Application of visual,statistical and artificial neural network methods in the differentiation of water from the exploited aquifers in Kuwait

The ability of artificial neural network to differentiate water samples from the two aquifers of Kuwait on the basis of their major ion chemistry has been demonstrated. The major ion concentration distribution in the groundwater of the Kuwait Group and the Dammam Formation aquifers of Kuwait appears very similar. Cross-plots, supported by the discriminant function analysis of the data, however, suggest that there are some subtle differences in the overall composition of the water from the two aquifers that make it possible to differentiate the water from the two aquifers in almost 80% of the cases. An artificial neural network improved the differentiation capability to 90% of the cases. It is also possible to estimate the fraction of Kuwait Group water in the flow stream of dually completed wells with the help of an artificial neural network developed for this purpose. Electronic Publication     

A coupled,dynamical and chemical model for the prestellar core L1544: Comparison of modeled and observed C<Superscript>18</Superscript>O,HCO<Superscript>+</Superscript>, and CS emission spectra

We consider radiative transfer in C¹⁸O, HCO⁺, and CS molecular lines in a spherically symmetrical, coupled, dynamical and chemical model of a prestellar core whose evolution is determined by ambipolar diffusion. Theoretical and observed line profiles are compared for the well-studied core L1544, which may be a collapsing protostellar cloud. We study the relationship between the line shapes and model parameters. The structure of the envelope and kinematic parameters of the cloud are the most important factors determining the shape of the lines. Varying the input model parameters for the radiative transfer—the kinetic temperature and microturbulent velocity—within the limits imposed by observations does not result in any substantial variations of the line profiles. The comparison between the model and observed spectra indicates that L1544 displays a flattened structure, and is viewed at an oblique angle. A two-dimensional model is needed to reproduce this structure.     

2D stabilised analytic signal method in DC pole-pole potential data interpretation

Using analytic signal method, interpretation of pole-pole secondary electric potentials due to 2D conductive/resistive prisms is presented. The estimated parameters are the location, lateral extent or width and depth to top surface of the prism. Forward modelling is attempted by 2D-Finite Difference method. The proposed stabilised analytic signal algorithm (RES2AS) uses Tikhonov’s regularization scheme and FFT routines. The algorithm is tested on three theoretical examples and field data from the campus of Roorkee University. The stability of RES2AS is also tested on synthetic error prone secondary pole-pole potential data.     

Predators of juvenile blue crabs outside of refuge habitats in lower Chesapeake Bay

Blue crabsCallinectes sapidus in lower Chesapeake Bay are subject to high rates of predation during the late summer of their first year of growth as they migrate out of vegetated nursery habitats. Predators, potentially contributing to this pattern, were identified in video-recorded field observations of tethered juvenile crabs (20–25 mm carapace width). Predators were also tested in large laboratory tanks containing similarly-sized untethered crabs as prey. Seven different predators attacked tethered crabs in the field. Only two predators, larger blue crabs and northern puffers,Sphoeroides maculatus, consistently succeeded in preying on crabs in both field and laboratory settings. These results confirm the importance of cannibalism on juvenile blue crabs and identify puffers as a potentially overlooked source of predation pressure.     

Simulating Temporal Fluctuations of Real Estate Development in a Cellular Automata City

This research aims to understand the source of temporal fluctuations in real estate development through simulating a cellular automata model. In this cellular automata city, investment decisions are made according to the profitability measured in a local neighbourhood. If developers think there is enough of a profit margin in a particular site, i.e. a 'niche' of investment, they will increase investment at that site. However, by increasing investment at the site, new 'niches' might be created. Therefore, the action of converging towards an equilibrium state itself paves the way towards new fluctuations. This model demonstrates the potential of using simulation to increase our understanding of real estate dynamics. The experiments suggest that locally made 'rational' decisions can lead to temporal fluctuations because of non–linearity (discrete changes/densification and local bounded information). Interestingly, the fluctuations may show the property of a temporal fractal. This requires a sufficiently sensitive process of 'niche' formation compared with a relatively large impact of additional investment. The simulation suggests that the impact should be 4 to 20 times higher than the threshold over which a niche will be formed. This condition is satisfied in most cases of real estate investment, thus suggesting a self–organised criticality in complex real estate development.     

按不同气候背景制作单站MOS预报方程

在基层业务体制的框架基本形成以后，县局在参考上级指导预报的同时，初步开展对单站数值预报模式的研究，注意中、小尺度天气的变化规律，以提高订正预报的精度。