accepted for publication in Ap

On long-wavelength magnetic anomalies over Indian region

A data set composed of vector magnetic measurements obtained by MAGSAT and very accurate altitude determinations made using Sun sensors and star cameras was used to obtain data for very quiet days over the Indian region at 10 S to 40 N and 60 E to 110 E in an effort to determine the validity of quantitative estimates made from aeromagnetic data obtained by removing the core field. To further account for the external effects, the ring current contributions estimated using both X and Z variations were subtracted from the observed values. Before this, the core contribution was eliminated through a spherical harmonic expansion with terms up to N=13. Analysis of the residual measurements using Fast Fourier techniques indicates that the anomalies contain substantial power for wavelengths of about 1500 kms. Because the ring current effect has a spatial structure of this dimension over India, efforts are being made to exactly eliminate these two interfering effects from the data

Diagnosing Heart Diseases For Type 2 Diabetic Patients By Cascading The Data Mining Techniques

Motivated by the world-wide increasing mortality of heart disease patients each year, researchers have been using data mining techniques to help health care professionals in the diagnosis of heart disease. Heart disease is the leading cause of death in the world over the past 10 years. Researchers have been using several data mining techniques to help health care professionals in the diagnosis of heart disease. To review the primary prevention studies that focused on the development, validation and impact assessment of a heart disease risk model, scores or rules that can be applied to patients with type 2 diabetes. Efficient predictive modeling is required for medical researchers and practitioners. Attribute values measurement using entropy and information gain parameters. This study proposes Hybrid type 2 diabetes Prediction Model which uses Improved Fuzzy C Means (IFCM) clustering algorithm aimed at validating chosen class label of given data in which incorrectly classified instances are removed and. pattern extracted from original data. Support Vector Machine (SVM) algorithm is used to build the final classifier model by using the k-fold cross-validation method. The aim of this paper is to highlight all the techniques and risk factors that are considered for diagnosis of heart disease. This paper will provide a roadmap for researchers seeking to understand existing automated diagnosis of heart disease

Identification of Biometric-Based Continuous user Authentication and Intrusion Detection System for Cluster Based Manet

Mobile ad hoc is an infrastructure less dynamic network used in many applications; it has been targets of various attacks and makes security problems. This work aims to provide an enhanced level of security by using the prevention based and detection based approaches such as authentication and intrusion detection. The multi-model biometric technology is used for continuous authentication and intrusion detection in high security cluster based MANET. In this paper, an attempt has been made to combine continuous authentication and intrusion detection. In this proposed scheme, Dempster-Shafer theory is used for data fusion because more than one device needs to be chosen and their observation can be used to increase observation accuracy

Niosomes as vesicular carriers for delivery of proteins and biologicals

Over the past several years, treatment of infectious diseases and immunization has undergone a paradigm shift. Stemming from the nanobiotechnology research, not only a large number of disease-specific biologicals have been developed, but also enormous efforts have been made to effectively deliver these biologicals. Niosomes are vesicular systems prepared from self-assembly of hydrated non-ionic surfactants. Opinions of the usefulness of niosomes in delivery of proteins and biologicals range from unsubstantiated optimism to undeserved pessimism. This article reviews the current deepening and widening of interest of niosomes in many scientific disciplines, and their application in medicine particularly for the delivery of proteins (insulin, cyclosporine, bacitracin, trypsin), vaccines and antigens (bovine serum albumin, antigen tetanus toxoid, haemagglutinin). This article also presents an overview of techniques of noisome preparation, characterization of niosomes and their applications.Keywords: Niosomes, Proteins, Biologicals, Vaccines, Oral deliver

Niosomes as vesicular carriers for delivery of proteins and biologicals

Over the past several years, treatment of infectious diseases and immunization has undergone a paradigm shift. Stemming from the nanobiotechnology research, not only a large number of disease-specific biologicals have been developed, but also enormous efforts have been made to effectively deliver these biologicals. Niosomes are vesicular systems prepared from self-assembly of hydrated non-ionic surfactants. Opinions of the usefulness of niosomes in delivery of proteins and biologicals range from unsubstantiated optimism to undeserved pessimism. This article reviews the current deepening and widening of interest of niosomes in many scientific disciplines, and their application in medicine particularly for the delivery of proteins (insulin, cyclosporine, bacitracin, trypsin), vaccines and antigens (bovine serum albumin, antigen tetanus toxoid, haemagglutinin). This article also presents an overview of techniques of noisome preparation, characterization of niosomes and their applications.Keywords: Niosomes, Proteins, Biologicals, Vaccines, Oral deliver

Cloud based multicasting using fat tree data confidential recurrent neural network

With the progress of cloud computing, more users are attracted by its strong and cost-effective computation potentiality. Nevertheless, whether Cloud Service Providers can efficiently protect Cloud Users data confidentiality (DC) remains a demanding issue. The CU may execute several applications with multicast needs. In Cloud different techniques were used to provide DC with multicast necessities. In this work, we aim at ensuring DC in the cloud. This is achieved using a two-step technique, called Fat Tree Data Confidential Recurrent Neural Network (FT-DCRNN) in a cloud environment. The first step performs the construction of Fat Tree based on Multicast model. The aim to use Fat Tree with Multicast model is that the multicast model propagates traffic on multiple links. With the Degree Restrict Multicast Fat Tree construction algorithm using a reference function, the minimum average between two links is measured. With these measured links, multicast is said to be performed that in turn improves the throughput and efficiency of cloud service. Then, with the objective of providing DC for the multi-casted data or messages, DCRNN model is applied. With the Non-linear Recurrent Neural Network using Logistic Activation Function, by handling complex non-linear relationships, average response time is said to be reduced