Smothering effect of different crops on weed Malva neglecta Wallr.

Field study was conducted at experimental farm of Punjab Agricultural University ,Ludhiana (India) during rabi seasons of 2004-05 and 2005-06. The experiment was laid out in randomized block design with fourteen treatments having combination of seven different crops viz. bread wheat, durum wheat, six - rowed barley, two-rowed barley, raya, gobhi sarson, linseed and two weed control treatments i.e. hand weeded and unweeded. The study was planned with an objective to find out the most suitable Rabi crop that can suppress the weeds to maximum extent with minimum reduction in yield as there was no herbicide available which can control the weeds in an effective manner. Minimum weed dry matter accumulation was observed in raya (0.97qha-1 in the weeded plot) whereas maximum dry matter accumulation was observed in bread wheat (8.3qha-1), followed by durum wheat (6.1qha-1), linseed(5.0qha-1), barley (6-row) (4.9qha-1), barley (2-row) (2.6qha-1) and gobhi sarson (2.4qha-1). Raya (Brassica juncea) showed maximum suppressing poten-tial as minimum per cent reduction in crop yield of unweeded over weeded (7.4%) and minimum per cent increase in weed dry matter of unweeded over weeded( 44%) was observed in this crop. Gobhi sarson (Brassica napus) was the next best smothering crop followed by barley (2-row), barley (6-row), linseed, durum wheat and bread wheat, respectively in suppressing the M. neglecta. Two hand weedings treatment proved better in controlling the weeds as compared to unweeded treatment

A review on Machine Learning Techniques

Machine learning is the essence of artificial intelligence. Machine Learning learns from past experiences to improve the performances of intelligent programs. Machine learning system builds the learning model that effectively “learns” how to estimate from training data of given example. IT refers to a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. In this new era, Machine learning is mostly in use to demonstrate the promise of producing consistently accurate estimates. The main goal and contribution of this review paper is to present the overview of machine learning and provides machine-learning techniques. Also paper reviews the merits and demerits of various machine learning algorithms in different approaches

Predicting The Intention To Accept Monthly Tax Deduction (MTD) As Final Tax Among Salaried Taxpayers

This study surveyed the level of awareness and determinants of intention to accept Monthly Tax Deduction (MTD) as final tax among salaried taxpayers in Kulim, Kedah using Theory Planned Behavior. The acceptance level of the implemented MTD as final tax system from the Year of Assessment 2014 was still unknown. The aim of this study is to investigate the relationship between attitudes, subjective norm, and perceived behavioral control as the independent variables and intention as dependent variable to accept Monthly Tax Deduction (MTD) as final tax among salaried taxpayers in the private and public sector in Kulim, Kedah. In order to collect data a total of 300 self administered questionnaires were distributed to the salaried taxpayers entitled to the monthly tax deduction and 109 usable responses were used to analyze the data collected. Using the Statistical Package for the Social Sciences (SPSS) version 20.0 analysis methods, the hypothesis results showed that there was a positive and significant relationship among the two variables attitude and perceived behavior control except subjective norm has a negative and insignificant relationship towards the intention to accept Monthly Tax Deduction (MTD) as final tax. The overall finding indicates that the attitude and perceived behavior control are the key factors that attract the salaried taxpayers to accept MTD as final tax

Genetic and molecular understanding for the development of methionine-rich maize: a holistic approach

Maize (Zea mays) is the most important coarse cereal utilized as a major energy source for animal feed and humans. However, maize grains are deficient in methionine, an essential amino acid required for proper growth and development. Synthetic methionine has been used in animal feed, which is costlier and leads to adverse health effects on end-users. Bio-fortification of maize for methionine is, therefore, the most sustainable and environmental friendly approach. The zein proteins are responsible for methionine deposition in the form of δ-zein, which are major seed storage proteins of maize kernel. The present review summarizes various aspects of methionine including its importance and requirement for different subjects, its role in animal growth and performance, regulation of methionine content in maize and its utilization in human food. This review gives insight into improvement strategies including the selection of natural high-methionine mutants, molecular modulation of maize seed storage proteins and target key enzymes for sulphur metabolism and its flux towards the methionine synthesis, expression of synthetic genes, modifying gene codon and promoters employing genetic engineering approaches to enhance its expression. The compiled information on methionine and essential amino acids linked Quantitative Trait Loci in maize and orthologs cereals will give insight into the hotspot-linked genomic regions across the diverse range of maize germplasm through meta-QTL studies. The detailed information about candidate genes will provide the opportunity to target specific regions for gene editing to enhance methionine content in maize. Overall, this review will be helpful for researchers to design appropriate strategies to develop high-methionine maize

Historical Vehicle Traffic Analysis and Commute Time Prediction Using Web Mining

Analyzing historical vehicle traffic data has many applications including urban planning and intelligent in-vehicle route prediction. A common practice to acquire this data is through roadside sensors. This approach is expensive because of infrastructure and planning costs and cannot be easily applied to new routes. A Web mining approach is proposed to address these limitations. The proposed system gathers information about vehicle commute times, accidents, and weather reports from heterogeneous Web sources. This information is combined to support vehicle traffic analytics. Clustering analysis is performed on historical data that investigates the traffic patterns of highways and arterial roads with factors having the most impact on commute time. A commute time prediction model is built on historical vehicle traffic data analytics. Commute time prediction model is trained with the traffic problems faced in the past and forecasts the commute time incorporating the impact of external factors such as weather and accidents

Potassium Management for Improving Mash Grain Yield in a Field Experiment at Regional Research Station, Gurdaspur

To improve production and quality of pulse crops, balanced use of production inputs is important to sustain soil fertility and to combat nutrient deficiency in particular. To understand the effect of potassium (K) fertilization on yield and yield attributes of mash bean/ black gram in a potassium deficient soil, a study was carried out for two consecutive years at the experimental farm of Punjab Agricultural University, Regional Research Station, Gurdaspur, India. Mash variety ‘Mash 114’ was tested in a randomized complete block design with three replications having different fertilizer treatments of potassium application rates Application of potassium fertilizer significantly increased the grain yield to 1963 kg ha-1 whereas plots without K fertilization maintained an average grain yield of 1204 kg ha-1. Maximum grain and straw yield in black gram was obtained with potassium application at the rate of 50 kg K2O ha-1 followed by 25 kg K2O ha-1. The two treatments were at par with each other however, treatment 50kg K2O ha-1 was significantly superior to treatment 12.5 kg K2O ha-1, NP and control. Inclusion of potassium in fertilization schedule alongwith N and P significantly influenced plant height, number of pods per plant, and 100 seed weight (g) in comparison to NP and control treatment. Quadratic regression equation also explained the progressive increase in seed yield of mash bean with increasing levels of potassium

Sequence analysis of six full?length bean yellow mosaic virusgenomes reveals phylogenetic diversity in India strains, suggestingsubdivision of phylogenetic group?IV

Abstract We report the complete genome sequence offive bean yellow mosaic virus (BYMV) isolates (CK-GL1,CK-GL3, CK-GL4, CK-GL5 and Vfaba2) that share 74.6-98.9% (nucleotide) and 81.5-99.1% (amino acid) identitywith globally available BYMV sequences. Phylogeneticanalysis clustered them specifically in BYMV phylogeneticgroup-IV within the existing nine groups. The CK-GL1,CK-GL2, CK-GL4 and CK-GL5 isolates formed a discretecluster within group-IV. The present study suggests subdivisionof group-IV into subgroup-IVa and IVb. Moreover,infectivity assays using in vitro RNA transcripts fromsubgroup-IVa (CK-GL3 isolate) and IVb (CK-GL1 isolate)showed distinct biological differences between the isolatessupporting subdivision

On the Equivalence of Acoustic Impedance and Squeeze Film Impedance in Micromechanical Resonators

In this work, we address the issue of modeling squeeze film damping in nontrivial geometries that are not amenable to analytical solutions. The design and analysis of microelectromechanical systems (MEMS) resonators, especially those that use platelike two-dimensional structures, require structural dynamic response over the entire range of frequencies of interest. This response calculation typically involves the analysis of squeeze film effects and acoustic radiation losses. The acoustic analysis of vibrating plates is a very well understood problem that is routinely carried out using the equivalent electrical circuits that employ lumped parameters (LP) for acoustic impedance. Here, we present a method to use the same circuit with the same elements to account for the squeeze film effects as well by establishing an equivalence between the parameters of the two domains through a rescaled equivalent relationship between the acoustic impedance and the squeeze film impedance. Our analysis is based on a simple observation that the squeeze film impedance rescaled by a factor of jx, where x is the frequency of oscillation, qualitatively mimics the acoustic impedance over a large frequency range. We present a method to curvefit the numerically simulated stiffness and damping coefficients which are obtained using finite element analysis (FEA) analysis. A significant advantage of the proposed method is that it is applicable to any trivial/nontrivial geometry. It requires very limited finite element method (FEM) runs within the frequency range of interest, hence reducing the computational cost, yet modeling the behavior in the entire range accurately. We demonstrate the method using one trivial and one nontrivial geometry

On the method of extraction of lumped parameters for the radiation impedance of complex radiator geometries

This work addresses the problem of finding expressions for the radiation impedance of a circular plate with cuts (holes + slits) and mounted in an infinite baffle. Due to the nontrivial nature of the structural geometry and the boundary conditions, analytical solution of the required Rayleigh integral is difficult for this case. The analysis in this case is carried out numerically using COMSOL Multiphysics. The air on top in contact with the vibrating plate, loads the plate with additional mass and also dissipates away energy depending on the frequency of vibration. The numerical solution obtained using FEA needs to be converted into suitable frequency based expressions. We use curve fitting to relate these radiation impedance values to an already reported equivalent circuit (for modeling the radiation impedance) in the literature. The detailed method of lumped parameter extraction, as well as the method of reduction of the circuit to its high and low frequency counterparts, is reported in this paper. The method described here is a generic one and can be used for any kind of geometry