A REALISTIC AND VALUABLE VARIETY SELECTION POLICY FOR HUGE RANGE DE-DUPLICATION

The data provided using the customer to tune the deduplication process is generally symbolized having a couple of by hands labeled pairs. In large datasets, producing this type of labeled set may well be a daunting task because it requires a specialist to choose and label plenty of informative pairs. Within the first stage, we advise a procedure for produce balanced subsets of candidate pairs for labeling. Within the second stage, an active selection is incrementally invoked to get rid of the redundant pairs within the subsets produced within the first stage to be able to provide an even smaller sized plus much more informative training set. This training set is effectively used both to understand in which the most ambiguous pairs lie also to configure the classification approaches. Our evaluation makes sure that TSSS cuts lower around the labeling effort substantially while achieving a hostile or superior matching quality in comparison with condition-of-the-art deduplication methods in large datasets. The information deduplication task has attracted lots of attention inside the research community to be able to provide efficient and effective solutions

Identification of Novel QTLs for BPH Tolerance in Rice Using Resistant Donor BM 71

Rice is the most widely grown crop in the world, feeding half of the world’s population. Brown plant hopper (BPH) is a considerable risk to rice fields carrying 20-90% yield losses. Hopper burn can be effectively managed by the recognition and use of BPH genes. Marker based genetic analysis of 136 RILcollected from a high yielding susceptible variety, MTU 3626 and BM 71, a BPH donor developed at RARS, identified 3 minor novel QTLs viz; qmbph2.1,qmbph4.1 and qmbph12.1 on chromosomes 2, 4 and 12 and two other QTLson chromosome 5 and 7, namelyqmbph5.1 and qmbph7.1. The phenotyping of RIL’s revealed that ten RIL’s (2711 – 31, 2711 – 37, 2711 – 50, 2711 – 69, 2711 – 84, 2711 – 88, 2711 – 94, 2711 – 100, 2711 – 168 and 2711 – 191) recorded yields comparable to checks, Swarna and Pushyami along with BPH score similar to donor. The BPH resistance lines recognised will be further evaluated, and the confirmed lines can be employed in rice breeding programs

Meeting Future Energy Needs in the Hindu Kush Himalaya

As mentioned in earlier chapters, the HKH regions form the entirety of some countries, a major part of other countries, and a small percentage of yet others. Because of this, when we speak about meeting the energy needs of the HKH region we need to be clear that we are not necessarily talking about the countries that host the HKH, but the clearly delineated mountainous regions that form the HKH within these countries. It then immediately becomes clear that energy provisioning has to be done in a mountain context characterized by low densities of population, low incomes, dispersed populations, grossly underdeveloped markets, low capabilities, and poor economies of scale. In other words, the energy policies and strategies for the HKH region have to be specific to these mountain contexts

Thermochemical conversion of guaiacol in aqueous phase by density functional theory

The conversion of guaiacol to benzene, toluene and o-cresol along with several important intermediates like phenol, catechol and others in aqueous phase has been theoretically studied under the framework of density functional theory (DFT). The bond dissociation energy (BDE) calculation has been performed on optimized structures of guaiacol, phenol and anisole; and accordingly several reaction pathways have been proposed. The thermochemical parameters like Gibb's free energy change and enthalpy change of the reactions have also been reported using M06-2X functional. In BDE study of the three compounds, i. e., guaiacol, phenol and anisole, it is observed that the scission of H. at fifth carbon position of an aromatic ring is the highest energy demanding dissociation, whereas the cleavage of bond from the functional group attached to the aromatic ring has the least BDE. The formation of phenol from guaiacol is more likely to occur by simultaneous hydrogenation and demethoxylation of guaiacol amongst all proposed pathways in aqueous phase. Further, decomposition of phenol to benzene is likely to occur via direct dehydroxylation of phenol. The simultaneous hydrogenation and dehydroxylation of guaiacol in aqueous phase are most likely to produce anisole which can further be reduced to phenol by direct cleavage of methyl group followed by hydrogenation. Further, free energy change landscape shows the conversion of guaiacol to phenol to be kinetically most favourable conversion at low temperature and high pressure in the aqueous phase. Finally, the increase in temperature causes a decrease in Gibb's free energy change and enthalpy change of overall reactions, thereby increasing favourability of most of the reactions in aqueous phase. Furthermore, the comparison between gaseous and aqueous phase results have been made wherever applicable

End-group analysis of vinyl polyperoxides by MALDI-TOF-MS, FT-IR technique and thermochemical calculations

A first comprehensive investigation has been made to unequivocally analyze the end groups of two vinyl polyperoxide polymers namely, poly(α-methylstyrene peroxide), and poly(methylmethacrylate peroxide), using matrix-assisted laser desorption ionization-time of flight-mass spectrometry, Fourier transform-infra red techniques and thermochemical calculations. In both the polymers, the end groups formed due to chain transfer reactions were found in large concentrations. Detail mechanism of the formation of end groups has been presented

Thermochemical Mapping of Levulinic Acid Conversion to Pentane in Supercritical Water within the Framework of Density Functional Theory

Undoubtedly, fossil fuels being the primary source of energy have led us to milestone achievements to date. However, its alarming rate of depletion has raised concerns on a global level, which has channelized significant scientific research on biomass-to-biofuel conversion. Nonetheless, the economics of biomass conversion still poses a challenge due to low yield and conversion. In this regard, experimental studies have suggested supercritical water as a medium, which can facilitate better heat and mass transfer amidst the products and reactants. Thus, in this study, the authors applied the density functional theory (DFT) to simulate upgrading of a bio-oil model compound, levulinic acid, under supercritical water conditions. The supercritical water was defined at densities 0.089, 0.109, 0.190, and 0.360 g/cc, and the corresponding parameters (such as dielectric constant, refractive index, hydrogen-bond acidity, basicity, etc.) were manually set in the SMD implicit solvation model. The present method of model description for supercritical water within the framework of DFT is first of its kind and is the most reliable approach owing to validation with experimental results. Further, in this study, numerous pathways elaborating the conversion of levulinic acid to pentane via intermediates like pentanol and acetopropanol were simulated. The kinetic mapping of the pathways was then done by evaluating Gibbs free-energy change and enthalpy change. The supercritical water showed an advantage in deoxygenating compounds with a higher number of oxy groups. However, in some reactions like conversion of 5,5-dihydroxypentan-2-one to 5-hydroxypentan-2-one (γ-Acetopropanol), the effects of temperature and pressure were seen to offset the solvent effect. Of the four supercritical conditions, ρ = 0.109 and 0.360 g/cc were found to be the most favorable supercritical water densities for the conversion of levulinic acid. Overall, the production of pentane from levulinic acid is found to be most advantageous in the supercritical water density of ρ = 0.109 g/cc till pentane-1,4-diol and further conversion to pentane under supercritical conditions of ρ = 0.360 g/cc is the best pathway. Furthermore, the gas phase was found to be the least favorable medium in almost all of the reactions. In contrast, the presence of supercritical water showed an advantage in nearly all of the reactions suggesting supercritical water to be a suitable solvent for the production of biomass-derived chemicals. Thus, this line of investigation warrants further study, especially by experimental groups, to corroborate the findings of this study and scale-up potential

NARX Based Short Term Wind Power Forecasting Model

Nowadays, with the growing needs of the consumers there is a huge demand for the electric power but the fuel reserves are also depleting at the same pace. So, this has created the need to depend up on the renewable energy resources to meet the required power demand.  Since the power generated through renewable resources is eco friendly in nature and distributed, this is an added advantage. Of all the renewable energy resources solar and wind plays the most crucial part in the power generation because of their wide spread availability. But the wind energy is volatile and intermittent by nature, due to this interconnecting the power generated to grid becomes a hectic task. So in this paper a wind power forecasting model with the help of artificial neural networks (ANN) is developed so that the wind power can be forecasted well in progress, which helps in maintaining and operating grid interconnection and also scheduling of units. The developed model is based on the non-linear auto regressive with exogenous input (narx) tool which trains the ANN for the time series. The input parameters taken into consideration are wind speed, temperature, pressure, air density and the output parameter is generated power. The required data is collected from the Energy Department of KLUniversity, Andhra Pradesh which consists of 720 hours data from that 672 hours data is used for training and 48 hours data is used for prediction. Mean square error and root mean square error are calculated from the predicted and known results. DOI: http://dx.doi.org/10.11591/telkomnika.v15i1.807