Comparison of NALC-NAOH processing method with C18-carboxy propyl betaine method for the detection of mycobacterium in sputum

Background: Tuberculosis is an infectious disease which remains to be a major public health risk worldwide even after the availability of many highly sensitive diagnostic tools. Early case detection plays an important role in control of the disease which relies solely on the detection of acid-fast bacilli in clinical samples which is low sensitive. Prior decontamination of sputum sample may improve the detection of mycobacterium.Methods: A prospective study was conducted with a total of (N=464) clinically suspected TB patient sputum samples which were collected and processed directly for AFB. From which AFB +ve samples were excluded. The direct AFB-ve (N=279) samples were processed using concentration (NALC, CB-18) and culture (LJ medium). After concentration, smears were examined under oil immersion for acid fast bacilli by ZN staining.Results: Out of 464 sputum samples, 185 direct ZN stain +ve were excluded. Among the ZN-ve (N=279) samples, N= 48 (17.2%) were positive using NALC-NaOH method. The positivity has improved to N=69 (25%) using CB-18 and N=79 (28.3%) using culture (LJ medium).Conclusions: CB-18 is sensitive than NALC-NaOH method and its sensitivity is almost comparable to the gold standard culture using LJ medium. Therefore we conclude that the identification of AFB using CB-18 concentration method can be used in resource limited health care setups which might help us to diagnose the TB at the earliest

A State-of-the-Art Review of Time Series Forecasting Using Deep Learning Approaches

Time series forecasting has recently emerged as a crucial study area with a wide spectrum of real-world applications. The complexity of data processing originates from the amount of data processed in the digital world. Despite a long history of successful time-series research using classic statistical methodologies, there are some limits in dealing with an enormous amount of data and non-linearity. Deep learning techniques effectually handle the complicated nature of time series data. The effective analysis of deep learning approaches like Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Long short-term memory (LSTM), Gated Recurrent Unit (GRU), Autoencoders, and other techniques like attention mechanism, transfer learning, and dimensionality reduction are discussed with their merits and limitations. The performance evaluation metrics used to validate the model's accuracy are discussed. This paper reviews various time series applications using deep learning approaches with their benefits, challenges, and opportunities

NOTATIONAL ANALYSIS OF PLAYING ABILITY ON MEN HANDBALL TEAMS

The purpose of the study was to assess the playing ability by notational analysis system for men handball players. To achieve the purpose of the study the four teams those who participated in the Madurai Kamaraj University Inter-Collegiate Handball Tournament 2017-18 for men were selected. The teams were SVN College, American College, Arul Anandar College and Madurai Kamaraj University, Madurai. The age of the men handball players ranged from 18 to 24 years. The following match analysing factors which are expected to give the complete performance of the team & individual five factors were finalized. A panel of experts consisting of coaches, players and experts as well as fellow researchers aided in the development and ranking of performance scores for the effects of each skill as it is performed during the game. Each attempt was noted according to whether the attempt was off-target, on-target, or resulted in a goal. The pass was evaluated according to the result, such as if the other team intercepted the pass or it resulted in a scoring opportunity. Cards received by the players, penalty shoot were carefully noted. The data was collected during the real time match. The collected data were analysed statistically using mean and standard deviation. The outcome of the study might act as a tool to analyse the team & individual performance in the game of Handball

Examining public sentiments and attitudes toward COVID-19 vaccination: infoveillance study using Twitter posts

Background: A global rollout of vaccinations is currently underway to mitigate and protect people from the COVID-19 pandemic. Several individuals have been using social media platforms such as Twitter as an outlet to express their feelings, concerns, and opinions about COVID-19 vaccines and vaccination programs. This study examined COVID-19 vaccine–related tweets from January 1, 2020, to April 30, 2021, to uncover the topics, themes, and variations in sentiments of public Twitter users. Objective: The aim of this study was to examine key themes and topics from COVID-19 vaccine–related English tweets posted by individuals, and to explore the trends and variations in public opinions and sentiments. Methods: We gathered and assessed a corpus of 2.94 million COVID-19 vaccine–related tweets made by 1.2 million individuals. We used CoreX topic modeling to explore the themes and topics underlying the tweets, and used VADER sentiment analysis to compute sentiment scores and examine weekly trends. We also performed qualitative content analysis of the top three topics pertaining to COVID-19 vaccination. Results: Topic modeling yielded 16 topics that were grouped into 6 broader themes underlying the COVID-19 vaccination tweets. The most tweeted topic about COVID-19 vaccination was related to vaccination policy, specifically whether vaccines needed to be mandated or optional (13.94%), followed by vaccine hesitancy (12.63%) and postvaccination symptoms and effects (10.44%) Average compound sentiment scores were negative throughout the 16 weeks for the topics postvaccination symptoms and side effects and hoax/conspiracy. However, consistent positive sentiment scores were observed for the topics vaccination disclosure, vaccine efficacy, clinical trials and approvals, affordability, regulation, distribution and shortage, travel, appointment and scheduling, vaccination sites, advocacy, opinion leaders and endorsement, and gratitude toward health care workers. Reversal in sentiment scores in a few weeks was observed for the topics vaccination eligibility and hesitancy. Conclusions: Identification of dominant themes, topics, sentiments, and changing trends about COVID-19 vaccination can aid governments and health care agencies to frame appropriate vaccination programs, policies, and rollouts. [Abstract copyright: ©Ranganathan Chandrasekaran, Rashi Desai, Harsh Shah, Vivek Kumar, Evangelos Moustakas. Originally published in JMIR Infodemiology (https://infodemiology.jmir.org), 15.04.2022.

Modeling Tag Prediction based on Question Tagging Behavior Analysis of CommunityQA Platform Users

In community question-answering platforms, tags play essential roles in effective information organization and retrieval, better question routing, faster response to questions, and assessment of topic popularity. Hence, automatic assistance for predicting and suggesting tags for posts is of high utility to users of such platforms. To develop better tag prediction across diverse communities and domains, we performed a thorough analysis of users' tagging behavior in 17 StackExchange communities. We found various common inherent properties of this behavior in those diverse domains. We used the findings to develop a flexible neural tag prediction architecture, which predicts both popular tags and more granular tags for each question. Our extensive experiments and obtained performance show the effectiveness of our modelComment: 20 page

Effect on extracts of Stevia rebaudiana bertoni. in ethanol induced gastric ulcer by using wister rats

The sweet herb of Paraguay, Stevia rebaudiana Bertoni produces, in its leaves, just such an alternative with the added advantage that Stevia sweeteners are natural plant products. In addition, the sweet steviol glycosides have functional and sensory properties superior to those of many other high potency sweeteners. The PESR, EESR & AESR has investigated the anti ulcerogenic activity by using Wister rats in both sexes. Oral administration of petroleum ether, ethanol & aqueous extracts of S. rebaudiana (100 & 300 mg, p.o) produced a significant (