Unified formation of astronomical objects up to stellar mass range

In dense interstellar clouds or in the surroundings of just-formed stars, the larger grains form proto-cores by segregating from the gas under the influence of the gravitational field of the cloud during intervals of the order 10⁸ yr.If the mass of the proto-cores is smaller than a certain limit, the object possesses a negligible atmosphere and remains composed mainly of solid grain material. If the mass of the proto-core exceeds the limiting mass, the proto-core can bind around it an atmosphere. When the temperature of the opaque part of the atmosphere is only fractions of a degree above the temperature of the surrounding tenuous gas, gravitational contraction of the opaque part of the atmosphere sets in, forming gaseous objects up to stellar mass range.Binary and multiple systems originate from neighbouring proto-cores, through gravitational contraction of both their separate and common outer atmospheres.Pycnonuclear reactions are not able to prevent a star with mass 0.08M from cooling to the black dwarf stadium.     

Optimal selection of artificial neural network parameters for the prediction of a karstic aquifer's response

The simulation of karstic aquifers is difficult using traditional groundwater numerical simulators, as the exact knowledge of the hydraulic characteristics of the physical system in small scale is rarely available and the numerical simulators produce results of limited reliability. In the present work, artificial neural networks (ANNs) are utilized to predict the response of a karstic aquifer, using the hydraulic head change per time step rather than the hydraulic head itself as output parameter of the network. As it will be demonstrated, in the first case a better approximation of the physical system's response is achieved as the change of the hydraulic head is more naturally connected to the input parameters of the network, which model the aquatic equilibrium of the system. The correlation of rainfall and hydraulic head change per time step was initially used to determine the time lag of the rainfall input data, which represents the time needed by the rainfall to percolate and reach the water table. In a second step, a differential evolution (DE) algorithm is utilized for the optimal selection of rainfall time lag as well as ANN's architecture and training parameters. Although a time consuming procedure, the improvement obtained suggests that the empirical determination of the ANN parameters and structure is not always sufficient and an optimization procedure, which minimizes the training and evaluation errors of the ANN, may provide substantially better simulation results. The optimized networks were finally used for midterm predictions (30 to 90 days ahead) of the hydraulic head, showing the ability of the ANN with hydraulic head change as output parameter to provide predictions with high accuracy at the end of the considered time period. Copyright © 2009 John Wiley & Sons, Ltd.     

Effects of mechanical macrophyte control on suspended sediment concentrations in streams

Suspended sediment (SS) is an important pollutant in freshwater ecosystems and can be detrimental to fish communities. Although macrophytes mediate sediment deposition, little effort has been put into determining how their removal affects sediment resuspension. The present study examined the immediate and long-term impacts of mechanical macrophyte removal on SS concentrations in streams. The results of this study suggest that bed disturbance during mechanical excavation of macrophytes significantly increases SS in the short term, and concentrations were found to increase by as much as 15,687 mg L^–1 immediately after macrophyte removal. Significant long-term (77 day) increases in SS were also observed, indicating that without macrophytes, disturbed material is continually resuspended after excavation by fluvial processes. These results demonstrate that macrophyte removal can result in SS levels that have previously been shown to harm fish, and indicate that this activity may be more detrimental to fish than previously thought.     

Artificial neural networks as an alternative approach to groundwater numerical modelling and environmental design

Classical optimization methodologies based on mathematical theories have been developed for the solution of various constrained environmental design problems. Numerical models have been widely used to represent an environmental system accurately. The use of methodologies such as artificial neural networks (ANNs), which approximate the complicated behaviour and response of physical systems, allows the optimization of a large number of case scenarios with different set of constraints within a short period of time, whereas the corresponding simulation time using a numerical model would be prohibitive. In this paper, a combination of an ANN with a differential evolution algorithm is proposed to replace the classical finite‐element numerical model in water resources management problems. The objective of the optimization problem is to determine the optimal operational strategy for the productive pumping wells located in the northern part of Rhodes Island in Greece, to cover the water demand and maintain the water table at certain levels. The conclusions of this study show that the use of ANN as an approximation model could (a) significantly reduce the computational burden associated with the accurate simulation of complex physical systems and (b) provide solutions very close to the optimal ones for various constrained environmental design problems. Copyright © 2008 John Wiley & Sons, Ltd.     

On the theoretical possibility of the libration cloud

We show within the framework of the restricted three body problem that

1. Only in the immediate neighbourhood of the Lagrangian pointsL ₄ andL ₅ the distribution of a cloud of particles tends to become uniform under the influence of random stochastic perturbations. No consequences can be derived from this fact for a tendency of dispersion of clouds librating at arbitrary distances around the Lagrangian points.
2. From an elementary inspection of the Jacobi integral we cannot conclude that mutual completely inelastic collisions tend to drive the particles away from the vicinity of the libration points.

Finally the motion of a particle within the libration cloud, approximated as a resisting medium, is briefly examined.     

A coupled groundwater-flow-modelling and vulnerability-mapping methodology for karstic terrain management

A coupled groundwater-flow-modelling and vulnerability-mapping methodology for the management of karst aquifers with spatial variability is developed. The methodology takes into consideration the duality of flow and recharge in karst and introduces a simple method to integrate the effect of temporal storage in the unsaturated zone. In order to investigate the applicability of the developed methodology, simulation results are validated against available field measurement data. The criteria maps from the PaPRIKa vulnerability-mapping method are used to document the groundwater flow model. The FEFLOW model is employed for the simulation of the saturated zone of Palaikastro-Chochlakies karst aquifer, in the island of Crete, Greece, for the hydrological years 2010–2012. The simulated water table reproduces typical karst characteristics, such as steep slopes and preferred drain axes, and is in good agreement with field observations. Selected calculated error indicators—Nash-Sutcliffe efficiency (NSE), root mean squared error (RMSE) and model efficiency (E′)—are within acceptable value ranges. Results indicate that different storage processes take place in different parts of the aquifer. The north-central part seems to be more sensitive to diffuse recharge, while the southern part is affected primarily by precipitation events. Sensitivity analysis is performed on the parameters of hydraulic conductivity and specific yield. The methodology is used to estimate the feasibility of artificial aquifer recharge (AAR) at the study area. Based on the developed methodology, guidelines were provided for the selection of the appropriate AAR scenario that has positive impact on the water table.