Blindly detecting orbital modulations of jets from merging supermassive black holes

In the last few years before merger, supermassive black hole binaries will rapidly inspiral and precess in a magnetic field imposed by a surrounding circumbinary disk. Multiple simulations suggest this relative motion will convert some of the local energy to a Poynting-dominated outflow, with a luminosity 10^{43} erg/s * (B/10^4 G)^2(M/10^8 Msun)^2 (v/0.4 c)^2, some of which may emerge as synchrotron emission at frequencies near 1 GHz where current and planned wide-field radio surveys will operate. On top of a secular increase in power on the gravitational wave inspiral timescale, orbital motion will produce significant, detectable modulations, both on orbital periods and (if black hole spins are not aligned with the binary's total angular momenta) spin-orbit precession timescales. Because the gravitational wave merger time increases rapidly with separation, we find vast numbers of these transients are ubiquitously predicted, unless explicitly ruled out (by low efficiency $\epsilon$) or obscured (by accretion geometry f_{geo}). If the fraction of Poynting flux converted to radio emission times the fraction of lines of sight accessible $f_{geo}$ is sufficiently large (f_{geo} \epsilon > 2\times 10^{-4} for a 1 year orbital period), at least one event is accessible to future blind surveys at a nominal 10^4 {deg}^2 with 0.5 mJy sensitivity. Our procedure generalizes to other flux-limited surveys designed to investigate EM signatures associated with many modulations produced by merging SMBH binaries.Comment: Submitted to ApJ. v1 original submission; v2 minor changes in response to refere

Constraints on the environment and energetics of the Broad-Line Ic SN2014ad from deep radio and X-ray observations

Broad-line type Ic Supernovae (BL-Ic SNe) are characterized by high ejecta velocity ($\gtrsim 10^4$ km s$^{-1}$) and are sometimes associated with the relativistic jets typical of long duration ($\gtrsim 2$ s) Gamma-Ray Bursts (L-GRBs). The reason why a small fraction of BL-Ic SNe harbor relativistic jets is not known. Here we present deep X-ray and radio observations of the BL-Ic SN2014ad extending from $13$ to $930$ days post explosion. SN2014ad was not detected at either frequency and has no observational evidence of a GRB counterpart. The proximity of SN2014ad ($d\sim 26$ Mpc) enables very deep constraints on the progenitor mass-loss rate $\dot{M}$ and on the total energy of the fast ejecta $E$. We consider two synchrotron emission scenarios for a wind-like circumstellar medium (CSM): (i) uncollimated non-relativistic ejecta, and (ii) off-axis relativistic jet. Within the first scenario our observations are consistent with GRB-less BL-Ic SNe characterized by a modest energy budget of their fast ejecta ($E \lesssim 10^{45}$ erg), like SNe 2002ap and 2010ay. For jetted explosions, we cannot rule out a GRB with $E \lesssim 10^{51}$ erg (beam-corrected) with a narrow opening angle ($\theta_j \sim 5^{\circ}$) observed moderately off-axis ($\theta_{\rm obs} \gtrsim 30^{\circ}$) and expanding in a very low CSM density ($\dot{M}$ $\lesssim 10^{-6}$ M$_{\odot}$ yr$^{-1}$). Our study shows that off-axis low-energy jets expanding in a low-density medium cannot be ruled out even in the most nearby BL-Ic SNe with extensive deep observations, and might be a common feature of BL-Ic SNe.Comment: 9 pages, 5 figures, accepted in Ap

Cricket Score Prediction Using Machine Learning

Currently, there is a system which can calculate the current run rate and from it calculates the final score of the team. It doesn’t consider the fact about the no of wickets and also where the game is being played. The problem with the current system is that it is unable to predict the score of the 2nd team and also unable to predict the win percentage This system which is developed will have 2 model in it the 1st model predict the score a team will get after playing 50 over from the current situation. The second method predicts the win percentage of both teams even before the match has started this done by player selection. We found that error in regression toward the mean classifier could be a smaller quantity than Naïve mathematician in predicting match outcome has been sixty-eight ab initio from 2-15 overs to ninety-one until the top of 42th over

DEVELOPMENT OF SIMPLE HPLC METHOD TO ESTIMATE THE BLOOD PLASMA CONCENTRATION OF EFAVIRENZ IN RAT AFTER ORAL ADMINISTRATION

Objective: The present study was design with an objective of developing a simple and rapid high performance liquid chromatography (HPLC) method for the determination of Efavirenz (EFA) in rat plasma.Methods: Chromatographic separation was achieved on C18 column using acetonitrile-50 mM potassium phosphate (55:45 v/v) as mobile phase at a flow rate of 1 ml/min and UV detection at 250 nm.Results: The retention time of EFA was found to be 13.2 min. The developed method was validated for linearity, limit of quantification (LOQ), limit of detection (LOD), Stability and selectivity. Linearity studies were found to be acceptable over the range of 5-50 μg/ml.Conclusion: The present analytical method was found to be specific, sensitive, accurate and precise for quantification of EFA in rat plasma. It can be successively applied for pharmacokinetics studies also.Â

Deep Learning for Dense Interpretation of Video: Survey of Various Approach, Challenges, Datasets and Metrics

Video interpretation has garnered considerable attention in computer vision and natural language processing fields due to the rapid expansion of video data and the increasing demand for various applications such as intelligent video search, automated video subtitling, and assistance for visually impaired individuals. However, video interpretation presents greater challenges due to the inclusion of both temporal and spatial information within the video. While deep learning models for images, text, and audio have made significant progress, efforts have recently been focused on developing deep networks for video interpretation. A thorough evaluation of current research is necessary to provide insights for future endeavors, considering the myriad techniques, datasets, features, and evaluation criteria available in the video domain. This study offers a survey of recent advancements in deep learning for dense video interpretation, addressing various datasets and the challenges they present, as well as key features in video interpretation. Additionally, it provides a comprehensive overview of the latest deep learning models in video interpretation, which have been instrumental in activity identification and video description or captioning. The paper compares the performance of several deep learning models in this field based on specific metrics. Finally, the study summarizes future trends and directions in video interpretation

New Report On AMF Colonization in Root Parasite Striga gesnerioides and its Host Lepidagathis hamiltoniana from High Altitude Region of Maharashtra

Present paper deals with in-depth analysis of AMF colonization reported in root parasite Striga gesnerioides (Willd) Vatke. Oester, Var gesnerioides and its host Lepidagathis hamiltoniana Wall. ex Nees collected from from Alang, and Madan Forts situated at high altitude region of Maharashtra. Although AM fungal colonization in S. gesnerioides and its host L. cuspidata has been recently reported, this is the new report with reference to host- parasite system of S. gesnerioides - L. hamiltoniana from high altitude region of Maharashtra

Rupture of Heart in a Cannabis Addict: an Autopsy Case Report

Background: Cannabis sativa or indica also known as Indian hemp is most widely used illicit drug in the world in its various forms such as bhang, majoon, ganja, charas or hashis. It affects various systems of human body on virtue of its active principle i.e. delta-9 tetrahydrocannabinol (THC). Its effect on cardiovascular system such as dose dependant increase in heart rate, arrhythmia and increased occurrence of myocardial infarction are well known.Case Report: In present case, a 42 years old male, addicted to ingestion of ‘bhang’ and suffering from psychiatric illness was brought to the hospital with history of headache and vomiting since last 12 hours. There was history of his violent behaviour, hence he was kept locked in a room for few hours and then relieved. He was treated for few hours and succumbed to death. On autopsy, patent coronaries and rupture of anterior wall of heart, in the vicinity of inter-ventricular septum was revealed.Conclusion: To the best of our knowledge, no such case was found in the literature. Treatment of patients with history of cannabis addiction must be focused in the view of acute cardiac conditions

Application of improved you only look once model in road traffic monitoring system

The present research focuses on developing an intelligent traffic management solution for tracking the vehicles on roads. Our proposed work focuses on a much better you only look once (YOLOv4) traffic monitoring system that uses the CSPDarknet53 architecture as its foundation. Deep-sort learning methodology for vehicle multi-target detection from traffic video is also part of our research study. We have included features like the Kalman filter, which estimates unknown objects and can track moving targets. Hungarian techniques identify the correct frame for the object. We are using enhanced object detection network design and new data augmentation techniques with YOLOv4, which ultimately aids in traffic monitoring. Until recently, object identification models could either perform quickly or draw conclusions quickly. This was a big improvement, as YOLOv4 has an astoundingly good performance for a very high frames per second (FPS). The current study is focused on developing an intelligent video surveillance-based vehicle tracking system that tracks the vehicles using a neural network, image-based tracking, and YOLOv4. Real video sequences of road traffic are used to test the effectiveness of the method that has been suggested in the research. Through simulations, it is demonstrated that the suggested technique significantly increases graphics processing unit (GPU) speed and FSP as compared to baseline algorithms

Isolation, identification and screening of potential cellulase-free xylanase producing fungi and its production

In order to isolate cellulase-free xylanase producing fungi, screening and isolation was done using composting soil as microbial source. Eight fungal species were selected for further study based on clearing zones formation on agar media containing covalently linked xylan with dye cibacron brilliant red-3BA. Both solid state and submerged fermentations were done with eight fungal isolates to identify strain that could produce highest amount of cellulase-free xylanase at a pH of 5.5 and at 28 ± 2°C temperature. Under solid state conditions, 50% of the strains produced xylanase (45.78 to 923 U gds-1) and lower amount of cellulase (20 to 33 U gds-1). The amount of soluble protein was also determined which ranged between 67 to 99 mg gds-1. In submerged conditions, 25% strains produced xylanase (45 to 205 U mL-1) and negligible amount of cellulase (12 to 13 U mL-1). The amount of soluble protein was determined which ranged between 45 and 85 U ml-1 in submerged conditions. Growth was determined in terms of mycelial dry weight which ranged between 0.70 and 2.90 mg mL-1.Keywords: Cellulase-free xylanase, xylan, solid state fermentation, submerged fermentatio