Smart grid-Power factor Correction and Maintenance in Consumer Side Using RFID Based Power Line Carrier

Smart grid is a grouping of information and communication technology and intelligent common infrastructure. Talking about smart grid the  consumers and suppliers are very much important inorder to manage,monitor and control all energy issuses smartly. Easy instalation and high reliablity data communication over power line carrier is an important  requirment to make a smart grid more constructive than fixed grid system.Therefore  a latest RFID based power line technology has been developed unlike conventional system carrying data through antenna. RFID based power line carrier technology is used for detection and payment inorder to keep up the grid smart. With this technology, power factor correction and maintanance techniques are included inorder to improve the power system stability. Whenever the non-linear load is connected in load side, the proposed system will automatically detect and connect the power factor correction circuit(capacitor bank) for maintain the  power factor in consumer side

MITIGATE THE REAL POWER LOSSES IN RADIAL DISTRIBUTED NETWORK USING DG BY ABC ALGORITHM

Recently, integration of Distributed generation (DG) in distribution system has increased to high penetration levels. The impact of DG on various aspects of distribution system operation, such as reliability and energy loss depend highly on DG location in distribution feeder .Optimal DG placement plays an important role . This project presents a new methodology using Artificial Bee Colony  algorithm (ABC) to find the optimal size and optimum location for the placement of DG in the radial distribution networks for active power compensation by reduction in real power losses .The proposed technique is tested on standard IEEE-33 bus test system

Comparative analysis of salivary microbiome in oral squamous cell carcinoma patients and healthy individuals using 16S rRNA sequencing

BACKGROUND: Oral microbiome and chronic inflammation are known to influence carcinogenesis. Many studies are ongoing to ascertain the relationship between oral microbiome, inflammation and oral cancer. This study was done to ascertain the oral microbiome in the saliva of Oral Squamous Cell Carcinoma (OSCC) and healthy individuals using 16S rRNA gene sequencing. AIM AND OBJECTIVES: To ascertain the oral microbiome in saliva samples of OSCC patients and healthy individuals using 16S rRNA gene sequencing of bacteria with BLAST (Basic Local Alignment Search Tool) analysis in NCBI (National Centre for Biotechnology Information) database and to quantify the concentration of DNA extracted from bacterial cells using QUBITTM Fluorometer. MATERIALS AND METHODS: Saliva from ten OSCC patients and ten healthy individuals (controls) were collected. DNA was extracted from the saliva samples and then subjected to 16S rRNA gene sequencing to assess the oral microbiome between the two groups. RESULTS: A total of 19 phyla were identified of which Proteobacteria (39%), Firmicutes (22%), Actinobacteria (15%) and Bacteroidetes (12%) were the major phyla. The most prevalent bacteria present in OSCC patients were Bacillus, Bacterium, Buchnera, Caulobacter, Clostridium, Corynebacterium, Desulfutomaculum, Enterococcus, Flavobacterium, Gemmata, Hymenobacter, Lactobacillus, Listeria, Lysinibacillus, Marinifilum, Ruminococcus, Streptococcus, Streptomyces, Thermoanaerobacter. In healthy individuals the prevalent bacteria were Bacillus, Enterococcus, Lactobacillus, Massilia, Paenibacillus, Streptococcus. The predominant bacteria that were common in OSCC patients and in healthy individuals are Bacillus, Enterococcus, Lactobacillus and Streptococcus. CONCLUSION: The oral microbiome is complex and our study shows that there are differences in the microbiome of OSCC subjects and healthy individuals. The data from this study will help us to identify the species which need to be studied further to ascertain their role in oral carcinogenesis

A Self-Diagnosis Medical Chatbot Using Artificial Intelligence

To lead a good life healthcare is very much important. But it is very difficult to obtain the consultation with the doctor in case of any health issues. The proposed idea is to create a medical chatbot using Artificial Intelligence that can diagnose the disease and provide basic details about the disease before consulting a doctor .To reduce the healthcare costs and improve accessibility to medical knowledge the medical chatbot is built. Certain chatbots acts as a medical reference books, which helps the patient know more about their disease and helps to improve their health. The user can achieve the real benefit of a chatbot only when it can diagnose all kind of disease and provide necessary information. A text-to-text diagnosis bot engages patients in conversation about their medical issues and provides a personalized diagnosis based on their symptoms. Hence, people will have an idea about their health and have the right protection

Modelling the elements of flash flood hydrograph using genetic programming

1031-1038A novel approach is proposed in this work on constructing the flash flood hydrograph by modelling the elements of the hydrograph namely the time to start of the initial flood (ti), the time to peak discharge (tp), the peak discharge (Qp) and the base time (tb) using Genetic Programming (GP). The proposed method is applied to the Kickapoo River catchment in Wisconsin, USA. It is demonstrated that even under limited data scenario, for a poorly gauged station, GP is able to model the elements of hydrograph with reasonably high accuracy thereby offering considerable lead time to predict the flash flood. The mathematical models developed by GP also offer some understanding of the influence of rainfall events and the stream discharge in producing the flash floods

Immune indices and identical functions of two prophenoloxidases from the haemolymph of green tiger shrimp Penaeus semisulcatus and its antibiofilm activity

In the present study, we purified two prophenoloxidases (proPO) from haemolymph of green tigershrimp,Penaeus semisulcatusby gel fermentation chromatography using blue Sepharose matrix. The twopurified prophenoloxidase macromolecules are of about 76 and 75 kDa determined through SDS-PAGEand named asPenaeus semisulcatusprophenoloxidase I (PSproPO I) andPenaeus semisulcatusproph-enoloxidase II (PSproPO II). It was further characterized by X-Ray Diffraction (XRD), Fourier TransformInfrared Spectroscopy (FTIR), Circular Dichroism (CD) and High Performance Liquid Chromatography(HPLC) analysis. The purified PSproPO I and PSproPO II showed the strongest agglutination titre againsthuman erythrocytes compared to goat RBC. The PSproPO I and PSproPO II showed phagocytic activityagainst yeastSaccharomyces cerevisiaeand encapsulation activity against Sepharose CL 6B beadscompared to CM Sepharose and Sodium alginate beads. The functional analysis of purified PSproPO I andPSproPO II showed enhanced PO activity when added with the triggering molecules such as pathogenassociated molecular patterns (PAMPs), metals and chemicals. In addition, eluted fraction containingPSproPO I and PSproPO II showed antibiofilm activity against Gram positive and Gram negative bacteria.The above results concluded that no significant differences were found between the purified PSproPO Iand PSproPO II immune indices and functions. This study might provide a sensitive platform to under-stand more about the critical roles of PSproPO I and PSproPO II in crustacean immune syste

Multiple Genome Wide Association Mapping Models Identify Quantitative Trait Nucleotides for Brown Planthopper (Nilaparvata lugens) Resistance in MAGIC Indica Population of Rice

Brown planthopper (BPH), one of the most important pests of the rice (Oryza sativa) crop, becomes catastrophic under severe infestations and causes up to 60% yield loss. The highly disastrous BPH biotype in the Indian sub-continent is Biotype 4, which also known as the South Asian Biotype. Though many resistance genes were mapped until now, the utility of the resistance genes in the breeding programs is limited due to the breakdown of resistance and emergence of new biotypes. Hence, to identify the resistance genes for this economically important pest, we have used a multi-parent advanced generation intercross (MAGIC) panel consisting of 391 lines developed from eight indica founder parents. The panel was phenotyped at the controlled conditions for two consecutive years. A set of 27,041 cured polymorphic single nucleotide polymorphism (SNPs) and across-year phenotypic data were used for the identification of marker–trait associations. Genome-wide association analysis was performed to find out consistent associations by employing four single and two multi-locus models. Sixty-one SNPs were consistently detected by all six models. A set of 190 significant marker-associations identified by fixed and random model circulating probability unification (FarmCPU) were considered for searching resistance candidate genes. The highest number of annotated genes were found in chromosome 6 followed by 5 and 1. Ninety-two annotated genes identified across chromosomes of which 13 genes are associated BPH resistance including NB-ARC (nucleotide binding in APAF-1, R gene products, and CED-4) domain-containing protein, NHL repeat-containing protein, LRR containing protein, and WRKY70. The significant SNPs and resistant lines identified from our study could be used for an accelerated breeding program to develop new BPH resistant cultivars