2,088 research outputs found

    Turbulent Fluid Flow Over Aerodynamically Rough Surfaces Using Direct Numerical Simulations

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    Incompressible turbulent fluid flow in aerodynamically rough channels is investigated using direct numerical simulations. A comprehensive database of simulation data for rough surfaces with different topographical properties has been developed for 17 industrially relevant rough surface samples. It includes numerous commonlyseen industrial rough surfaces such as concrete, graphite, carbon-carbon composite and ground, shotblasted and spark-eroded steel. Other surfaces such as cast, filed and gritblasted steel are also studied, along with replicas of ship propeller surfaces eroded by periods of service. The Reynolds number considered is Reτ = 180, for which the flow is in the transitionally rough regime. A study with variable δ/Sq ratio while keeping S + q constant, where Sq is the root mean squared roughness height, is conducted for one of the samples with the mean profiles showing convergence for δ/Sq >≈ 25. A Reynolds number dependence study is conducted for two of the samples with Reτ up to 720 showing a more complete range up to the fully rough flow regime, allowing the equivalent sandgrain roughness height, ks to be computed. A correlation based on the frontal and wetted roughness area is found to be superior to the surface skewness in predicting ∆U + based on the topographic surface parameters

    Uterine volume measurement as a determinant in route of hysterectomy

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    Background: Objectives of the study were to determine the role of uterine volume rather than uterine length in assessing the route of hysterectomy; to estimate the cut-off of uterine volume for route of hysterectomy; and to correlate uterine volume measured preoperatively by ultrasound with post-operative uterine weight.Methods: This was a prospective observational study including a total of 101 women who underwent hysterectomies (vaginal, laparascopic assisted vaginal hysterectomy (LAVH), total laparascopic hysterectomy (TLH), abdominal) in a period of 2 years 2 months from July 2018 to August 2020 in Mehta Multispeciality Hospital, Chetpet, Chennai. Uterine size was measured by clinical examination. Ease of the procedure with various uterine volume and routes of hysterectomy were studied.Results: 51 (50.49%) underwent vaginal route (including laparascopic hysterectomy), 50 (49.50%) underwent abdominal hysterectomy. Mean uterine volume leading to removal vaginally was 168.09±139.28 cc whereas 309.12±182.47 cc for abdominal hysterectomy (p=0.001) which was statistically significant. vaginal hysterectomy was done without difficulty up to 300 cc. Postoperative complications were less with vaginal hysterectomy compared to abdominal hysterectomy was statistically significant (p=0.0001).Uterine volume measured pre operatively by ultrasound showed positive correlation (r=0.82) with post-operative uterine weight proved that uterine volume measurements was superior to the clinical estimate of uterine size in assessing the route of hysterectomy.Conclusions: Uterine volume on ultrasonography (USG) can be a good predictor in deciding whether hysterectomy via vaginal route is possible.

    Environmental Balance Through Optimal Control on Pollutants

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    Pollution, which is a very common term has been divided as primary pollutants and secondary pollutants. Primary pollutants are those who results directly from some process whereas secondary pollutants are caused due to intermixing and reaction of primary pollutants. These pollutants result into acid rain. In this paper, a mathematical model has been developed to study the environmental impact due to acid rain. Pollutants such as primary and secondary pollutants are the causes of acid rain. Control in terms of gases emitted by factories, smog, burning of coal and fossil fuels have been applied on primary pollutants, secondary pollutants and acid rain to have an ecofriendly environment. Stability for the equilibrium points have been worked out. Simulation of the model has been carried out, which shows that there can be a clean environment if all the necessary steps are taken care of to curb this problem

    Antimutagenic Potential of Probiotic Lactobacillus sporogenes Using Ames assay

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    Objective: Probiotic are beneficial microbial nutrition supplements which have useful effects on human health by conserving of bowel microbial balance. There are many studies that have been recommended the use of probiotic products as cancer risk reducer. The aim of present study was to investigate antimutagenic potential of Probiotic Lactobacillus sporogenes against TA98 and TA100 strain of Salmonella typhimurium.Material and Methods: Ames test was used in the present investigation to evaluate antimutagenic activity in TA98 and TA100 strains of Salmonella typhimurium using direct acting mutagens (Sodium azide) and different concentration of Probiotic L.Sporogenes (25, 50, 100 and 500 μg/0.1 ml/plate).Results: Probiotic Lactobacillus sporogenes showed significant antimutagenicity against mutagen sodium azide in TA98 and TA100 tester strains whereas it showed antimutagenicity result in inhibition of 93-97% and 62-88% of his+ revertants induced by sodium azide in TA98 and TA100 strains respectively.Conclusion: The antimutagenicity of Probiotic Lactobacillus sporogenes the observed in the present study implies chemopreventive pharmacological importance of Probiotic Lactobacillus sporogenes and encourages its use as a biotherapeutic agent

    Antibodies to Enteroviruses in Cerebrospinal Fluid of Patients with Acute Flaccid Myelitis.

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    Acute flaccid myelitis (AFM) has caused motor paralysis in >560 children in the United States since 2014. The temporal association of enterovirus (EV) outbreaks with increases in AFM cases and reports of fever, respiratory, or gastrointestinal illness prior to AFM in >90% of cases suggest a role for infectious agents. Cerebrospinal fluid (CSF) from 14 AFM and 5 non-AFM patients with central nervous system (CNS) diseases in 2018 were investigated by viral-capture high-throughput sequencing (VirCapSeq-VERT system). These CSF and serum samples, as well as multiple controls, were tested for antibodies to human EVs using peptide microarrays. EV RNA was confirmed in CSF from only 1 adult AFM case and 1 non-AFM case. In contrast, antibodies to EV peptides were present in CSF of 11 of 14 AFM patients (79%), significantly higher than controls, including non-AFM patients (1/5 [20%]), children with Kawasaki disease (0/10), and adults with non-AFM CNS diseases (2/11 [18%]) (P = 0.023, 0.0001, and 0.0028, respectively). Six of 14 CSF samples (43%) and 8 of 11 sera (73%) from AFM patients were immunoreactive to an EV-D68-specific peptide, whereas the three control groups were not immunoreactive in either CSF (0/5, 0/10, and 0/11; P = 0.008, 0.0003, and 0.035, respectively) or sera (0/2, 0/8, and 0/5; P = 0.139, 0.002, and 0.009, respectively).IMPORTANCE The presence in cerebrospinal fluid of antibodies to EV peptides at higher levels than non-AFM controls supports the plausibility of a link between EV infection and AFM that warrants further investigation and has the potential to lead to strategies for diagnosis and prevention of disease

    Sentimental Analysis of Social Media Using R language and Hadoop

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    The way of expressing people’s views, opinions and Sentiments about others has been changed due to the growth of Technology of World Wide Web. Mostly people use blogs, Social sites, online discussions etc. for expressing their views. Massive amount of data is generated because of this. Companies face many problems in storing this massive data. This paper helps in analysis of sentiments of the data fetched from twitter using R language which either collects the information in the form of positive, negative or neutral score. After this the fetched data is pre-processed i.e. all the slang words, misspelled words etc. are removed. Using R language and Hadoop Connector we perform the analysis of twitter data which has size of TB’s also known as big data. R language and Hadoop tool are the two different platforms on which the performance estimation will be based on
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