An optical spectroscopic HR diagram for low-mass stars and brown dwarfs in Orion

The masses and temperatures of young low-mass stars and brown dwarfs in star-forming regions are not yet well established because of uncertainties in the age of individual objects and the spectral type–temperature scale appropriate for objects with ages of only a few Myr. Using multi-object optical spectroscopy, 45 low-mass stars and brown dwarfs in the Trapezium Cluster in Orion have been classified and 44 of these confirmed as bona fide cluster members. The spectral types obtained have been converted to effective temperatures using a temperature scale intermediate between those of dwarfs and giants, which is suitable for young pre-main-sequence objects. The objects have been placed on a Hertzsprung–Russell (HR) diagram overlaid with theoretical isochrones. The low-mass stars and the higher mass substellar objects are found to be clustered around the 1 Myr isochrone, while many of the lower mass substellar objects are located well above this isochrone. An average age of 1 Myr is found for the majority of the objects. Assuming coevality of the sources and an average age of 1 Myr, the masses of the objects have been estimated and range from  0.018 to 0.44 M_⊙  . The spectra also allow an investigation of the surface gravity of the objects by measurement of the sodium doublet equivalent width. With one possible exception, all objects have low gravities, in line with young ages, and the Na indices for the Trapezium objects lie systematically below those of young stars and brown dwarfs in Chamaeleon, suggesting that the 820 nm Na index may provide a sensitive means of estimating ages in young clusters.     

Optical spectroscopic classification and membership of young M dwarfs in star-forming regions

The spectral type is a key parameter in calibrating the temperature which is required to estimate the mass of young stars and brown dwarfs. We describe an approach developed to classify low-mass stars and brown dwarfs in the Trapezium Cluster using red optical spectra, which can be applied to other star-forming regions. The classification uses two methods for greater accuracy: the use of narrow-band spectral indices which rely on the variation of the strength of molecular lines with spectral type and a comparison with other previously classified young, low-mass objects in the Chamaeleon I star-forming region. We have investigated and compared many different molecular indices and have identified a small number of indices which work well for classifying M-type objects in nebular regions. The indices are calibrated for young, pre-main-sequence objects whose spectra are affected by their lower surface gravities compared with those on the main sequence. Spectral types obtained are essentially independent of both reddening and nebular emission lines.
Confirmation of candidate young stars and brown dwarfs as bona fide cluster members may be accomplished with moderate resolution spectra in the optical region by an analysis of the strength of the gravity-sensitive Na doublet. It has been established that this feature is much weaker in these very young objects than in field dwarfs. A sodium spectral index is used to estimate the surface gravity and to demonstrate quantitatively the difference between young (1–2 Myr) objects, and dwarf and giant field stars.     

Sheathed prokaryotic filaments,major components of Mid-Cretaceous French amber microcoenoses

Prokaryotes were the first organisms to colonize Earth, but little evidence of their existence has been found in the fossil record. Recent studies of amber, a fossil resin from gymnosperms or angiosperms, have revealed a number of rarely fossilized microorganisms. Several amber-bearing localities of Mid-Cretaceous age in southwestern France (Charentes and Aude regions) led to the discovery of a rich and diverse biota of resin-preserved microorganisms. These amber microcoenoses are dominated by sheathed prokaryotic filaments similar to those of the cyanobacterium Palaeocolteronema cenomanensis Breton and Tostain (2005) and to those of the bacterium Leptotrichites resinatus Schmidt 2005. These sheathed filaments appear as peripheral cortexes around some pieces of amber from the Charentes outcrops and as peripheral dark areas on amber from the Aude locality. Macroscopic and microscopic features, as well as measurements of phycocyanin concentrations from the filaments, made it possible to identify two different taxa. The sheathed filaments from Charentes correspond to P. cenomanensis. They were growing in freshwater ponds when amber trapped them. Those of the Aude outcrop represent L. resinatus. The latter were probably trapped in less humid environments than were P. cenomanensis filaments.     

Drivers of afforestation in Northern Vietnam: Assessing local variations using geographically weighted regression

This article identifies drivers of forest transition in a province of Northern Vietnam between 1993 and 2000 by applying geographically weighted regression (GWR) analysis to remotely sensed and statistical data. The regression model highlighted the spatial variation of the relationship between the percentage of land afforested and its proximate causes. Factors identified as having a major impact on afforestation are: the presence or proximity of a wood-processing industry, the distance to highways, and land allocation to households. Whereas the two former variables are in most areas of the province positively correlated with afforestation, an unexpected negative correlation was observed for the latter. The analysis of these results, supported by an in-depth knowledge of the area and of the political context, leads to the conclusion that, during the time period considered, afforestation was largely driven by state organisations on protected state-owned land, and forestry was not a significant component of household economic activities.     

Multiobjective fuzzy optimization for sustainable groundwater management using particle swarm optimization and analytic element method

Groundwater management involves conflicting objectives as maximization of discharge contradicts the criteria of minimum pumping cost and minimum piping cost. In addition, available data contains uncertainties such as market fluctuations, variations in water levels of wells and variations of ground water policies. A fuzzy model is to be evolved to tackle the uncertainties, and a multiobjective optimization is to be conducted to simultaneously satisfy the contradicting objectives. Towards this end, a multiobjective fuzzy optimization model is evolved. To get at the upper and lower bounds of the individual objectives, particle Swarm optimization (PSO) is adopted. The analytic element method (AEM) is employed to obtain the operating potentio metric head. In this study, a multiobjective fuzzy optimization model considering three conflicting objectives is developed using PSO and AEM methods for obtaining a sustainable groundwater management policy. The developed model is applied to a case study, and it is demonstrated that the compromise solution satisfies all the objectives with adequate levels of satisfaction. Sensitivity analysis is carried out by varying the parameters, and it is shown that the effect of any such variation is quite significant. Copyright © 2015 John Wiley & Sons, Ltd.     

Application of Artificial Neural Network Model for the Prediction of Suspended Sediment Load in the Large River

Water Resources - Predicting the Suspended Sediment Load (SSL) of the river is a very significant and challenging task. Being a non-linearity in the SSL data, it requires a non-linear method to get...