Showing papers by "Government College published in 2017"

Bacterial laccase: recent update on production, properties and industrial applications.

Abstract: Laccases (benzenediol: oxygen oxidoreductase, EC 1.10.3.2) are multi-copper enzymes which catalyze the oxidation of a wide range of phenolic and non-phenolic aromatic compounds in the presence or absence of a mediator. Till date, laccases have mostly been isolated from fungi and plants, whereas laccase from bacteria has not been well studied. Bacterial laccases have several unique properties that are not characteristics of fungal laccases such as stability at high temperature and high pH. Bacteria produce these enzymes either extracellularly or intracellularly and their activity is in a wide range of temperature and pH. It has application in pulp biobleaching, bioremediation, textile dye decolorization, pollutant degradation, biosensors, etc. Hence, comprehensive information including sources, production conditions, characterization, cloning and biotechnological applications is needed for the effective understanding and application of these enzymes at the industrial level. The present review provides exhaustive information of bacterial laccases reported till date.

Contribution of Zinc Solubilizing Bacteria in Growth Promotion and Zinc Content of Wheat.

Abstract: Zinc is an imperative micronutrient required for optimum plant growth. Zinc solubilizing bacteria are potential alternatives for zinc supplementation and convert applied inorganic zinc to available forms. This study was conducted to screen zinc solubilizing rhizobacteria isolated from wheat and sugarcane, and to analyze their effect on wheat growth and development. Fourteen exo-polysaccharides producing bacterial isolates of wheat were identified and characterized biochemically as well as on the basis of 16S rRNA gene sequences. Along these, 10 identified sugarcane isolates were also screened for zinc solubilizing ability on five different insoluble zinc sources. Out of 24, five strains, i.e., EPS 1 (Pseudomonas fragi), EPS 6 (Pantoea dispersa), EPS 13 (Pantoea agglomerans), PBS 2 (E. cloacae) and LHRW1 (Rhizobium sp.) were selected (based on their zinc solubilizing and PGP activities) for pot scale plant experiments. ZnCO3 was used as zinc source and wheat seedlings were inoculated with these five strains, individually, to assess their effect on plant growth and development. The effect on plants was analyzed based on growth parameters and quantifying zinc content of shoot, root and grains using atomic absorption spectroscopy. Plant experiment was performed in two sets. For first set of plant experiments (harvested after 1 month), maximum shoot and root dry weights and shoot lengths were noted for the plants inoculated with Rhizobium sp. (LHRW1) while E. cloacae (PBS 2) increased both shoot and root lengths. Highest zinc content was found in shoots of E. cloacae (PBS 2) and in roots of P. agglomerans (EPS 13) followed by zinc supplemented control. For second set of plant experiment, when plants were harvested after three months, Pantoea dispersa (EPS 6), P. agglomerans (EPS 13) and E. cloacae (PBS 2) significantly increased shoot dry weights. However, significant increase in root dry weights and maximum zinc content was recorded for Pseudomonas fragi (EPS 1) inoculated plants, isolated from wheat rhizosphere. While maximum zinc content for roots was quantified in the control plants indicating the plant's inability to transport zinc to grains, supporting accelerated bioavailability of zinc to plant grains with zinc solubilizing rhizobacteria.

A systematic review on ethnomedicines of anti-cancer plants.

Abstract: Cancer is a serious health problem and the second leading cause of death around the globe. Present review is an attempt to provide utmost information based on ethno-pharmacological and toxicological aspects of anti-cancer plants of the world. A total of 276 articles published in English journals and containing maximum ethnomedicinal information were reviewed using several data sources such as; Google scholar, Web of Science, Scopus, PubMed and floras of different countries. A total of 199 anti-cancer plants were recorded in present review and results indicated that traditional medicines are mostly being use in developing countries for cancer treatment. Traditionally and scientifically skin and breast cancer types gained more focus. Seventy plants were reportedly analyzed for in-vitro activities while 32 plants were having in-vivo reports. Twenty nine pure compounds (mostly phenolic) were reportedly isolated from anti-cancer plants and tested against different cancer cell lines. Inspite having better efficiency of ethnomedicines as compared to synthetic drugs, several plants have also shown toxic effects on living system. Therefore, we invite researchers attention to carry out detailed ethno-pharmacological and toxicological studies on un-explored anti-cancer plants in order to provide reliable knowledge to the patients and develop novel anti-cancer drugs. Copyright © 2017 John Wiley & Sons, Ltd.

Analysis on credit card fraud identification techniques based on KNN and outlier detection

Abstract: Popular payment mode accepted both offline and online is credit card that provides cashless transaction. It is easy, convenient and trendy to make payments and other transactions. Credit card fraud is also growing along with the development in technology. It can also be said that economic fraud is drastically increasing in the global communication improvement. It is being recorded every year that the loss due to these fraudulent acts is billions of dollars. These activities are carried out so elegantly so it is similar to genuine transactions. Hence simple pattern related techniques and other less complex methods are really not going to work. Having an efficient method of fraud detection has become a need for all banks in order to minimize chaos and bring order in place. There are several techniques like Machine learning, Genetic Programming, fuzzy logic, sequence alignment, etc are used for detecting credit card fraudulent transactions. Along with these techniques, KNN algorithm and outlier detection methods are implemented to optimize the best solution for the fraud detection problem. These approaches are proved to minimize the false alarm rates and increase the fraud detection rate. Any of these methods can be implemented on bank credit card fraud detection system, to detect and prevent the fraudulent transaction.

Maximizing the wireless sensor networks lifetime through energy efficient connected coverage

Abstract: Wireless Sensor Network (WSN) is an emerging technology that is gaining much importance owing to its immense contribution in various day-to-day applications. A sensor is battery-operated, unattended low-cost device with limited computing, communication and storage capabilities. Thus the network lifetime has become the key characteristic for evaluating sensor networks in an application-specific way. There are certain approaches in literature which consider the lifetime maximization problem. However, they suffer from impulsive energy hole, coverage hole and communication hole. In this paper we propose a novel Energy Efficient Connected Coverage (EECC) scheduling to maximize the lifetime of the WSN. The EECC adheres to Quality of Service (QoS) metrics such as remaining energy, coverage and connectivity. In EECC the sensor which doesn't contribute to coverage will act as a relay node to reduce the burden of the sensing node. The sensing node senses the target whereas the relaying node communicates the sensory information to the sink. The EECC forms non-disjoint cover sets using remaining energy, coverage and connectivity of every sensor. The proposed EECC outperforms similar scheduling algorithms found in the literature in an energy efficient way with the short execution time. Through simulations the constancy of EECC in extending the lifetime of WSN is confirmed.

Investigation on performance, emission and combustion characteristics of variable compression engine fuelled with diesel, waste plastics oil blends

Abstract: Presently plastics are major contributors in solid waste which has higher thermal energy. Waste plastics can be converted into alternate fuel by pyrolysis which can replace diesel in compression ignition engines. The present study deals with the performance, combustion and emission characteristics of variable compression ratio engine fuelled with plastic oil, diesel and its blends with diethyl ether as an additive. Three blends 2.5, 7.5 and 12.5 % were tested in variable compression ratio engine. Waste plastic oil blend, pure plastic oil and diesel were considered for comparison. This study reveals that brake thermal efficiency increases for all the blends when compression ratio increases from 12 to 20. The specific fuel consumption of the blends and plastic oil were higher than the diesel. But the brake thermal efficiency for all the blends, plastic oil was comparatively lower than that of diesel. The regulated emissions of the variable compression ratio engine under varying loads and compression ratio for different blends were discussed.

Fabrication of ZnO/g-C3N4 nanocomposites for enhanced visible light driven photocatalytic activity

Abstract: ZnO/g-C3N4 nanocomposite photocatalysts were prepared using a simple and cost-effective pyrolysis method. The structural, optical, surface morphological and photocatalytic properties of the nanocomposites were analyzed and compared with those of g-C3N4. X-ray diffraction results revealed that all the ZnO/g-C3N4 samples have a hexagonal wurtzite phase of ZnO. Spectroscopic results obtained via FT-IR technique were consistent with the layered structure of sp2 hybridized bonding features of C and N in g-C3N4, besides Zn–O stretching vibrations. Photoluminescence results revealed that ZnO hybridization with g-C3N4 showed efficient separation and delayed recombination of photoinduced electron–hole pairs. TEM analysis clearly displayed that ZnO nanoparticles are anchored on g-C3N4 and showed the interface between the ZnO and g-C3N4. The ZnO/g-C3N4 nanocomposites exhibited enhanced visible light photocatalytic degradation against methylene blue dye when compared to g-C3N4. A plausible mechanism has been proposed for the observed enhanced photocatalytic activity.

Surface Plasmon Assisted Enhancement in the Nonlinear Optical Properties of Phenothiazine by Gold Nanoparticle

Abstract: We report the photophysical method for the synthesis of phenothiazine (PTZ)–gold (Au) nanocomposite (NC), by ablating a Au target in PTZ–dimethylformamide (DMF) solution using a Q-switched Nd:YAG laser delivering 7 ns pulses at 532 nm. The ablation of the Au target as well as the photoionization of PTZ was carried out simultaneously in the same medium with the same laser system. PTZ itself acts as a reducing and stabilizing agent during the formation of Au nanoparticles (NPs). The composite formation was confirmed from the Fourier transform infrared spectroscopy (FTIR) analysis and UV–visible absorption spectrum. The presence of NPs in the composite was evident from the absorption studies and transmission electron microscopy (TEM) analysis. A noticeable reduction in photoluminescence intensity was observed in the composite material, indicating the electron/energy transfer between the constituents. Nonlinear optical (NLO) studies have been done by employing the single beam Z-scan technique that uses 532 nm...

Anti-cancer potential of a mix of natural extracts of turmeric, ginger and garlic: A cell-based study

Abstract: Cancer related morbidity and mortality is a major health care concern. Developing potent anti-cancer therapies which are non-toxic, sustainable and affordable is of alternative medicine. This study was designed to investigate the aqueous natural extracts mixture (NE mix) prepared from common spices turmeric, ginger and garlic for its free radical scavenging potential and anti-cancer property against human breast cancer cell lines (MCF-7, ZR-75 and MDA-MB 231). Qualitative analysis of their bioactive constituents from turmeric, ginger and garlic were done using liquid chromatography-ESI- mass spectrometry (LC-ESI-MS/MS). To the best of our knowledge, NE mix with and without Tamoxifen has not been tested for its anti-cancer potential. We observed that the NE mix induced apoptosis in all the breast cancer cell lines, but it was more prominent in MCF-7 and ZR-75 cell lines in comparison to MDA-MB 231 cell line. The extent of apoptosis due to combined treatment with NE mix-Tamoxifen was higher than Tamoxifen alone, indicating a potential role of the NE mix in sensitizing the ER-positive breast cancer cells towards Tamoxifen. In support to MTT assay, cell cycle analysis, our RT-PCR results also prove that the NE mix 10 μg, Tam 20 μg and combination of NE mix 10 μg-Tam 20 μg altered the expression of apoptotic markers (p53 and Caspase 9) leading to apoptosis in all three cell lines. Our data strongly indicate that our NE mixture is a potential alternative therapeutic approach in certain types of cancer.

Short and long term stock trend prediction using decision tree

Abstract: This paper presents the results of method designed to predict price trends in the stock market. First objective of this research is to optimize the stock price trend prediction for short term using some oscillators and indicators: Moving Average Convergence Divergence (MACD), the Relative Strength Index (RSI), the Stochastic Oscillator (KDJ) and Bollinger Band (BB). It is observed that using appropriate pre-processing technique and Machine learning model, it is possible to improve accuracy rate of short-term trend prediction. Applying Preprocessing and then using combination of data can yield a better Accuracy rate in Short term Trades, while predicting for Long-term Trend of Stock this Technical indicators are not sufficient. Along with some of this Technical data and Fundamental Data of the company, it is possible to predict Long term stock movement. For Long term Prediction its Debt to Equity, Net profit of pervious 3 year, Promoters holding, Dividend yield and PE ratio is used along with Technical Factors. It is observed that using Fundamental and Technical Data, Long term Stock Prediction is Possible.

A Unified Shear Deformation Theory for the Bending of Isotropic, Functionally Graded, Laminated and Sandwich Beams and Plates

Abstract: In this paper, a displacement-based unified shear deformation theory is developed for the analysis of shear deformable advanced composite beams and plates. The theory is developed with the inclusio...

Punica granatum peel extracts: HPLC fractionation and LC MS analysis to quest compounds having activity against multidrug resistant bacteria

Abstract: Medicinal plants are rich source of traditional herbal medicine around the globe. Most of the plant’s therapeutic properties are due to the presence of secondary bioactive compounds. The present study analyzed the High Pressure Liquid Chromatography (HPLC) fractions of Puncia granatum (peel) extracts (aqueous, chloroform, ethanol and hexane) against multidrug resistant bacterial pathogens (Acinetobacter baumannii, Escherichia coli, Pseudomonas aeruginosa and Staphylococcus aureus). All the fractions having antibacterial activity was processed for bioactive compounds identification using LC MS/MS analysis. Among total HPLC fractions (n = 30), 4 HPLC fractions of P. granatum (peel) showed potential activity against MDR pathogens. Fraction 1 (F1) and fraction 4 (F4) collected from aqueous extract showed maximum activity against P. aeruginosa. Fraction 2 (F2) of hexane showed antibacterial activity against three pathogens, while ethanol F4 exhibited antibacterial activity against A. baumannii. The active fractions were processed for LC MS/MS analysis to identify bioactive compounds. Valoneic acid dilactone (aqueous F1 and F4), Hexoside (ethanol F4) and Coumaric acid (hexane F2) were identified as bioactive compounds in HPLC fractions. Puncia granatum peel extracts HPLC fractions exhibited potential inhibitory activity against MDR bacterial human pathogens. Several bioactive compounds were identified from the HPLC fractions. Further characterization of these compounds may be helpful to conclude it as therapeutic lead molecules against MDR pathogens.

Sustainable chemical technologies for textile production

Abstract: Conventional textile production is one of the most polluting industries on earth. The textile industries are responsible for as much as 20% of pollution of our rivers and lands. The use of toxic chemicals in production and packaging, the generation of a considerable amount of waste, the use and pollution of a huge quantity of water, the high consumption of energy in production and transport with the consequent release of greenhouse gases are responsible for the nonsustainability of the textile industry. Improvement in the sustainability of textile production is important for all of us. The chapter discusses greener textile materials including organic fibres, the use of eco-friendly dyes and chemicals, and enzymatic and other eco-friendly processing. Adaptation of improved processes with strict process controls and waterless dyeing are some ways in which sustainability can be improved.

Reformulated query-based document retrieval using optimised kernel fuzzy clustering algorithm

Abstract: Clustering-based document retrieval system offers to find similar documents for a given user's query. This study explores the scope of kernel fuzzy c-means (KFCM) with the genetic algorithm on document retrieval issue. Initially, genetic algorithm-based kernel fuzzy c-means algorithm (GKFCM) is proposed to make the clustering of documents in the library. For each cluster, an index is created, which contains a common significant keywords of the documents for that cluster. Once the user enters the keyword as the input to the system, it will process the keywords with the WORDNET ontology to achieve the neighbourhood keywords and related synset keywords. Lastly, the documents inside the cluster are released at first as the resultant-related documents for the query keyword, which clusters have the maximum matching score values. Experiments results prove that GKFCM-based proposed system outperforms better performance than existing methods.

Quality characterization and pollution source identification of surface water using multivariate statistical techniques, Nalagarh Valley, Himachal Pradesh, India

Abstract: Sirsa River flows through the central part of the Nalagarh valley, belongs to the rapid industrial belt of Baddi, Barotiwala and Nalagarh (BBN). The appraisal of surface water quality to ascertain its utility in such ecologically sensitive areas is need of the hour. The present study envisages the application of multivariate analysis, water utility class and conventional graphical representation to reveal the hidden factor responsible for deterioration of water quality and determine the hydrochemical facies and its evolution processes of water types in Nalagarh valley, India. The quality assessment is made by estimating pH, electrical conductivity (EC), total dissolved solids (TDS), total hardness, major ions (Na+, K+, Ca2+, Mg2+, HCO3 −, Cl−, SO4 2−, NO3 − and PO4 3−), dissolved oxygen (DO), biological oxygen demand (BOD) and total coliform (TC) to determine its suitability for drinking and domestic purposes. The parameters like pH, TDS, TH, Ca2+, HCO3 −, Cl−, SO4 2−, NO3 − are within the desirable limit as per Bureau of Indian Standards (Indian Standard Drinking Water Specification (Second Edition) IS:10500. Indian Standard Institute, New Delhi, pp 1–18, 2012). Mg2+, Na+ and K+ ions for pre monsoon and EC during pre and post monsoon at few sites and approx 40% samples of BOD and TC for both seasons exceeds the permissible limits indicate organic contamination from human activities. Water quality classification for designated use indicates that maximum surface water samples are not suitable for drinking water source without conventional treatment. The result of piper trillinear and Chadha’s diagram classified majority of surface water samples for both seasons fall in the fields of Ca2+–Mg2+–HCO3 − water type indicating temporary hardness. PCA and CA reveal that the surface water chemistry is influenced by natural factors such as weathering of minerals, ion exchange processes and anthropogenic factors. Thus, the present paper illustrates the importance of multivariate techniques for reliable quality characterization of surface water quality to develop effective pollution reduction strategies and maintain a fine balance between the industrialization and ecological integrity.

A study of probable alpha-ternary fission fragments of 257Fm

Abstract: The probable α-accompanied cold ternary fission fragments of 257Fm are studied using six types of nuclear proximity potentials. We have studied the driving potential, probability, relative yield and half-lives of possible alpha ternary fission fragments. It is clear from present study that the alpha accompanied cold ternary fission reactions of 257Fm having minimum driving potential, maximum fission yield and small fission half lives for 48Ca + 205Pt + 4He. Hence this combination is recognized as most probable alpha ternary fission fragments of 257Fm due to the presence of doubly magic nucleus 48Ca. This study finds important in the experiments on alpha ternary fission of 257Fm.

A review of topologies of inverter for grid connected PV systems

Abstract: The demand of renewable resources has been increasing rapidly due to the environmental concerns and need of energy. Solar photovoltaic energy is currently one of the most popular and renewable energy resource on the earth. Inverter is essential component in grid connected PV systems. This review focus on the standards of inverter for grid connected PV system, several inverter topologies for connecting PV panels to the three phase or single phase grid with their advantages and limitations. In this paper different converter topologies used for inverter are carried out and comparison of various inverter topologies has discussed according to their efficiency, energy harvesting, cost, shading effect and reliability.