Comparison of post-Newtonian templates for extreme mass ratio inspirals

Extreme mass ratio inspirals (EMRIs), the inspirals of compact objects into supermassive black holes, are important gravitational wave sources for the Laser Interferometer Space Antenna (LISA). We study the performance of various post-Newtonian (PN) template families relative to the high precision numerical waveforms in the context of EMRI parameter estimation with LISA. Expressions for the time domain waveforms TaylorT1, TaylorT2, TaylorT3, TaylorT4 and TaylorEt are derived up to 22PN order, i.e $\mathcal{O}(v^{44})$ ($v$ is the characteristic velocity of the binary) beyond the Newtonian term, for a test particle in a circular orbit around a Schwarzschild black hole. The phase difference between the above 22PN waveform families and numerical waveforms are evaluated during two-year inspirals for two prototypical EMRI systems with mass ratios $10^{-4}$ and $10^{-5}$. We find that the dephases (in radians) for TaylorT1 and TaylorT2, respectively, are about $10^{-9}$ ($10^{-2}$) and $10^{-9}$ ($10^{-3}$) for mass ratio $10^{-4}$ ($10^{-5}$). This suggests that using 22PN TaylorT1 or TaylorT2 waveforms for parameter estimation of EMRIs will result in accuracies comparable to numerical waveform accuracy for most of the LISA parameter space. On the other hand, from the dephase results, we find that TaylorT3, TaylorT4 and TaylorEt fare relatively poorly as one approaches the last stable orbit. This implies that, as for comparable mass binaries using the 3.5PN phase of waveforms, the 22PN TaylorT3 and TaylorEt approximants do not perform well enough for the EMRIs. The reason underlying the poor performance of TaylorT3, TaylorT4 and TaylorEt relative to TaylorT1 and TaylorT2 is finally examined.Comment: 10 page

BAT Algorithm-Based Multi-Class Crop Leaf Disease Prediction Bootstrap Model

In the task of identification of infected agriculture plants, the leaf-based disease identification technique is especially effective in better understand crop disease among various techniques to detect infection. Recognition of an infected leaf image from healthy images gets encumbered when the model is required to detect the type of leaf disease. This paper presents a BAT-based crop disease prediction bootstrap model (BCDPBM) that identifies the health of the leaf and performs disease prediction. The BAT algorithm in the proposed model increases the capability of the Gaussian mixture model for foreground region detection. Furthermore, in the work, the co-occurrence matrix feature and histogram feature are extracted for the training of the bootstrap model. Hence, leaf foreground detection by the BAT algorithm with the Gaussian mixture improves the feature extraction quality for bootstrap learning. The proposed model utilizes a dataset of real leaf images for conducting experiments. The results of the model are compared with different existing models across various parameters. The results show the prediction accuracy enhancement of multiclass leaf disease using the BCDPBM model

A review of Amlapitta

Over the last several decades our diet has become unhealthy and our lifestyle sedentary. These factors have resulted in an ever-increasing prevalence of the lifestyle disease. Among the environmental factors, lifestyle factors in particular being overweight, incorrect dietary habits, lack of regular physical activity and smoking have frequently been resulted in various gastrointestinal diseases. Lifestyle is an essential factor in heath. Unhealthy behavior can lead to illness, disability and even death. Earlier the diet used to include a lot of vegetables and fruits which gave nutritional value. With the fast-paced modern lifestyle the diet has also become fast. In a competitive world people have no time to cook meal or sit and eat slowly. People resort to fast foods frozen foods loaded with preservatives and skip on healthy nutritional food. Along with poor eating habits lack of physical fitness is a significant problem in modern lifestyle. Use of mobile phones, television, computers longer commutes have contributed to sleep deprivation. Lifestyle modifications are currently used as first line of treatment for subjects with gastrointestinal diseases

A comparative study of cognitive insight in schizophrenia patients with and without depression

Background: Lack of insight has been linked to disorganized symptoms or symptoms of formal thought disorder which is often seen in schizophrenia. The main aim of our study was to assess cognitive insight in patients of schizophrenia with and without depression and relation of cognitive insight with psychopathology of schizophrenia.Methods: The Present study was carried out on 60 patients in both groups. After randomization, assessment of Socio demographic details was done with the help of semi-structured performa.Results: There was no significant difference was found in both groups in socio demographic data. Better cognitive insight was found in schizophrenia patients with depression. The cognitive insight and psychopathology were not found significantly correlated to the age of the patient, age of onset of the illness and the total duration of the illness. There was significant difference among groups in relation to the PANSS-P, PANSS-G, with cognitive insight SR, SC, RC (p value 0.000).  No significant difference was found for the PANSS-N (p=0.156) among both groups.Conclusions: Cognitive insight may impact negative symptoms directly via a rigid reasoning style that fosters disengagement in constructive activity as well as reduced interpersonal expressivity.

Treatment with Green Tea Prevents Intracerebroventricular Streptozotocin Induced Cognitive Impairment and Oxidative Stress in Mice

Green tea polyphenols have demonstrated significant antioxidant, anti-carcinogenic, anti-mutagenic and antidiabetic in numerous human, animal and in vitro studies. Hence present study was design to evaluate the influence of green tea in streptozotocin induced oxidative stress in mice.Morris water maze, Elevated plus maze and passive avoidance apparatus was used for the evaluation of learning and memory. Brain thiobarbituric acid reactive substance was also estimated.Intracerebroventricular administration of streptozotocin reduces the learning and memory and increase the concentration of thiobarbituric acid reactive substance in mice. Green tea significantly improves the learning and memory and reverses the increase thiobarbituric acid reactive substance concentration in mice.The result of present study indicates that green tea improve the learning and memory. It also reduces the streptozotocin induced oxidative stress.Keyword: Hippocampus, degenerative disease, green te

Treatment with Green Tea Prevents Intracerebroventricular Streptozotocin Induced Cognitive Impairment and Oxidative Stress in Mice

Green tea polyphenols have demonstrated significant antioxidant, anti-carcinogenic, anti-mutagenic and antidiabetic in numerous human, animal and in vitro studies. Hence present study was design to evaluate the influence of green tea in streptozotocin induced oxidative stress in mice.Morris water maze, Elevated plus maze and passive avoidance apparatus was used for the evaluation of learning and memory. Brain thiobarbituric acid reactive substance was also estimated.Intracerebroventricular administration of streptozotocin reduces the learning and memory and increase the concentration of thiobarbituric acid reactive substance in mice. Green tea significantly improves the learning and memory and reverses the increase thiobarbituric acid reactive substance concentration in mice.The result of present study indicates that green tea improve the learning and memory. It also reduces the streptozotocin induced oxidative stress.Keyword: Hippocampus, degenerative disease, green te

Tropical Grassland Ecosystems and Climate Change

Grasses are unique group of flowering plants that form the foundation for the trophic structure in terrestrial communities. The grasses are found in every conceivable habitat where plants can thrive – from sea to deserts and from wetlands to peaks of highest mountains. The grasses form a distinct biome – a major ecological formation in the global classification of vegetation

A client-server software application for statistical analysis of fMRI data

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2004.Includes bibliographical references (leaves 63-66).Statistical analysis methods used for interrogating functional magnetic resonance imaging (fMRI) data are complex and continually evolving. There exist a scarcity of educational material for fMRI. Thus, an instructional based software application was developed for teaching the fundamentals of statistical analysis in fMRI. For wider accessibility, the application was designed with a client/server architecture. The Java client has a layered design for flexibility and a nice Graphical User Interface (GUI) for user interaction. The application client can be deployed to multiple platforms in heterogeneous and distributed network. The future possibility of adding real-time data processing capabilities in the server led us to choose CGI/Perl/C as server side technologies. The client and server communicates via a simple protocol through the Apache Web Server. The application provides students with opportunities for hands-on exploration of the key concepts using phantom data as well as sample human fMRI data. The simulation allows students to control relevant parameters and observe intermediate results for each step in the analysis stream (spatial smoothing, motion correction, statistical model parameter selection etc.). Eventually this software tool and the accompanying tutorial will be disseminated to researchers across the globe via Biomedical Informatics Research Network (BIRN) portal.by Vijay Singh Choudhary.S.M

PHYTOCHEMISTRY AND PHARMACOLOGY OF PTEROCARPUS SANTALINUS AND ITS ROLE IN DERMATOLOGY

The review provides an updated overview of the phytochemical and pharmacological studies on Pterocarpus santalinus. It briefs on the synergistic interactions of P. santalinus with other medicinal plants and its use in Ayurvedic formulations. Phytochemical analysis suggests the presence of triterpenoids, steroids, flavonoids, and phenolic acids. The phytoconstituents and related pharmacological activities of various parts of P. santalinus include antifungal, anticholinesterase, antidiabetic, antibacterial, antipyretic, anti-inflammatory, anticancer, and antiulcer. Literature survey highlights the dermatological applications of the phytoconstituents such as pterostilbene, savinin, and betulin as potential leads for anti-aging, ultraviolet rays (UV-B) protective, and wound healing effects. Undoubtedly, P. santalinus has wide therapeutic value. The dermatologically significant phytoconstituents, namely, pterostilbene, cedrol, savinin, lupeol, betulin, β-eudesmol, and α-bisabolol, if isolated and used in dermatological formulations, can show promising skin protective effect. The data were compiled using scientific databases, namely, Google Scholar and PubMed, the data made available specifically from 2010 to 2021