An Intensive Spectrum for Intention Mining Analysis

There is huge volume of data in the social networks. This data can be retrieved and integrated to extract useful meaning and come out with the insights which is called as intentions. This can be used in different fields like business, recommender systems, education, Scientific research, games, etc. Also, there are various intention mining techniques which can be applied to several fields as information retrieval, business, etc. There is no specific definition of intention mining and also there is very less existing literature present. Accordingly, there is need to conduct systematic literature review of the very recent research area. Understanding intention mining, purpose of intention mining, categories and techniques of intention mining is the need. The paper endorses a spectrum for intention mining so that further literature review of intention mining can be completed. We validate our work through dimensions, categories and techniques for intention mining

Understanding the Order of 500 and 1000 Rupees Notes Ban using Reinforcement Learning

In the field of machine learning called reinforcement learning, complicated sequential decision-making problems have been addressed. The issue that arises when an agent learns behavior by trial-and-error runs to determine the ideal policy, or the sequence of behaviors so that rewards are maximized,is known as reinforcement learning. Because many reinforcement learning methods use dynamic programming approaches, the environment is characterized as a Markov Decision Process (MDP). The research presents reinforcement learning using Bigram, trigram, and 4-gram models for tweets collected for "500 and 1000 notes banned." A multistage graph problem is used to draw the graph and the Bayes method is used to compute the probabilities. For the given word sequence, it determines the shortest route between source and destination. After that, the path is defined by the agent's randomly selected states and actions, which are subsequently followed to receive rewards. Epsilon greedy selection mode randomly chooses an action to explore the environment

GC-MS and FTIR analysis of methanolic leaf extract of Rhynchosia minima (L.) DC.

The current analysis was carried out to determine the chemical components in the leaves of R. minima (L.) DC. The GC-MS analysis of methanolic leaves extract of R. Minima indicated the presence of 19 compounds. The prevailing compounds of R. minima leaves were 1Pentadecene (14.31), alpha. Bisabolol (10.39%), 1Heptadecene (9.78%), Cyclohexene,4 (1,5dimethyl1,4hexadienyl (7.06%), 3Hexadecene (Z) (8.10%), Caryophyllene (6.58%), Neophytadiene (5.16%), Humulene (1.91%), Naphthalene,1,2,3,5,6,8 a-hexahydro-4,7-dimethyl (3.72%), Hexadecanoic acid, methyl ester (2.09%), Pentadecanone (3.13%), 8-Octadecanone (4.02%),1-Nonadecene (4.16%), Spiro[4.5]dec-6-en-8-one,1,7-dimethyl-4-(1-methylethyl (2.97%), Neophytadiene (2.24%),(E)-. beta.-Famesene (1.92%), Cyclohexene,4-[(1E)-1,5-dimethyl-1,4-hexadien (1.80%), Cyclohexane,octyl (1.45%), beta Bisabolene (9.21%). These compounds have antibacterial, antifungal, antioxidant, hemolytic, insecticidal, and lubricant activity. Fourier Transform Infra-Red Spectroscopy (FTIR) leaf anlysis of R. minima shows lipid, protein, phosphate ion, carboxylic acid, hydroxy compound, aliphatic bromo compounds. The present study revealed that R. minima leaves represent various types of bioactive compounds. 1-Heptadecene with antibiotic activity, 8-Octadecanone shows antimicrobial activity and hexadecanoic acid, nematicide, antibiotic, antioxidant, hypocholesterolemic production of methyl ester

Randomized Clinical Trial of High-Dose Rifampicin With or Without Levofloxacin Versus Standard of Care for Pediatric Tuberculous Meningitis: The TBM-KIDS Trial

Background. Pediatric tuberculous meningitis (TBM) commonly causes death or disability. In adults, high-dose rifampicin may reduce mortality. The role of fluoroquinolones remains unclear. There have been no antimicrobial treatment trials for pediatric TBM. Methods. TBM-KIDS was a phase 2 open-label randomized trial among children with TBM in India and Malawi. Participants received isoniazid and pyrazinamide plus: (i) high-dose rifampicin (30 mg/kg) and ethambutol (R30HZE, arm 1); (ii) high-dose rifampicin and levofloxacin (R30HZL, arm 2); or (iii) standard-dose rifampicin and ethambutol (R15HZE, arm 3) for 8 weeks, followed by 10 months of standard treatment. Functional and neurocognitive outcomes were measured longitudinally using Modified Rankin Scale (MRS) and Mullen Scales of Early Learning (MSEL). Results. Of 2487 children prescreened, 79 were screened and 37 enrolled. Median age was 72 months; 49%, 43%, and 8% had stage I, II, and III disease, respectively. Grade 3 or higher adverse events occurred in 58%, 55%, and 36% of children in arms 1, 2, and 3, with 1 death (arm 1) and 6 early treatment discontinuations (4 in arm 1, 1 each in arms 2 and 3). By week 8, all children recovered to MRS score of 0 or 1. Average MSEL scores were significantly better in arm 1 than arm 3 in fine motor, receptive language, and expressive language domains (P < .01). Conclusions. In a pediatric TBM trial, functional outcomes were excellent overall. The trend toward higher frequency of adverse events but better neurocognitive outcomes in children receiving high-dose rifampicin requires confirmation in a larger trial. Clinical Trials Registration. NCT02958709

COMPARISON OF CLASSIFIERS FOR SENTIMENT ANALYSIS

The need of social media has vividly changed people’s life with more and more sharing their thoughts, expressing opinions, and in the hunt for support on social media websites such as Twitter, Facebook, blogs etc. Twitter, an online social networking and micro bloggingservice, which enables users to send and read text-based posts, known as tweets, with 140-character limit. Newspapers and blogs express opinion of news entities (people, places, things) while exposure to recent events. We present a system which extracts the sentiments from the online posts of twitter about news event. Our system shows sentiment identification, which expresses opinion associated with each entity. Also it consists of scoring phase, which assigns scores to each entity, on which the tweets are classified. Finally, we compare Maximum Entropy, Decision tree, Support vector machine and NaivesBayes classifiers

Comparison of Classifiers for Sentiment Analysis

The need of social media has vividly changed people's life with more and more sharing their thoughts, expressing opinions, and in the hunt for support on social media websites such as Twitter, Facebook, blogs etc. Twitter, an online social networking and micro bloggingservice, which enables users to send and read text-based posts, known as tweets, with 140-character limit. Newspapers and blogs express opinion of news entities (people, places, things) while exposure to recent events. We present a system which extracts the sentiments from the online posts of twitter about news event. Our system shows sentiment identification, which expresses opinion associated with each entity. Also it consists of scoring phase, which assigns scores to each entity, on which the tweets are classified. Finally, we compare Maximum Entropy, Decision tree, Support vector machine and NaivesBayes classifiers

Ultrasound-assisted, green and efficient synthesis of ferrocene-appended azo-phenothiazines

An effortless and highly efficient strategy for the synthesis of ferrocene-appended azo-phenothiazines (PHz's) under ultrasound irradiation has been developed. The said protocol allows for a more environmentally friendly approach, such as operationally simple, tolerates a wide range of functional groups compared to conventional methods, and is applicable on a gram scale without additional purification or other solvent waste. The synthesized compounds 6(aa-ec) were tested for their antimicrobial activity in vitro. Off all the compounds tested, 6ca and 6da showed maximum antibacterial against S. enteric and Bacillus cereus as well as excellent antifungal activity against A. flavus and A. fumigatus

Transparency in Algorithmic Decision-making: Interpretable Models for Ethical Accountability

Concerns regarding their opacity and potential ethical ramifications have been raised by the spread of algorithmic decisionmaking systems across a variety of fields. By promoting the use of interpretable machine learning models, this research addresses the critical requirement for openness and moral responsibility in these systems. Interpretable models provide a transparent and intelligible depiction of how decisions are made, as opposed to complicated black-box algorithms. Users and stakeholders need this openness in order to understand, verify, and hold accountable the decisions made by these algorithms. Furthermore, interpretability promotes fairness in algorithmic results by making it easier to detect and reduce biases. In this article, we give an overview of the difficulties brought on by algorithmic opacity, highlighting how crucial it is to solve these difficulties in a variety of settings, including those involving healthcare, banking, criminal justice, and more. From linear models to rule-based systems to surrogate models, we give a thorough analysis of interpretable machine learning techniques, highlighting their benefits and drawbacks. We suggest that incorporating interpretable models into the design and use of algorithms can result in a more responsible and moral application of AI in society, ultimately benefiting people and communities while lowering the risks connected to opaque decision-making processes

Lasers in endodontics review

Lasers have been a significant advancement in the field of endodontics. Be it effective cleaning, root canal treatment, surgery etc. The lateral accessory canals and anatomical complexities have been a restraint in root canal procedure, for such cases lasers have been introduced to simplify the process &amp; have good clinical results. As there has been a boon in the improvement of laser techniques, many latest lasers having a broad array of characteristics is accessible and can also be helpful in several areas related to dentistry. When compared with conventional techniques, laser treatments have been proven to be more advantageous. The purpose of this article is to summarize laser applications in endodontics, including their use in pulp diagnosis, dentinal hypersensitivity, pulp capping and pulpotomy, sterilization of root canals, root canal shaping &amp; obturation &amp; apicectomy. This article reviews the role of lasers in endodontics since the early 1970s &amp; summarizes what future may hold for endodontics. With the potential availability of many new laser wavelengths and modes, much interest is developing in this promising field

Stability-Indicating Reverse-Phase High-Performance Liquid Chromatographic Method Development and Validation of Lamotrigine in Bulk and Pharmaceutical Dosage Form

In the current study, analytical method has been validated by system suitability parameters, linearity, accuracy and percent recovery, precision, ruggedness, robustness, limit of detection, and limit of quantification. The present study of lamotrigine was achieved using Cosmosil C18 (250 nm×4.6 ID, particle size: 5 Micron) Column with mobile phase methanol: water (60:40) pH: 3 at a flow rate 0.8 ml/min with UV detection at 308 nm. The retention time for lamotrigine was found to be 4.979 min. In linearity, the correlation coefficient (R2) for lamotrigine was found to be 0.999, slope is 39,801, and intercept was found to be 51,862 which are well within the acceptance criteria. The mean percent recovery for lamotrigine at three different levels for 50%, 100%, and 150% was found to be 99.28%, 99.30%, and 100.40%. The % RSD should not more than 2%. In precision study, interday (RSD is 0.41%) and intraday (RSD is 0.26%) are found. Forced degradation experiments were carried out by exposing standard form of lamotrigine for acid-base, oxidative, photolytic, and thermal stress conditions. Hence, the developed method is accurate, precise, repeatable, and reproducible and can be used for routine analysis of lamotrigine