Crop residue,manure and fertilizer in dryland maize under reduced tillage in northern China: I grain yields and nutrient use efficiencies

The rapidly increasing population and associated quest for food and feed in China has led to increased soil cultivation and nitrogen (N) fertilizer use, and as a consequence to increased wind erosion and unbalanced crop nutrition. In the study presented here, we explored the long-term effects of various combinations of maize stover, cattle manure and nitrogen (N) and phosphorus (P) fertilizer applications on maize (Zea mays L.) yield and nutrient and water use efficiencies under reduced tillage practices. In a companion paper, we present the effects on nutrient balances and soil fertility characteristics. The ongoing factorial field trial was conducted at Shouyang Dryland Farming Experimental Station in northern China from 1993 onwards. The incomplete, determinant-optimal design comprised 12 treatments, including a control treatment, in duplicate. Grain yields and N, P, and potassium (K) uptakes and N, P and K use efficiencies were greatly influenced by the amount of rain during the growing season (GSR), and by soil water at sowing (SWS). There were highly significant interactions between GSR and added stover and manure, expressed in complex annual variations in grain yield and N, P and K use efficiencies. Annual mean grain yields ranged from 3,000 kg ha⁻¹ to 10,000 kg ha⁻¹ and treatment mean yields from 4,500 kg ha⁻¹ to 7,000 kg ha⁻¹. Balanced combination of stover (3,000–6,000 kg), manure (1,500–6,000 kg) and N fertilizer (105 kg) gave the highest yield. Stover and manure were important for supplying K, but the effects differed greatly between years. Overall mean N recovery efficiency (NRE) ranged from 28% to 54%, depending on N source. NRE in wet years ranged from 50% to 90%. In conclusion, balanced combinations of stover, manure and NP fertilizer gave the highest yield and NRE. Reduced tillage with adding stover and manure in autumn prior to ploughing is effective in minimizing labor requirement and wind erosion. The potentials of split applications of N fertilizer, targeted to the need of the growing crop (response farming), should be explored to further increase the N use efficiency.     

Purification of 2-mercaptobenzothiazole by solvent extraction

−Purification of 2-mercaptobenzothiazole (91.9% purity) by solvent extraction was studied. The extraction of impurities present in crude 2-MBT (e.g. benzothiazole, sulfides and sulfur containing compounds) was carried out at temperatures between 70-180°C using various solvents and their mixtures of different polarity. The highest purity of 2-MBT, above 99% was obtained using nitrobenzene, toluene and ethanol, even at a concentration of 2-MBT above 50 wt%. Increasing temperature and decreasing concentration of the raw material have a positive influence on the purification process. A comparable efficiency of purification was observed also with mixed solvents, (toluene with ethanol, acetone and aniline) possessing the same polarities. A correlation between the polarity indexes (PI) of mixed solvents and experimentally obtained purity of 2-MBT was found. The highest purity of 2-MBT provides extraction of the raw material with mixed solvents having PI 3.8-4.4.     

Synthesis and properties of chitosan-modified poly(vinyl butyrate)

Modification of chitosan by grafting of vinyl butyrate was carried out in homogeneous phase using potassium persulfate as redox initator and 1.5% acetic acid as solvent. The percent grafting and grafting efficiency were analysed and the high grafting efficiency up to 94% was observed. The effects of reaction variables such as monomer concentration, initiator concentration, temperature and reaction time were investigated. It was observed that the solubility of chitosan was markedly reduced after grafting with vinyl butyrate. The grafted product is insoluble in common organic solvents as well in dilute organic and inorganic acids. Characterization of the graft copolymers were carried out by using Fourier Transform Infrared Spectroscopy (FTIR), Differential Scanning Calorimetry (DSC) and Scanning Electron Microscopy (SEM) technics. Characteristic signal of carbonyl group was observed at 1,731 cm⁻¹ which belongs to the poly vinyl butyrate segments in the graft copolymer. The melting transition of the chitosan main chain in the copolymer shifted to 124°C from its original value 101°C. In addition to these, we have also studied topology of the graft copolymer and the SEM micrograph showed continuous homogenous matrix which means there is no phase separation.     

Short beam three point bend tests in syntactic foams. Part I: Microscopic characterization of the failure zones

Scanning Electron Microscopic (SEM) studies were carried out on the failure surface of syntactic foam material tested in a short beam three point bend test (SBT) by employing 21 × 15 × 3 mm³ dimension bearing specimens. The syntactic foams were fabricated using glass microballoons in epoxy binder. The failure of the tensile, compression, and shear dominated regions were studied by SEM at different magnifications. The tensile region had characteristic features, such as partial debonding of the microballoons from the matrix and cracking of glass microballoons, apart from matrix cracking and some river pattern features. The compression side was characterized by crushing and collapsing of microballoons, resulting in accumulation of debris with no apparent river pattern for matrix‐rich regions. The midway positions of the SBT failed surface comprised of deformation bands in the matrix and occasional debonding of microballoons. The morphology recorded in the tensile and compression regions corroborated well with the results obtained on these foam samples in those specimens that were subjected to pure uniaxial tension and compression, respectively. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 98: 673–679, 2005     

IEVCA: An efficient image encryption technique for IoT applications using 2-D Von-Neumann cellular automata

Multimedia Tools and Applications - Present era is marked by exponential growth in transfer of multimedia data through internet. Most of the Internet-of-Things(IoT) applications send images to...     

Computer aided decision support system for mitral valve diagnosis and classification using depthwise separable convolution neural network

Multimedia Tools and Applications - The significance of mitral valve (MV) treatment is increasing recently because of an aging population. The computer vision-based acquisition and quantification...     

Video sequence feature extraction and segmentation using likelihood regression model

The development of digital technology is utilized by people to capture and share video frames. At present, rather than capturing images, people are interested in recording video footage for exploring information. Here, retrieval of video from large databases is challenging due to the continuous frame count. To overcome these challenges associated with the retrieval of video from available databases, this research proposed a likelihood-based regression approach for video processing. To improve the retrieval accuracy of video sequences, the proposed method utilizes a likelihood estimation technique integrated with a regression model. The likelihood estimate measures the pixel level roughly for estimating the pixel range, after which the regression approach measures the pixel level for transforming certainly blurred and unwanted pixels. In the proposed likelihood regression approach, the video is converted into a video frame and stored in a database. Query frames are taken into account by the generated database depending on the features which are used for a given video to be retrieved. The significant video retrieval performance obtained from the simulation results for the proposed likelihood-based regression model shows that the proposed model performs well over the other state-of-the-art techniques.

     

Development of new encryption system using Brownian motion based diffusion

Multimedia Tools and Applications - A new cryptographic model is proposed incorporating intertwining logistic map based confusion process and two dimensional Brownian Motion based diffusion...     

A Computationally Efficient and Scalable Key Management Scheme for Access Control of Media Delivery in Digital Pay-TV Systems

Multimedia Tools and Applications - In today’s Internet era, group communications in multimedia applications are becoming more and more popular. The issues of controlling illegal access to...     

Liver disorder detection using variable- neighbor weighted fuzzy K nearest neighbor approach

The human liver disorder is a genetic problem due to the habituality of alcohol or effect by the virus. It can lead to liver failure or liver cancer, if not been detected in initial stage. The aim of the proposed method is to detect the liver disorder in initial stage using liver function test dataset. The problem with many real-world datasets including liver disease diagnosis data is class imbalanced. The word imbalance refers to the conditions that the number of observations belongs to one class having more or less than the other class(es). Traditional K- Nearest Neighbor (KNN) or Fuzzy KNN classifier does not work well on the imbalanced dataset because they treat the neighbor equally. The weighted variant of Fuzzy KNN assign a large weight for the neighbor belongs to the minority class data and relatively small weight for the neighbor belongs to the majority class to resolve the issues with data imbalance. In this paper, Variable- Neighbor Weighted Fuzzy K Nearest Neighbor Approach (Variable-NWFKNN) is proposed, which is an improved variant of Fuzzy-NWKNN. The proposed Variable-NWFKNN method is implemented on three real-world imbalance liver function test datasets BUPA, ILPD from UCI and MPRLPD. The Variable-NWFKNN is compared with existing NWKNN and Fuzzy-NWKKNN methods and found accuracy 73.91% (BUPA Dataset), 77.59% (ILPD Dataset) and 87.01% (MPRLPD Dataset). Further, TL_RUS method is used for preprocessing and it improved the accuracy as 78.46% (BUPA Dataset), 78.46% (ILPD Dataset) and 95.79% (MPRLPD Dataset).