40 research outputs found
Population dynamics of citrus whitefly, Dialeurodes citri (Ashmead) on Citrus reticulate (Mandarin) var. Kinnow as influenced by weather conditions
A field study on population dynamics of citrus whitefly, Dialeurodes citri (Ashmead) on citrus mandarin (var. Kinnow) was carried out during 2014-15 at Centre of Excellence (COE) for Fruits situated in village Mangiana of district Sirsa, Haryana. The population of nymphs and adults of this pest was recorded from March 2014 to February 2015 at weekly interval. The nymphal population of the pest was observed only between 12th to 47th meteorological standard weeks (SW) with two major peaks i.e. one during 16th SW with a population of 83.44 nymphs/ 20 leaves and the second during 40th SW with a population of 133.22 nymphs/20 leaves. The above said population dynamics confirmed that this pest remained inactive in pupal stage during winter i.e. 48th to 11th SW. Similar trend was observed in respect of adult population. Nymphal population showed significant positive correlation with morning relative humidity (r = 0.329) and sunshine hours (r = 0.362), while adult population was found to have positive correlation with sunshine hours only (r = 0.332). Multiple regression analysis of the pest population with environment variables indicated that out of 45 per cent variability in nymphal population, 37 per cent was due to relative humidity and sunshine hours. Out of the total variability of 30 per cent variation in adult population, 20 per cent was due to evening relative humidity, while 10 per cent attributed to sunshine hours. The other weather parameters were found to have no significant correlation with the pest population. Although study of population dynamics of this study were conducted elsewhere but this is first study of its kind in the state of Haryana. The population dynamics revealed by this study have far reaching significance in pest management strategy as integrated control measures may be focused only during the period wherein population exceeds economic threshold level (ETL). The information on population dynamics of any insect pest in a given ecological niche should be considered as starting point for evolving eco - friendly pest management package
A novel plasmonic interferometry and the potential applications
In this article, we have proposed the plasmonic interferometry concept and analytical details given. By using the conventional optical interferometry, which can be simply calculated by using the relationship between the electric field and electron mobility, the interference mobility visibility (fringe visibility) can be observed. The surface plasmons in the sensing arm of the Michelson interferometer is constructed by the stacked layers of the silicon-graphene-gold, allows to characterize the spatial resolution of light beams in terms of the electron mobility down to 100-nm scales, with measured coherence lengths as low as ∼100 nm for an incident wavelength of 1550 nm. We have demonstrated a compact plasmonic interferometer that can apply to the electron mean free paths measurement, from which the precise determination can be used for the high-resolution mean free path measurement and sensing applications. This system provides the practical simulation device parameters that can be fabricated and tested by the experimental platform
Mathematical Model of Plasmid-Mediated Resistance to Ceftiofur in Commensal Enteric Escherichia coli of Cattle
Antimicrobial use in food animals may contribute to antimicrobial resistance in bacteria of animals and humans. Commensal bacteria of animal intestine may serve as a reservoir of resistance-genes. To understand the dynamics of plasmid-mediated resistance to cephalosporin ceftiofur in enteric commensals of cattle, we developed a deterministic mathematical model of the dynamics of ceftiofur-sensitive and resistant commensal enteric Escherichia coli (E. coli) in the absence of and during parenteral therapy with ceftiofur. The most common treatment scenarios including those using a sustained-release drug formulation were simulated; the model outputs were in agreement with the available experimental data. The model indicated that a low but stable fraction of resistant enteric E. coli could persist in the absence of immediate ceftiofur pressure, being sustained by horizontal and vertical transfers of plasmids carrying resistance-genes, and ingestion of resistant E. coli. During parenteral therapy with ceftiofur, resistant enteric E. coli expanded in absolute number and relative frequency. This expansion was most influenced by parameters of antimicrobial action of ceftiofur against E. coli. After treatment (>5 weeks from start of therapy) the fraction of ceftiofur-resistant cells among enteric E. coli, similar to that in the absence of treatment, was most influenced by the parameters of ecology of enteric E. coli, such as the frequency of transfer of plasmids carrying resistance-genes, the rate of replacement of enteric E. coli by ingested E. coli, and the frequency of ceftiofur resistance in the latter
An antibiotic linked to peptides and proteins is released by electron capture dissociation fourier transform ion cyclotron resonance mass spectrometry
A Semantically Data-Driven Classification Framework for Energy Consumption in Buildings
Encouraged by the European Union, all European countries need to enforce solutions to reduce non-renewable energy consumption in buildings. The reduction of energy (heating, domestic hot water, and appliances consumption) aims for the vision of near-zero energy consumption as a requirement goal for constructing buildings. In this paper, we review the available standards, tools and frameworks on the energy performance of buildings. Additionally, this work investigates if energy performance ratings can be obtained with energy consumption data from IoT devices and if the floor size and energy consumption values are enough to determine a dwellings’ energy performance rating. The essential outcome of this work is a data-driven prediction tool for energy performance labels that can run automatically. The tool is based on the cutting edge kNN classification algorithm and trained on open datasets with actual building data such as those coming from the IoT paradigm. Additionally, it assesses the results of the prediction by analysing its accuracy values. Furthermore, an approach to semantic annotations for energy performance certification data with currently available ontologies is presented. Use cases for an extension of this work are also discussed in the end
A Semantically Data-Driven Classification Framework for Energy Consumption in Buildings
Encouraged by the European Union, all European countries need to enforce solutions to reduce non-renewable energy consumption in buildings. The reduction of energy (heating, domestic hot water, and appliances consumption) aims for the vision of near-zero energy consumption as a requirement goal for constructing buildings. In this paper, we review the available standards, tools and frameworks on the energy performance of buildings. Additionally, this work investigates if energy performance ratings can be obtained with energy consumption data from IoT devices and if the floor size and energy consumption values are enough to determine a dwellings’ energy performance rating. The essential outcome of this work is a data-driven prediction tool for energy performance labels that can run automatically. The tool is based on the cutting edge kNN classification algorithm and trained on open datasets with actual building data such as those coming from the IoT paradigm. Additionally, it assesses the results of the prediction by analysing its accuracy values. Furthermore, an approach to semantic annotations for energy performance certification data with currently available ontologies is presented. Use cases for an extension of this work are also discussed in the end
Bacillus amyloliquefaciens induces production of a novel blennolide K in coculture of Setophoma terrestris
The discovery of known bioactive chemical leads from microbial monocultures hinders the efficiency of drug discovery programmes. Therefore, in recent years, the use of fungal–bacterial coculture experiments has gained considerable attention due to their ability to generate new bioactive leads. In this work, fungal strain Setophoma terrestris was cocultured with Bacillus amyloliquifaciens to discover novel bioactive compounds