Finding Frequent Text-Patterns on Big Data using Visualisation Techniques

Big Data has got more importance in various industries over the last couple of years, which is applied on various huge and large data sets because it cannot be stored and process through traditional databases. Big data has huge potential to store and process such huge and large datasets in several ways because, during processing, we are analyzing the large datasets in required time. Text analysis is still somewhat in its infancy but is very promising. Because in most of the companies 80% of data is in unstructured form, while most types of analysis only work with structured data. In this paper, we are discussing some visualization techniques available for Big data. Finally, R package is used to analyze unstructured text because R is freely available and it comes with lots of free packages and powerful tools through which we can easily analyze the large data sets in a sufficient time

Optimization of Energy Aware Path Routing Protocol in Wireless Sensor Networks

Strength conservation is one of the biggest challenges to the successful WSNs since the tiny  very limited resource nodes  such as energy, memory space| as well as communication and computation capabilities. the sensors are unattended Implemented  and battery recharge is almost impossible. So  many investigations have be done in redirecting energy efficient algorithms or protocols for WSNs. Our reasons behinds the study of number is based on the following three aspects. Initially of all First, we see That immediate transmittal is employed under small scale while multi-hop network transmittal network is employed under mass. All of us want to find the Which factors influence the transmittal manner. Second, it is Commonly That multi-hop agree transmitting more energy efficient than Usually transmitting When the average solitary source to destination distance is large. Yet ,}how to look for the optimal hop number in order That the overall energy consumption is  nominal is not well  tackled. Third, the hot location phenomenon the networking lifetime influences directly. After that all of us recommend to Optimization of energy aware routing path (OEAPR) algorithm, Which incorporate the overall routing mechanism With hop-based direction-finding nature During process in WSNs

Optimization of bioethanol production from saccharified sweet potato root flour by co-fermentation of Saccharomyces cerevisiae and Pichia sp. using OVAT and response surface methodologies

In recent years with the increase in price of fossil fuels, the demand of biofuel production from tuber crops such as sweet potato has become very important to meet the future energy crisis in developing countries. In the present study, fermentation of saccharified sweet potato root flour (SPRF) was carried out using co-culture of cells of Saccharomyces cerevisiae and Pichia sp. in immobilized condition for bioethanol production. Various growth parameters like incubation time, fermentation medium pH, incubation temperature and inoculum size were initially optimized using one variable at a time (OVAT) methodology. Then, temperature, pH and incubation time were found to be the most favorable variables for the maximum ethanol production with Box-Behnken design of response surface methodology (RSM). The maximum ethanol yield of 127.2 ± 2 g/kg of SPRF was obtained at pH 5 with an incubation period of 72 h at 30 °C by OVAT methodology. RSM further enhanced the bioethanol yield to 138.6 ± 3 g/kg of SPRF with an overall increase of 8.22% as compared to the OVAT method

Biochemical fingerprint of colorectal cancer cell lines using label-free live single-cell Raman spectroscopy

Label-free live single-cell Raman spectroscopy was used to obtain a chemical fingerprint of colorectal cancer cells including the classification of the SW480 and SW620 cell line model system, derived from primary and secondary tumour cells from the same patient. High-quality Raman spectra were acquired from hundreds of live cells, showing high reproducibility between experiments. Principal component analysis with linear discriminant analysis yielded the best cell classification, with an accuracy of 98.7±0.3% (standard error) when compared to discrimination trees or support vector machines. SW480 showed higher content of the disordered secondary protein structure amide III band, whereas SW620 showed larger α-helix and β-sheet band content. The SW620 cell line also displayed higher nucleic acid, phosphates, saccharide, and CH2 content. HL60, HT29, HCT116, SW620 and SW480 live single-cell spectra were classified using PCA/LDA with an accuracy of 92.4±0.4% (standard error), showing differences mainly in the β-sheet content, the cytochrome C bands, the CH-stretching regions, the lactate contributions and the DNA content. The lipids contributions above 2900 cm-1 and the lactate contributions at 1785 cm-1 appeared to be dependent on the colorectal adenocarcinoma stage, the advanced stage cell lines showing lower lipid and higher lactate content. The results demonstrate that these cell lines can be distinguished with high confidence, suggesting that Raman spectroscopy on live cells can distinguish between different disease stages, and could play an important role clinically as a diagnostic tool for cell phenotyping

Multifrequency Radiation of Extragalactic Large-Scale Jets

Large-scale extragalactic jets, observed to extend from a few to a few hundred kiloparsecs from active galactic nuclei, are now studied over many decades in frequency of electromagnetic spectrum, from radio until (possibly) TeV gamma rays. For hundreds of known radio jets, only about 25 are observed at optical frequencies. Most of them are relatively short and faint, with only a few exceptions, like 3C 273 or M 87, allowing for detailed spectroscopic and morphological studies. Somewhat surprisingly, the large-scale jets can be very prominent in X-rays. Up to now, about 25 jets were detected within the 1 - 10 keV energy range, although the nature of this emission is still under debate. In general, both optical and X-ray jet observations present serious problems for standard radiation models for the considered objects. Recent TeV observations of M 87 suggest the possibility of generating large photon fluxes at these high energies by its extended jet. In this paper we summarize information about multiwavelength emission of the large-scale jets, and we point out several modifications of the standard jet radiation models (connected with relativistic bulk velocities, jet radial stratification and particle energization all the way along the jet), which can possibly explain some of the mentioned puzzling observations. We also comment on gamma-ray emission of the discussed objects.Comment: 29 pages. Modified version, accepted for publication in Chinese Journal of Astronomy and Astrophysic

Homeostatic proliferation generates long-lived natural killer cells that respond against viral infection

Like memory T cells, natural killer cells that undergo homeostatic expansion in mice self-renew and retain the ability to respond to subsequent viral infection

Raman Spectroscopy and Regenerative Medicine: A Review

The field of regenerative medicine spans a wide area of the biomedical landscape—from single cell culture in laboratories to human whole-organ transplantation. To ensure that research is transferrable from bench to bedside, it is critical that we are able to assess regenerative processes in cells, tissues, organs and patients at a biochemical level. Regeneration relies on a large number of biological factors, which can be perturbed using conventional bioanalytical techniques. A versatile, non-invasive, non-destructive technique for biochemical analysis would be invaluable for the study of regeneration; and Raman spectroscopy is a potential solution. Raman spectroscopy is an analytical method by which chemical data are obtained through the inelastic scattering of light. Since its discovery in the 1920s, physicists and chemists have used Raman scattering to investigate the chemical composition of a vast range of both liquid and solid materials. However, only in the last two decades has this form of spectroscopy been employed in biomedical research. Particularly relevant to regenerative medicine are recent studies illustrating its ability to characterise and discriminate between healthy and disease states in cells, tissue biopsies and in patients. This review will briefly outline the principles behind Raman spectroscopy and its variants, describe key examples of its applications to biomedicine, and consider areas of regenerative medicine that would benefit from this non-invasive bioanalytical tool

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis