Synthesis and Characterization of Gold Nanoparticles

In this paper, Gold Nanoparticles (GNPs) has been successfully prepared by chemical reduction method (TERKEWISH method) using Sodium Citrate as reducing agent and by Green method using Fructose as reducing agent. The synthesized gold colloidal solution is characterized by using ZETA POTENTIAOMETER, FTIR and UV-VIS spectroscopy. Results of zeta shows that GNPs with sodium citrate have particle size of 119.5 nm (diameter) and have incipient stability. GNPs made with green method using fructose have particle size 50 nm (diameter) and have moderate stability. Results of FTIR are in good agreement to that has been explained in literature. Results of UV- VIS shows that GNPs with sodium citrate gives peak at 526 nm and GNPs made with green method using fructose gives peak at 520 nm, these results match with literature reviews

Properties and Applications of Gold Nanoparticles

In this paper, properties and applications of gold nanoparticles have been discussed. Gold nanoparticles exhibit outstanding optical properties. These properties show variations with size of gold nanoparticles and their surface features. Gold spheres with dimension greater than 20 nm exhibit purple color. They exhibit red color for 10-20 nm size and appears yellow at 2-5 nm dimension. Gold nanoparticles show single electron tunnelling which describes their excellent conductivity. Gold is non magnetic in bulk size but at nano dimension it shows magnetic behaviour due to change in magnetic coupling. Due to all these outstanding properties, gold nanoparticles have been utilized for various applications like biological tagging, biomedical imaging, catalysis, cancer therapy, food packaging and monitoring, scatterind based imaging, biosensors, sunscreen, drug delivery, DNA labelling etc

Role of Sodium Alginate in Gastroesophageal Reflux Disease: An Overview

Sodium alginate helps manage and treat heartburn and gastroesophageal reflux disease (GERD). This article discusses thestructure, mechanism of action and clinical application. A brief review of the literature is carried out

Pidotimod: An Immunity Booster

Pidotimod is a synthetic dipeptide, which has immunomodulatory property. It is used in recurrent upper respiratory tract infections, where there is nonspecific immune deficiency, especially in children who are more prone to recurrent respiratory infections. This article discusses its structure, pharmacokinetics including mechanism of action and clinical uses. A brief review of literature has been carried out. Possible future application is suggested

Performance-Based Analysis of Blockchain Scalability Metric

Cryptocurrencies like Bitcoin and Ethereum, are widely known applications of blockchain technology, have drawn much attention and are largely recognized in recent years. Initially Bitcoin and Ethereum processed 7 and 15 Transactions Per Second (TPS) respectively, whereas VISA and Paypal process 1700 and 193 TPS respectively. The biggest challenge to blockchain adoption is scalability, defined as the capacity to change the block size to handle the growing amount of load. This paper attempts to present the existing scalability solutions which are broadly classified into three layers: Layer 0 solutions focus on optimization of propagation protocol for transactions and blocks, Layer 1 solutions are based on the consensus algorithms and data structure, and Layer 2 solutions aims to decrease the load of the primary chain by implementing solutions outside the chain. We present a classification and comparison of existing blockchain scalability solutions based on performance along with their pros and cons

Effectiveness of Distraction Technique on Pain Reduction After Administration Subcutaneous Injection Among Children in Immunization Rooms

Pain is described as "an unpleasant, subjective sensory and emotional experience associated with existing or potential tissue damage, or described in terms of such damage," according to the International Association for the Study of Pain (IASP). Suffering results from untreated or ineffectively treated pain. The method of administering medication subcutaneously, which is frequently done by nurses, is associated with discomfort, pain, and injury to the tissue that is being injected. The primary goal of the study was to determine whether using a distraction approach helped children in the immunisation rooms of particular hospitals in Gurugram feel less discomfort after receiving a subcutaneous injection. Materials and Methods: 60 children were chosen by the purposive selection strategy from the hospital Gurugram's immunization rooms. The chosen individuals are then split into two equally sized groups. Results: In the assessment, the experimental group's mean score on the pre-facing rating scale was 6.93, while the control group's was 7.13, with an SD of 1.252. The experimental group's mean score on the post-faces rating scale is 2.00, whereas the control group's is 6.47, with a standard deviation of 1.548. Conclusion : The outcome demonstrates a movement in the sample's level of pain (hurts worse, hurts a lot, hurts a little more, hurts even more, hurts a little, doesn't hurt) in favour of the experimental group. When compared to the control group, it is because of the distraction strategy (an electronic moving toy)

Review Paper on Sentiment Analysis of The Demonetization of Economy

Sentiment analysis is one of the major tasks of NLP (Natural Language Processing). Sentiment analysis has increased the interest and attention of many researchers in recent years. Today online reviews of sentiment analysis on Demonetization has become a hot research field. Demonetization was a unique event for Indians which was organized by PM of India. On 8th nov,2016 PM of India declared a decision of Demonetization under which notes of 500 & 1000 were banned to tackle the problem of corruption, terrorist funding and black money. Sentiment analysis on Demonetization mainly focus on framework of lexicon construction, feature extraction, polarity determination, maximum entropy and SVM. This paper explains the survey on the latest development in sentiment analysis. The methods used in current research are especially emphasized to analysis the sentiments of Indians on Demonetization. Finally, in this paper we pointed out some possible future directions of research

Terzyme: a tool for identification and analysis of the plant terpenome.

Abstract Background Terpenoid hydrocarbons represent the largest and most ancient group of phytochemicals, such that the entire chemical library of a plant is often referred to as its ‘terpenome’. Besides having numerous pharmacological properties, terpenes contribute to the scent of the rose, the flavors of cinnamon and the yellow of sunflowers. Rapidly increasing -omics datasets provide an unprecedented opportunity for terpenome detection, paving the way for automated web resources dedicated to phytochemical predictions in genomic data. Results We have developed Terzyme, a predictive algorithm for identification, classification and assignment of broad substrate unit to terpene synthase (TPS) and prenyl transferase (PT) enzymes, known to generate the enormous structural and functional diversity of terpenoid compounds across the plant kingdom. Terzyme uses sequence information, plant taxonomy and machine learning methods for predicting TPSs and PTs in genome and proteome datasets. We demonstrate a significant enrichment of the currently identified terpenome by running Terzyme on more than 40 plants. Conclusions Terzyme is the result of a rigorous analysis of evolutionary relationships between hundreds of characterized sequences of TPSs and PTs with known specificities, followed by analysis of genome-wide gene distribution patterns, ontology based clustering and optimization of various parameters for building accurate profile Hidden Markov Models. The predictive webserver and database is freely available at http://nipgr.res.in/terzyme.html and would serve as a useful tool for deciphering the species-specific phytochemical potential of plant genomes

Impact of Random, Uniform node placement and Grid environment on the Performance of Routing Protocols in MANET

An ad-hoc network is frequently represented as a group of mobile platforms or nodes where each node can move freely and randomly without the benefit of any fixed infrastructure except for the nodes themselves. They are often autonomous, self-configuring, and adaptive. Each node in an ad hoc network is in charge of routing information between its neighbors, thus imparting to and holding connectivity of the network. MANET has to face many challenges in various aspects; one of the future challenges is terrain size and node placement. Here, performance of two popular protocols in MANET i.e. AODV and DSDV is evaluated under three different node placements namely Random, Uniform and Grid using GLOMOSIM simulator. The performance analysis is based on different values of Radio Range in network and different network metrics such as Packet Delivery Ratio (PDR) and Average Delay