Spammers Detection on Twitter by Automated Multi Level Detection System

Twitter is one of the most well known micro-blogging administrations, which is commonly used to share news and updates through short messages confined to 280 characters. In any case, its open nature and huge client base are every now and again misused via robotized spammers, content polluters, and other not well expected clients to carry out different cyber violations, for example, cyber bullying, trolling, rumor dissemination, and stalking. Likewise, various methodologies have been proposed by specialists to address these issues. Nonetheless, the majority of these methodologies depend on client portrayal and totally dismissing shared communications. In this examination, we present a hybrid methodology for recognizing mechanized spammers by amalgamating network based features with other feature classifications, to be specific metadata-, content-, and association based features. The curiosity of the proposed methodology lies in the portrayal of clients dependent on their communications with their supporters given that a client can dodge features that are identified with his/her very own exercises, yet sidestepping those dependent on the devotees is troublesome. Nineteen distinct features, including six recently characterized features and two re-imagined features, are distinguished for learning three classifiers, in particular, irregular woods, choice tree, Bayesian system, and example pre-handling on a genuine dataset that involves generous clients and spammers. The separation intensity of various feature classifications is additionally broke down, and cooperation and network based features are resolved to be the best for spam identification, though metadata-based features are demonstrated to be the least compelling

Finite Element Analysis of Wire Drawing Process with different die contours

Finite element method is a numerical analysis tool for analyzing complex problems. It was originally developed as a tool for structural, Thermal; fluent analysis and magnetic, electrical current flow analysis but the theory and formulation has been progressively gives approximate solutions. I have taken the problem of understanding wire drawing process from theory of pure plasticity and Avitzur’s theory of law’s ‘Wire Drawing through Conical Dies of small cone angles and large cone angles’ This theory was used to obtain the drawing load. Wire is drawn through dies with different die contours viz. plain die with die land, Convex die, Concave die. Hence I found  least wire drawing defects and die life increased. Loads were applying to the finite element model treating the problem to be axi symmetric. The problem to be solving by using ANSYS 10 classic  a popular FEA software package

A retrospective analysis of normal saline and lactated ringers as resuscitation fluid in sepsis

BackgroundThe Surviving Sepsis Campaign suggested preferential resuscitation with balanced crystalloids, such as Lactated Ringer’s (LR), although the level of recommendation was weak, and the quality of evidence was low. Past studies reported an association of unbalanced solutions, such as normal saline (NS), with increased AKI risks, metabolic acidosis, and prolonged ICU stay, although some of the findings are conflicting. We have compared the outcomes with the preferential use of normal saline vs. ringer’s lactate in a cohort of sepsis patients.MethodWe performed a retrospective cohort analysis of patients visiting the ED of 19 different Mayo Clinic sites between August 2018 to November 2020 with sepsis and receiving at least 30 mL/kg fluid in the first 6 h. Patients were divided into two cohorts based on the type of resuscitation fluid (LR vs. NS) and propensity-matching was done based on clinical characteristics as well as fluid amount (with 5 ml/kg). Single variable logistic regression (categorical outcomes) and Cox proportional hazards regression models were used to compare the primary and secondary outcomes between the 2 groups.ResultsOut of 2022 patients meeting our inclusion criteria; 1,428 (70.6%) received NS, and 594 (29.4%) received LR as the predominant fluid (>30 mL/kg). Patients receiving predominantly NS were more likely to be male and older in age. The LR cohort had a higher BMI, lactate level and incidence of septic shock. Propensity-matched analysis did not show a difference in 30-day and in-hospital mortality rate, mechanical ventilation, oxygen therapy, or CRRT requirement. We did observe longer hospital LOS in the LR group (median 5 vs. 4 days, p = 0.047 and higher requirement for ICU post-admission (OR: 0.70; 95% CI: 0.51–0.96; p = 0.026) in the NS group. However, these did not remain statistically significant after adjustment for multiple testing.ConclusionIn our matched cohort, we did not show any statistically significant difference in mortality rates, hospital LOS, ICU admission after diagnosis, mechanical ventilation, oxygen therapy and RRT between sepsis patients receiving lactated ringers and normal saline as predominant resuscitation fluid. Further large-scale prospective studies are needed to solidify the current guidelines on the use of balanced crystalloids

Catheter Ablation for Atrial Fibrillation in Patients With Concurrent Heart Failure

Due to limited real-world data, the aim of this study was to explore the impact of catheter ablation (CA) for atrial fibrillation (AF) in heart failure (HF). This retrospective cohort study identified 119,694 patients with AF and HF from the Nationwide Readmissions Database (NRD) from 2016 to 2017. Propensity-matching was generated using demographics, comorbidities, hospital and other characteristics through multivariate logistic regression. Greedy\u27s propensity score match (1:15) algorithm was used to create matched data. The primary end point was a composite of HF readmission and mortality at 1 year. Secondary outcomes include HF readmission, mortality, AF readmission, and any-cause readmission at 1 year. Of the 119,694 patients, 63,299 had HF with reduced ejection fraction (HFrEF), and 56,395 had HF with preserved ejection fraction (HFpEF). In the overall HFrEF cohort, the primary outcome was similar (HR, 95% confidence interval, p-value) (1.01, 0.91 to 1.13, 0.811). AF readmission (0.41, 0.33 to 0.49, \u3c0.001) and any readmission (0.87, 0.82 to 0.93, \u3c0.001) were reduced with CA. In the propensity-matched HFrEF cohort, results were unchanged (primary outcome: 1.10, 0.95 to 1.27, 0.189; AF readmission: 0.46, 0.36 to 0.59, \u3c0.001; any readmission: 0.89, 0.82 to 0.98, 0.015). In the overall HFpEF cohort, the primary outcome was similar (0.90, 0.78 to 1.04, 0.154). AF readmission was reduced with CA (0.54, 0.44 to 0.65, \u3c0.001). In the propensity-matched HFpEF cohort, results were unchanged (primary outcome 1.10, 0.92 to 1.31, 0.289; AF readmission 0.44, 0.33 to 0.57, \u3c0.001). CA did not reduce mortality and HF readmission at one year irrespective of the type of HF, but significantly reduce readmission due to AF