A Novel DUF569 Gene Is a Positive Regulator of the Drought Stress Response in Arabidopsis

In the last two decades, global environmental change has increased abiotic stress on plants and severely affected crops. For example, drought stress is a serious abiotic stress that rapidly and substantially alters the morphological, physiological, and molecular responses of plants. In Arabidopsis, several drought-responsive genes have been identified; however, the underlying molecular mechanism of drought tolerance in plants remains largely unclear. Here, we report that the “domain of unknown function” novel gene DUF569 (AT1G69890) positively regulates drought stress in Arabidopsis. The Arabidopsis loss-of-function mutant atduf569 showed significant sensitivity to drought stress, i.e., severe wilting at the rosette-leaf stage after water was withheld for 3 days. Importantly, the mutant plant did not recover after rewatering, unlike wild-type (WT) plants. In addition, atduf569 plants showed significantly lower abscisic acid accumulation under optimal and drought-stress conditions, as well as significantly higher electrolyte leakage when compared with WT Col-0 plants. Spectrophotometric analyses also indicated a significantly lower accumulation of polyphenols, flavonoids, carotenoids, and chlorophylls in atduf569 mutant plants. Overall, our results suggest that novel DUF569 is a positive regulator of the response to drought in Arabidopsis.     

Melt‐mixed polypropylene/acrylonitrile‐butadiene‐styrene blends with multiwall carbon nanotubes: Effect of compatibilizer and modifier on morphology and electrical conductivity

Cocontinuous blends of 45/55 polypropylene (PP)/acrylonitrile‐butadiene‐styrene (ABS) with multiwall carbon nanotubes (MWNT) were prepared by melt‐mixing in a conical twin‐screw microcompounder. PP‐grafted‐maleic anhydride (PP‐g‐MA) and styrene MA were used as compatibilizers for PP/ABS blends. Scanning electron microscopic observations showed phase segregation of PP‐g‐MA in the blends. State of dispersion of MWNT in the presence or absence of the compatibilizers was assessed through AC electrical conductivity measurements and crystallization studies of the blends. An improvement in AC electrical conductivity was observed in blends in presence of either styrene MA or dual compatibilizers. The lowest electrical percolation threshold was achieved at 0.1 wt % of MWNT using sodium salt of 6‐amino hexanoic acid‐modified MWNT. Significant increase in crystallization temperature of PP phase of blends with MWNT was observed in the presence of compatibilizers as compared to blends without compatibilizers. An attempt has been made to address the complex issues of phase segregation, compatibilization, and dispersion of MWNT in cocontinuous blends of PP/ABS. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011     

Photocatalytic degradation of dyes and organic contaminants in water using nanocrystalline anatase and rutile TiO2

Nanocrystalline TiO₂ was synthesized by controlled hydrolysis of titanium tetraisopropoxide. The anatase phase was converted to rutile phase by thermal treatment at 1023 K for 11 h. The catalysts were characterized by X-ray diffraction (XRD), diffuse reflectance spectroscopy (DRS), Fourier-transform infrared absorption spectrophotometry (FT-IR) and N₂ adsorption (BET) at 77 K. This study compare the photocatalytic activity of the anatase and rutile phases of nanocrystalline TiO₂ for the degradation of acetophenone, nitrobenzene, methylene blue and malachite green present in aqueous solutions. The initial rate of degradation was calculated to compare the photocatalytic activity of anatase and rutile nanocrystalline TiO₂ for the degradation of different substances under ultraviolet light irradiation. The higher photocatalytic activity was obtained in anatase phase TiO₂ for the degradation of all substances as compared with rutile phase. It is concluded that the higher photocatalytic activity in anatase TiO₂ is due to parameters like band-gap, number of hydroxyl groups, surface area and porosity of the catalyst.     

Hydrodynamic study on radially cross-flow fluidized bed multi-staged ion-exchange column

A hydrodynamic study was carried out on our patented radially cross-flow fluidized bed staged column, with the salt laden water and solid resins flowing counter-currently, to determine the loading/flooding criterion for a stable operation of the column, and also to ascertain the mal-distribution in flow. Residense time distribution measurements were taken to address the latter part of the study. The data collected from the hydrodynamic measurements show a wider range of liquid and solid flowrates that can be used for the stable operation of the column, in comparison to that obtained in the conventional multi-staged column. The extent of mal-distribution or channeling is also relatively smaller in the former. The observations are consistent with the mass-transfer results obtained in our recent study, where the separation of dissolved solids using the radially cross-flow ion exchange column was found to be 40% larger than that in the conventional column.     

Agro-Waste Generated Pd/CAP-Ash Catalyzed Ligand-Free Approach for Suzuki–Miyaura Coupling Reaction

Catalysis Letters - We converted agro-waste Custard Apple Peels (CAP) to ash via thermal treatment, on which Pd(OAc)2 was immobilized easily that produced a low-cost, highly efficient Pd/CAP-ash...     

An automatic channel selection method based on the standard deviation of wavelet coefficients for motor imagery based brain–computer interfacing

The redundant data in multichannel electroencephalogram (EEG) signals significantly reduces the performance of brain–computer interface (BCI) systems. By removing redundant channels, a channel selection strategy increases the classification accuracy of BCI systems. In this work, a novel channel selection method (stdWC) based on the standard deviation of wavelet coefficients across channels is proposed to identify Motor Imagery (MI) based EEG signals. The wavelet coefficients are calculated by employing a Continuous Wavelet Transform (CWT) filter bank to decompose each trial from the EEG channel. The wavelet coefficient's standard deviation values are obtained across the channels, and these values are then sorted to determine the EEG channels with the highest standard deviation values. The channels with the largest wavelet coefficient divergence are chosen. MI trials are then spatially filtered with the Common Spatial Pattern (CSP), and CWT filter bank-based 2D images are generated from the spatially filtered trials. These images are then classified using a unique nine-layered convolutional neural network (CNN) model that combines two feature maps acquired with differing filter sizes. The proposed framework (stdWC-CSP-CNN) is evaluated using kappa score and classification accuracy on two publically accessible datasets (BCI Competition III dataset IVa and BCI Competition IV dataset 2a). The suggested framework achieved a mean test classification accuracy of 88.8% for dataset IVa from BCI Competition III and 75.03% for dataset 2a from BCI Competition IV, according to the results. The proposed channel selection method outperforms the other channel selection methods examined, according to the results. By rejecting redundant channels, the whole framework can improve the performance of MI-based BCIs.     

Effect of swirl and number of swirler vanes on combustion characteristics of methane inverse diffusion flame

Journal of Mechanical Science and Technology - An experimental study is performed to explore the effect of swirl and number of swirler vanes on combustion characteristics of methane inverse...