Acclimation of morphology and physiology in turf grass to low light environment: A review

This short review elucidated the significance of the research on acclimation of the morphology and physiology in turf grass to low light environment, the mechanism of physiological response and the photosynthetic regulation and control of turf grass to suit low light environment. We also discussed current research problems and provided insight into future relevant research.Key words: Low light, morphological change, physiological acclimation, regulation mechanism, turf grass

Gate controlled electronic transport in monolayer MoS2 field effect transistor

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Cp∗Rh(III)-catalyzed electrophilic amination of arylboronic acids with azo compounds for synthesis of arylhydrazides

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Pentapotassium dicitrato(4-)manganate(III) pentahydrate

The centrosymmetric crystal structure pentapotassium dicitrato(4-) manganate(III) pentahydrate, K-5[Mn(C6H4O7) (2)].5H(2)O, has two independent anions, both of which lie at inversion centers in the triclinic unit cell. The Mn atoms are O, O', O"-chelated by the citrate entity and the six O atoms surrounding each Mn atom constitute an octahedron. The K atoms interact with the anions and the water molecules, leading to the formation of a network structure that also features extensive hydrogen bonding

Filtering electrocardiographic signals using an unbiased and normalized adaptive noise reduction system

We present a novel unbiased and normalized adaptive noise reduction (UNANR) system to suppress random noise in electrocardiographic (ECG) signals. The system contains procedures for the removal of baseline wander with a two-stage moving-average filter, comb filtering of power-line interference with an infinite impulse response (IIR) comb filter, an additive white noise generator to test the system's performance in terms of signal-to-noise ratio (SNR), and the UNANR model that is used to estimate the noise which is subtracted from the contaminated ECG signals. The UNANR model does not contain a bias unit, and the coefficients are adaptively updated by using the steepest-descent algorithm. The corresponding adaptation process is designed to minimize the instantaneous error between the estimated signal power and the desired noise-free signal power. The benchmark MIT-BIH arrhythmia database was used to evaluate the performance of the UNANR system with different levels of input noise. The results of adaptive filtering and a study on convergence of the UNANR learning rate demonstrate that the adaptive noise-reduction system that includes the UNANR model can effectively eliminate random noise in ambulatory ECG recordings., leading to a higher SNR improvement than that with the same system using the popular least-mean-square (LMS) filter. The SNR improvement provided by the proposed UNANR system was higher than that provided by the system with the LMS filter, with the input SNR in the range of 5-20 dB over the 48 ambulatory ECG recordings tested. Crown Copyright (C) 2008 Published by Elsevier Ltd on behalf of IPEM. All rights reserved

Microbial fuel cells: a green and alternative source for bioenergy production

Microbial fuel cell (MFC) represents one of the green technologies for the production of bioenergy. MFCs using microalgae produce bioenergy by converting solar energy into electrical energy as a function of metabolic and anabolic pathways of the cells. In the MFCs with bacteria, bioenergy is generated as a result of the organic substrate oxidation. MFCs have received high attention from researchers in the last years due to the simplicity of the process, the absence in toxic by-products, and low requirements for the algae growth. Many studies have been conducted on MFC and investigated the factors affecting the MFC performance. In the current chapter, the performance of MFC in producing bioenergy as well as the factors which influence the efficacy of MFCs is discussed. It appears that the main factors affecting MFC’s performance include bacterial and algae species, pH, temperature, salinity, substrate, mechanism of electron transfer in an anodic chamber, electrodes materials, surface area, and electron acceptor in a cathodic chamber. These factors are becoming more influential and might lead to overproduction of bioenergy when they are optimized using response surface methodology (RSM)

Hexaaquamagnesium bis{trans-[nitrilotriacetato(2-)-κ(3)O(1),N,O(2)]-μ-oxo-cis-dioxomolybdate(VI)} hexahydrate

Both the cation and anion in the title compound, [Mg(H2O)(6)][Mo2O5(C6H7NO6)(2)]. 6H(2)O, lie on centers of symmetry, and their metals are both six-coordinate in octahedral environments