Marginalizing over the waveform systematics of compact binary coalescence models using RIFT

As Einstein’s equations for binary compact object inspiral have only been approximately or intermittently solved by analytic or numerical methods, the models used to infer parameters of gravitational wave (GW) sources are subject to waveform modeling uncertainty. We illustrate these differences and then introduce a very efficient technique to marginalize over waveform uncertainties, relative to a prespecified sequence of waveform models. We also extend this technique to include dynamic weighting by calculating overlap of models with Numerical Relativity. Being based on RIFT, a very efficient parameter inference engine, our technique can directly account for any available models, including very accurate but computationally costly waveforms. Our evidence and likelihood-based method works robustly on a point-by-point basis, enabling accurate marginalization for models with strongly disjoint posteriors while simultaneously increasing the reusability and efficiency of our intermediate calculations

An Empirical Analysis on Software Development Efforts Estimation in Machine Learning Perspective

The prediction of effort estimation is a vital factor in the success of any software development project. The available of expert systems for the software effort estimation supports in minimization of effort and cost for every software project at same time leads to timely completion and proper resource management of the project. This article supports software project managers and decision makers by providing the state-of-the-art empirical analysis of effort estimation methods based on machine learning approaches. In this paper ?ve machine learning techniques; polynomial linear regression, ridge regression, decision trees, support vector regression and Multilayer Perceptron (MLP) are investigated for the purpose software development effort estimation by using bench mark publicly available data sets. The empirical performance of machine learning methods for software effort estimation is investigated on seven standard data sets i.e. Albretch, Desharnais, COCOMO81, NASA, Kemerer, China and Kitchenham. Furthermore, the performance of software effort estimation approaches are evaluated statistically applying the performance metrics i.e. MMRE, PRED (25), R2-score, MMRE, Pred(25). The empirical results reveal that the decision tree-based techniques on Deshnaris, COCOMO, China and kitchenham data sets produce more adequate results in terms of all three-performance metrics. On the Albretch and nasa datasets, the ridge regression method outperformed then other techniques except pred(25) metric where decision trees performed better

A prospective, randomized, double blind study to evaluate and compare the efficacy of lidocaine, ramosetron and tramadol pre-medication, in attenuating the pain caused due to propofol injection

Background: Propofol is a popular induction agent, especially for short cases, day care surgeries and when a laryngeal mask is to be used. It produces a good quality of anaesthesia and rapid recovery. Pain on injection of propofol has been reported and is an important limitation of its use. A multitude of interventions: pharmacological as well as non-pharmacological, have been tried for the attenuation of pain caused due to propofol injection. In our study, we evaluated and compared the efficacy of lidocaine, ramosetron and tramadol in attenuating pain on propofol injection.Methods: A total of 180 patients belonging to American Society of Anesthesiologists (ASA) grade I and II,  of either sex, aged between 21 to 50 years undergoing elective surgery under general anaesthesia, were taken up for the study and were divided into group A, B and C. Group A received 2ml of 2% (40mg) lidocaine, Group B received 2ml of ramosetron (0.3mg) and Group C received 1mg/kg of tramadol in 0.9% normal saline to make a total solution of 2ml. Venous occlusion was done by compressing forearm with tourniquet to increase the local concentration of drug after establishing an intravenous access. The study drug was injected over 10 seconds and then occlusion was removed after 60 seconds, followed by giving 25% of the total calculated dose (2.5mg/kg) of propofol (1% w/v in lipid base) injected over 20 seconds. This was followed by asking the patient about the severity of pain felt. The intensity of pain was graded using verbal rating scale (McCrirrick and Hunter) and was assessed at 0, 5, 10, 15 and 20 seconds, as after 20 seconds, the patient would be under the influence of propofol.Results: Lidocaine showed the best efficacy in attenuating propofol injection pain amongst the 3 groups recorded at 5 (95%), 10 (91.7%) and 15 seconds (98.3%). In addition to reducing the incidence of pain, it also reduced its severity, with majority of patients experiencing only mild pain. Ramosetron ranked 2nd in the overall reduction of propofol pain, with lowest incidence of propofol pain amongst 3 groups, recorded at 0 (98.3%) and 20 seconds (95%) of propofol injection. However, ramosetron failed in reducing severity of pain, with a significant number of patients experiencing moderate and severe pain. Tramadol ranked 3rd in the overall attenuation of propofol pain and showed lowest incidence of pain at 0 seconds (93%) of propofol injection.Conclusions: All the three study drugs viz lidocaine, ramosetron and tramadol cause a significant decrease in propofol injection pain with lidocaine as the most efficacious drug amongst the 3 drugs followed by ramosetron and tramadol. Lidocaine has an added advantage of decreasing incidence and severity of pain associated with propofol and ramosetron prevents postoperative nausea and vomiting

Effect of ketamine infusion in treatment resistant depression and in depressive patients with active suicidal ideations: a study from North India

Background: Treatment resistant depression can be a life-threatening condition as it leads to an increase of suicide attempts by two to three folds. It has been estimated that nearly 1 million people die due to suicide every year, and more than two-third of these cases occur when the person is undergoing a major depressive episode. Ketamine is an NMDA receptor antagonist, an anesthetic agent that is short acting and has recently been used as an antidepressant and anti-suicidal agent. It has been seen that a single intravenous infusion of ketamine at a lower dose. i.e., subanesthetic dose of 0.5 mg/kg over a period of 40 minutes produces antidepressant effect which lasts for about a week and various studies have proved that repeated infusions of ketamine can prolong the duration of the antidepressant response. Methods: It was an observational/descriptive study done in the ketamine clinic/ECT suite of institute of mental health and neurosciences Kashmir (an associate hospital of government medical college Srinagar) which runs once a week. In this study, patients satisfying the criteria of TRD and depressive patients with active suicidal ideations, visiting the ketamine clinic who had given a valid informed consent for ketamine infusion enrolled and observed for ketamine efficacy by using specific scales. The study done over a period of 18 months from January 2020 till July 2021. Results: The response rate of ketamine in our study for treatment resistant depression was 70.27%. The response rate of ketamine for suicidality in our study was 63.16%. Our study showed a rapid onset of action for ketamine, two hours after ketamine infusion. Conclusions: A significant fraction of patients suffering from major depressive disorder do not respond to antidepressants and have a poor psychosocial functioning and an increased risk of suicide attempts making their condition life threatening. These patients therefore require special attention to address their underlying condition as well as suicidality to improve their outcome. In this context we studied the role of intravenous ketamine infusion in these patients in improving the psychosocial outcome as well as preventing the suicidal ideation.

Seasonal to Inter-annual Climate Prediction Using Data Mining KNN TYechnique”,

Abstract. The impact of seasonal to inter-annual climate prediction on society, business, agriculture and almost all aspects of human life, force the scientist to give proper attention to the matter. The last few years show tremendous achievements in this field. All systems and techniques developed so far, use the Sea Surface Temperature (SST) as the main factor, among other seasonal climatic attributes. Statistical and mathematical models are then used for further climate predictions. In this paper, we develop a system that uses the historical weather data of a region (rain, wind speed, dew point, temperature, etc.), and apply the data-mining algorithm "K-Nearest Neighbor (KNN)" for classification of these historical data into a specific time span. The k nearest time spans (k nearest neighbors) are then taken to predict the weather. Our experiments show that the system generates accurate results within reasonable time for months in advance

Pavement Marking as a Means of Traffic Control Device for an Urban Intersection as per Indian Practice

Road markings are an integral part of our road geometrics but are unfortunately being considered as passive traffic control devices. These can actually be used as a means of Intersection control. Polo-View intersection lies in the heart of Srinagar city which is the summer capital of the state of Jammu & Kashmir in India. This intersection is a place of main commercial activity of the state (Central Business District) and has a historic, cultural and tourism importance .A detailed investigation of the said intersection is done and all the parameters are calculated and evaluated. Based upon the traffic flow there are many possible solutions to the Intersection Control. As all the software’s which are used to evaluate different options of Intersection design like PTV Vissim are not applicable in India, therefore traditional Traffic flow curves between major and minor roads are used for evaluations. Based upon these curves there are many solutions and each one is weighted. Traffic markings are an integral part of every road , therefore there respect and compliance are the pre-requisites for harmonious flow conditions, when these things are integrated with effective markings these form an important form of intersection design. We have aimed at designing these different possible Intersection types and then suggesting the best out of them as well as their long term implications. We have also taken into account how the Autonomous Vehicles may change the type of Intersection control