Optimisation of withered leaf moisture during the manufacture of black tea based upon theaflavins fractions

A study was conducted to see the effect of different moisture content of withered leaf on the activity of oxidative enzymes polyphenoloxidase (PPO) and peroxidase (PO) and on the formation of theaflavins (TFs) and thearubigins (TRs). Six commercially popular cultivars TV1, TV7, TV9, TV23, TV26 and T.3E/3 of Assam, India, were processed in four different moisture levels (72%, 70%, 68% and 65%). Significant reduction in PPO and PO enzymes, TFs, TRs and theaflavin digallate equivalent was observed with the decrease in moisture content of withered leaf. The TFs (0.83–5.4 mg g^?1) and TRs (23–107 mg g^?1) fractions were lowest at moisture level 65 ± 1%. Of the six cultivars studied, better quality of black tea was obtained for cultivar TV1, TV9 and TV23 at 70 ± 1% moisture content, while for TV7 and TV26, it was 68 ± 1%. Withered leaf moisture content should be carefully chosen to obtain the better quality tea from specific cultivar.     

Fast and exact out-of-core and distributed k-means clustering

Clustering has been one of the most widely studied topics in data mining and k-means clustering has been one of the popular clustering algorithms. K-means requires several passes on the entire dataset, which can make it very expensive for large disk-resident datasets. In view of this, a lot of work has been done on various approximate versions of k-means, which require only one or a small number of passes on the entire dataset.In this paper, we present a new algorithm, called fast and exact k-means clustering (FEKM), which typically requires only one or a small number of passes on the entire dataset and provably produces the same cluster centres as reported by the original k-means algorithm. The algorithm uses sampling to create initial cluster centres and then takes one or more passes over the entire dataset to adjust these cluster centres. We provide theoretical analysis to show that the cluster centres thus reported are the same as the ones computed by the original k-means algorithm. Experimental results from a number of real and synthetic datasets show speedup between a factor of 2 and 4.5, as compared with k-means.This paper also describes and evaluates a distributed version of FEKM, which we refer to as DFEKM. This algorithm is suitable for analysing data that is distributed across loosely coupled machines. Unlike the previous work in this area, DFEKM provably produces the same results as the original k-means algorithm. Our experimental results show that DFEKM is clearly better than two other possible options for exact clustering on distributed data, which are down loading all data and running sequential k-means or running parallel k-means on a loosely coupled configuration. Moreover, even in a tightly coupled environment, DFEKM can outperform parallel k-means if there is a significant load imbalance. Ruoming Jin is currently an assistant professor in the Computer Science Department at Kent State University. He received a BE and a ME degree in computer engineering from Beihang University (BUAA), China in 1996 and 1999, respectively. He earned his MS degree in computer science from University of Delaware in 2001, and his Ph.D. degree in computer science from the Ohio State University in 2005. His research interests include data mining, databases, processing of streaming data, bioinformatics, and high performance computing. He has published more than 30 papers in these areas. He is a member of ACM and SIGKDD. Anjan Goswami studied robotics at the Indian Institute of Technology at Kanpur. While working with IBM, he was interested in studying computer science. He then obtained a masters degree from the University of South Florida, where he worked on computer vision problems. He then transferred to the PhD program in computer science at OSU, where he did a Masters thesis on efficient clustering algorithms for massive, distributed and streaming data. On successful completion of this, he decided to join a web-service-provider company to do research in designing and developing high-performance search solutions for very large structured data. Anjan' favourite recreations are studying and predicting technology trends, nature photography, hiking, literature and soccer. Gagan Agrawal is an Associate Professor of Computer Science and Engineering at the Ohio State University. He received his B.Tech degree from Indian Institute of Technology, Kanpur, in 1991, and M.S. and Ph.D degrees from University of Maryland, College Park, in 1994 and 1996, respectively. His research interests include parallel and distributed computing, compilers, data mining, grid computing, and data integration. He has published more than 110 refereed papers in these areas. He is a member of ACM and IEEE Computer Society. He received a National Science Foundation CAREER award in 1998.     

Sustained transdermal release of diltiazem hydrochloride through electron beam irradiated different PVA hydrogel membranes

Extremely fast release of diltiazem hydrochloride (water soluble, anti anginal drug used to treat chest pain) together with its faster erosion has been the primary problem in conventional oral therapy. It has been addressed in this paper by encapsulating the drug in electron beam irradiated various poly (vinyl alcohol) hydrogel membranes and delivering it through transdermal route. Results show excellent control over the release of diltiazem hydrochloride through these membranes subject to their physico-mechanicals.     

A boundary element model for acoustic-elastic interaction with applications in ultrasonic NDE

The boundary integral equation method is applied to a class of time-harmonic acoustic scattering problems where the bounded elastic scatterer is submerged in a fluid. An exact mathematical model is presented for a finite scatterer with a closed surface, where the surface integral equations are exclusively used to represent the fluid-solid or acoustic-elastic interaction of the scattering process. The numerical procedure involves application of point collocation with quadratic isoparametric approximations that reduce the integral equations to a discrete set of complex linear algebraic equations. Examples emphasize the potential of the method to solve three-dimensional problems of practical interest. Limitations of the formulations and the extension to the case of a semi-infinite plane and curved fluid-solid interface are discussed in the latter part of the paper.     

Effect of silica-core gold-shell nanoparticles on the kinetics of biohydrogen production and pollutant hydrogenation via organic acid photofermentation over enhanced near-infrared illumination

A biological photoinduced fermentation process provides an alternative to traditional hydrogen productions. In this study, biohydrogen production was investigated at near IR region coupled to a near-field enhancement by silica-core gold-shell nanoparticles (NPs) over a range of acetate concentrations (5–40 mM) and light intensities (11–160 W/m²). The kinetic data were modeled using modified Monod equations containing light intensity effects. The yields of H₂ and CO₂ produced per acetate were determined as 2.31 mol-H₂/mol-Ac and 0.83 mol-CO₂/mol-Ac and increased to 4.38 mmol-H₂/mmol-Ma and 2.62 mmol-CO₂/mmol-Ma when malate was used. Maximum increases in H₂ and CO₂ productions by 115% and 113% were observed by adding NPs without affecting the bacterial growth rates (6.1–8.2 mg-DCM/L/hour) while the highest hydrogen production rate was determined as 0.81 mmol/L/hour. Model simulations showed that the energy conversion efficiency increased with NPs concentration but decreased with the intensity. Complete hydrogenation application was demonstrated with toxic 2-chlorobiphenyl using Pd catalysts.     

One-pot facile synthesis and electrochemical evaluation of selenium enriched cobalt selenide nanotube for supercapacitor application

The present study emulates a one-pot facile synthesis of selenium-enriched CoSe nanotube using a chemical bath deposition (CBD) procedure. Schematic incorporation of 3D Ni foam current collectors as substrates for the growth of CoSe–Se nanotubes helped us achieve a binder-less thin film coating. The controlled synthesis of CoSe–Se nanotube was carried out by optimizing the temperature and time of the deposition. CoSe–Se nanotubes were grown on a porous Ni foam substrate using lithium chloride as a shape directing agent. The study found that the one dimensional structure of the nanotubes with porous nature results in an uninterrupted network of electroactive sites. Due to the superior conductivity, the as-fabricated material exhibited excellent rate capability and a higher degree of electrolyte ion diffusion across the CoSe–Se crystal structure. The CoSe–Se@Ni foam electrodes exhibited a specific capacitance of 1750.81 F g^?1 at 1 A g^?1. The electrode exhibited excellent cycling stability and showed a capacitance retention of 95% after 4000 charge-discharge cycles. Finally, an asymmetric supercapacitor (ASC) device was fabricated with the as-synthesized CoSe–Se@Ni foam electrode as the cathode, activated carbon@Ni foam electrode as the anode, and a thin filter paper separator soaked in 1 M aqueous KOH electrolyte solution. The ASC device showed a specific capacitance value of 106.73 F g^?1 at 0.5 A g^?1, and achieved an energy density of 37.94 Wh kg^?1 at a power density of 475.30 W kg^?1. The ASC device was utilized in an extended potential window of 1.6 V. The fabricated device displayed exceptional cycling stability with a capacitance retention of 93% after 5000 charge-discharge cycles.     

Mining user–user communities for a weighted bipartite network using spark GraphFrames and Flink Gelly

The Journal of Supercomputing - Large-scale graph processing is one of the recently developed significant research areas relevant to big data analytics. Distributed graph analytics is useful to see...     

Little amounts of carbon nanotubes as anti-wear reinforcement for alumina in dry sliding

Carbon nanotubes (CNTs) are a leading choice for reinforcing oxide and nitride ceramics, but investigations into the tribological performance of CNT–ceramic composites remain inconclusive. Here, we show that reinforcement with only .1 wt% multi-walled CNTs improves the antifriction and anti-wear performance of zirconia-toughened alumina by up to 23% and 51%, respectively. Dry sliding tests under normal loads of 40–60 N for a sliding distance of 1000 m reveal a load-dependent transition in the lubrication mechanism—CNTs retain their tubular morphology at low loads and reduce friction via a sliding–rolling response, whereas high sliding loads trigger the formation of a uniform, thin lubricating film by the repeated crushing and smearing of exfoliated nanotubes. Raman spectra analyses confirmed that the carbon-rich tribo-film possesses a graphitic structure. Well-dispersed CNTs prevent wear loss by mechanisms, such as crack bridging and grain anchoring. The present work opens up new frontiers for the application of CNT–alumina tribo-ceramics in anti-wear, unlubricated, and high contact stress applications, such as in the manufacturing and mining industries.