Optimised Method of Resource Allocation for Hadoop on Cloud

— Many case studies have proved that the data generated at industries and academia are growing rapidly, which are difficult to store using existing database system. Due to the usage of internet many applications are created and has helped many industries such as finance, health care etc, which are also the source of producing massive data. The smart grid is a technology which delivers energy in an optimal manner, phasor measurement unit (PMU) installed in smart grid is used to check the critical power paths and also generate massive sample data. Using parallel detrending fluctuation analysis algorithm (PDFA) fast detection of events from PMU samples are made. Storing and analyzing the events are made easy using MapReduce model, hadoop is an open source implemented MapReduce framework. Many cloud service providers (CSP) are extending their service for Hadoop which makes easy for user’s to run their hadoop application on cloud. The major task is, it is users responsibility to estimate the time and resources required to complete the job within deadlines. In this paper, machine learning techniquies such as local weighted linear regression and the parallel glowworm swarm optimization (GSO) algorithm are used to estimate the resource and job completion time

Hybrid Cloud-Based Privacy Preserving Clustering as Service for Enterprise Big Data

Clustering as service is being offered by many cloud service providers. It helps enterprises to learn hidden patterns and learn knowledge from large, big data generated by enterprises. Though it brings lot of value to enterprises, it also exposes the data to various security and privacy threats. Privacy preserving clustering is being proposed a solution to address this problem. But the privacy preserving clustering as outsourced service model involves too much overhead on querying user, lacks adaptivity to incremental data and involves frequent interaction between service provider and the querying user. There is also a lack of personalization to clustering by the querying user. This work “Locality Sensitive Hashing for Transformed Dataset (LSHTD)” proposes a hybrid cloud-based clustering as service model for streaming data that address the problems in the existing model such as privacy preserving k-means clustering outsourcing under multiple keys (PPCOM) and secure nearest neighbor clustering (SNNC) models, The solution combines hybrid cloud, LSHTD clustering algorithm as outsourced service model. Through experiments, the proposed solution is able is found to reduce the computation cost by 23% and communication cost by 6% and able to provide better clustering accuracy with ARI greater than 4.59% compared to existing works

An analytical framework for smart manufacturing

Smart manufacturing is an emerging paradigm for the next generation of manufacturing systems. One key to the success of smart manufacturing is the ability to use the production data for defining predictive and descriptive models and their analyses. However, the development and refinement of such models is a labor- and knowledgeintensive activity that involves acquiring data, selecting and refining an analytical method and validating results. This paper presents an analytical framework that facilitates these activities by allowing ad-hoc analyses to be rapidly specified and performed. The proposed framework uses a domain-specific language to allow manufacturing experts to specify analysis models in familiar terms and includes code generators that automatically generate the lower-level artifacts needed for performing the analysis. We also describe the use of our framework with an example problem

Can Precision Electrophile Signaling Make a Meaningful and Lasting Impression in Drug Design?

For several years, drugs with reactive electrophilic appendages have been developed. These units typically confer prolonged residence time of the drugs on their protein targets, and may assist targeting shallow binding sites and/or improving the drug-protein target spectrum. Studies on natural electrophilic molecules have indicated that, in many instances, natural electrophiles use similar mechanisms to alter signaling pathways. However, natural reactive species are also endowed with other important mechanisms to hone signaling properties that are uncommon in drug design. These include ability to be active at low occupancy and elevated inhibitor kinetics. Herein, we discuss how we have begun to harness these properties in inhibitor design

Visible-Light Controlled Release of a Fluoroquinolone Antibiotic for Antimicrobial Photopharmacology

Owing to the dwindling arsenal of antibiotics, new methodologies for their effective and localized delivery are necessary. The use of optical control over delivery of drugs, also known as photopharmacology, has emerged as an important option for the spatiotemporally controlled generation of drugs and bioactive molecules. In the field of antimicrobial photopharmacology, most strategies utilize ultraviolet light for triggering release of the antibiotic. The use of such short wavelength light may have limitations such as phototoxicity. Here, a small molecule that is activated by visible light to release a fluoroquinolone, a broad-spectrum antibiotic, is reported. A boron-dipyrromethene, which is sensitive to cleavage at 470 nm, was used, and levofloxacin was used as a model fluoroquinolone. BDP-Levo was found to undergo cleavage in the presence of visible light to release the active antibiotic. Using growth inhibitory studies in Gram-positive as well as Gram-negative bacteria, the efficacy of BDP-Levo is demonstrated. Together, our study demonstrates that visible light can be used for optical control over antibiotic release and lays the foundation for visible-light-mediated antimicrobial photopharmacology

Facile Functionalization of Carbon Electrodes for Efficient Electroenzymatic Hydrogen Production.

Enzymatic electrocatalysis holds promise for new biotechnological approaches to produce chemical commodities such as molecular hydrogen (H2). However, typical inhibitory limitations include low stability and/or low electrocatalytic currents (low product yields). Here we report a facile single-step electrode preparation procedure using indium-tin oxide nanoparticles on carbon electrodes. The subsequent immobilization of a model [FeFe]-hydrogenase from Clostridium pasteurianum ("CpI") on the functionalized carbon electrode permits comparatively large quantities of H2 to be produced in a stable manner. Specifically, we observe current densities of >8 mA/cm2 at -0.8 V vs the standard hydrogen electrode (SHE) by direct electron transfer (DET) from cyclic voltammetry, with an onset potential for H2 production close to its standard potential at pH 7 (approximately -0.4 V vs. SHE). Importantly, hydrogenase-modified electrodes show high stability retaining ∼92% of their electrocatalytic current after 120 h of continuous potentiostatic H2 production at -0.6 V vs. SHE; gas chromatography confirmed ∼100% Faradaic efficiency. As the bioelectrode preparation method balances simplicity, performance, and stability, it paves the way for DET on other electroenzymatic reactions as well as semiartificial photosynthesis

Enzymatic and Microbial Electrochemistry: Approaches and Methods

[Image: see text] The coupling of enzymes and/or intact bacteria with electrodes has been vastly investigated due to the wide range of existing applications. These span from biomedical and biosensing to energy production purposes and bioelectrosynthesis, whether for theoretical research or pure applied industrial processes. Both enzymes and bacteria offer a potential biotechnological alternative to noble/rare metal-dependent catalytic processes. However, when developing these biohybrid electrochemical systems, it is of the utmost importance to investigate how the approaches utilized to couple biocatalysts and electrodes influence the resulting bioelectrocatalytic response. Accordingly, this tutorial review starts by recalling some basic principles and applications of bioelectrochemistry, presenting the electrode and/or biocatalyst modifications that facilitate the interaction between the biotic and abiotic components of bioelectrochemical systems. Focus is then directed toward the methods used to evaluate the effectiveness of enzyme/bacteria–electrode interaction and the insights that they provide. The basic concepts of electrochemical methods widely employed in enzymatic and microbial electrochemistry, such as amperometry and voltammetry, are initially presented to later focus on various complementary methods such as spectroelectrochemistry, fluorescence spectroscopy and microscopy, and surface analytical/characterization techniques such as quartz crystal microbalance and atomic force microscopy. The tutorial review is thus aimed at students and graduate students approaching the field of enzymatic and microbial electrochemistry, while also providing a critical and up-to-date reference for senior researchers working in the field

Chemoproteomics of an Indole-Based Quinone Epoxide Identifies Druggable Vulnerabilities in Vancomycin-Resistant Staphylococcus aureus

Publisher's version (útgefin grein)The alarming global rise in fatalities from multidrug-resistant Staphylococcus aureus (S. aureus) infections has underscored a need to develop new therapies to address this epidemic. Chemoproteomics is valuable in identifying targets for new drugs in different human diseases including bacterial infections. Targeting functional cysteines is particularly attractive, as they serve critical catalytic functions that enable bacterial survival. Here, we report an indole-based quinone epoxide scaffold with a unique boat-like conformation that allows steric control in modulating thiol reactivity. We extensively characterize a lead compound (4a), which potently inhibits clinically derived vancomycin-resistant S. aureus. Leveraging diverse chemoproteomic platforms, we identify and biochemically validate important transcriptional factors as potent targets of 4a. Interestingly, each identified transcriptional factor has a conserved catalytic cysteine residue that confers antibiotic tolerance to these bacteria. Thus, the chemical tools and biological targets that we describe here prospect new therapeutic paradigms in combatting S. aureus infections.The authors thank the Department of Biotechnology (DBT), Government of India (BT/PR15848/MED/29/1025/2016 to H.C. and S.C.), a Wellcome Trust DBT India Alliance Intermediate Fellowship (IA/I/15/2/502058 to S.S.K.) and a DST-FIST Infrastructure Development Grant (to IISER Pune Biology) for the financial support for our research. The Council for Scientific and Industrial Research (CSIR) and the Department of Science and Technology—Innovation in Science Pursuit for Inspired Research (DST-INSPIRE) for graduate student fellowships.Peer Reviewe