987 resultados para Theoretical prediction


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Fetal lung and liver tissues were examined by ultrasound in 240 subjects during 24 to 38 weeks of gestational age in order to investigate the feasibility of predicting the maturity of the lung from the textural features of sonograms. A region of interest of 64 X 64 pixels is used for extracting textural features. Since the histological properties of the liver are claimed to remain constant with respect to gestational age, features obtained from the lung region are compared with those from liver. Though the mean values of some of the features show a specific trend with respect to gestation age, the variance is too high to guarantee definite prediction of the gestational age. Thus, we restricted our purview to an investigation into the feasibility of fetal lung maturity prediction using statistical textural features. Out of 64 features extracted, those features that are correlated with gestation age and less computationally intensive are selected. The results of our study show that the sonographic features hold some promise in determining whether the fetal lung is mature or immature.

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Rotational spectra of five isotopologues of the title complex, C(6)H(5)CCH center dot center dot center dot H(2)O, C(6)H(5)CCH center dot center dot center dot HOD, C(6)H(5)CCH center dot center dot center dot D(2)O, C(6)H(5)CCH center dot center dot center dot H(2)(18)O and C(6)H(5)CCD center dot center dot center dot H(2)O, were measured and analyzed. The parent isotopologue is an asymmetric top with kappa = -0.73. The complex is effectively planar (ab inertial plane) and both `a' and `b' dipole transitions have been observed but no c dipole transition could be seen. All the transitions of the parent complex are split into two resulting from an internal motion interchanging the two H atoms in H(2)O. This is confirmed by the absence of such doubling for the C(6)H(5)CCH center dot center dot center dot HOD complex and a significant reduction in the splitting for the D(2)O analog. The rotational spectra, unambiguously, reveal a structure in which H(2)O has both O-H center dot center dot center dot pi (pi cloud of acetylene moiety) and C-H center dot center dot center dot O (ortho C-H group of phenylacetylene) interactions. This is in agreement with the structure deduced by IR-UV double resonance studies (Singh et al., J. Phys. Chem. A, 2008, 112, 3360) and also with the global minimum predicted by advanced electronic structure theory calculations (Sedlack et al., J. Phys. Chem. A, 2009, 113, 6620). Atoms in Molecule (AIM) theoretical analysis of the complex reveals the presence of both O-H center dot center dot center dot pi and C-H center dot center dot center dot O hydrogen bonds. More interestingly, based on the electron densities at the bond critical points, this analysis suggests that both these interactions are equally strong. Moreover, the presence of both these interactions leads to significant deviation from linearity of both hydrogen bonds.

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In this paper, we compare the electronic structure of the hafnacycloallene complex Cp(2)HfC(4)Rr'(2)R `' (5Hf), which was previously described by Erker et al., with those of the titanium, zirconium, and hafnium complexes Cp(2)M(eta(4)-RHC(4)HR) (3M; i.e. metallacyclopent-2,3,4-trienes, metallacyclocumulenes) and Cp(2)M(eta(2)-R(2)C(4)R(2)) (4M; i.e. 1-metallacyclopent-3-ynes) using density functional theory (BP86/LANL2DZ) calculations. Moreover, the eta(3)-phenylallenyl zirconocene complex 7Zr, which was synthesized by Wojcicki et al., is included for the comparison. These calculations and extended Huckel calculations show that the bonding in complex 5Hf is remarkably similar to that of complexes 4M and 7Zr. An analysis of the structural parameters and bonding reveals that the unique interaction of the internal carbon atoms along with the terminal carbon atoms with the bent-metallocene moiety is the reason for the unusual stability of these metallacycles. The molecular orbital analysis further suggests that complex 5Hf can react with another metal fragment to give the bimetallic complexes 9 and 10. The electronic structures of complexes 3M, 4M, 5Hf, and 7Zr have been comparatively studied to get a general understanding of the bonding in these metallacycles.

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In this paper, we model dwarf galaxies as a two-component system of gravitationally coupled stars and atomic hydrogen gas in the external force field of a pseudo-isothermal dark matter halo, and numerically obtain the radial distribution of HI vertical scale heights. This is done for a group of four dwarf galaxies (DDO 154, Ho II, IC 2574 and NGC 2366) for which most necessary input parameters are available from observations. The formulation of the equations takes into account the rising rotation curves generally observed in dwarf galaxies. The inclusion of self-gravity of the gas into the model at par with that of the stars results in scale heights that are smaller than what was obtained by previous authors. This is important as the gas scale height is often used for deriving other physical quantities. The inclusion of gas self-gravity is particularly relevant in the case of dwarf galaxies where the gas cannot be considered a minor perturbation to the mass distribution of the stars. We find that three out of four galaxies studied show a flaring of their HI discs with increasing radius, by a factor of a few within several disc scale lengths. The fourth galaxy has a thick HI disc throughout. This flaring arises as a result of the gas velocity dispersion remaining constant or decreasing only slightly while the disc mass distribution declines exponentially as a function of radius.

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The applicability of Artificial Neural Networks for predicting the stress-strain response of jointed rocks at varied confining pressures, strength properties and joint properties (frequency, orientation and strength of joints) has been studied in the present paper. The database is formed from the triaxial compression tests on different jointed rocks with different confining pressures and different joint properties reported by various researchers. This input data covers a wide range of rock strengths, varying from very soft to very hard. The network was trained using a 3 layered network with feed forward back propagation algorithm. About 85% of the data was used for training and remaining15% for testing the predicting capabilities of the network. Results from the analyses were very encouraging and demonstrated that the neural network approach is efficient in capturing the complex stress-strain behaviour of jointed rocks. A single neural network is demonstrated to be capable of predicting the stress-strain response of different rocks, whose intact strength vary from 11.32 MPa to 123 MPa and spacing of joints vary from 10 cm to 100 cm for confining pressures ranging from 0 to 13.8 MPa.

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Many shallow landslides are triggered by heavy rainfall on hill slopes resulting in enormous casualties and huge economic losses in mountainous regions. Hill slope failure usually occurs as soil resistance deteriorates in the presence of the acting stress developed due to a number of reasons such as increased soil moisture content, change in land use causing slope instability, etc. Landslides triggered by rainfall can possibly be foreseen in real time by jointly using rainfall intensity-duration and information related to land surface susceptibility. Terrain analysis applications using spatial data such as aspect, slope, flow direction, compound topographic index, etc. along with information derived from remotely sensed data such as land cover / land use maps permit us to quantify and characterise the physical processes governing the landslide occurrence phenomenon. In this work, the probable landslide prone areas are predicted using two different algorithms – GARP (Genetic Algorithm for Rule-set Prediction) and Support Vector Machine (SVM) in a free and open source software package - openModeller. Several environmental layers such as aspect, digital elevation data, flow accumulation, flow direction, slope, land cover, compound topographic index, and precipitation data were used in modelling. A comparison of the simulated outputs, validated by overlaying the actual landslide occurrence points showed 92% accuracy with GARP and 96% accuracy with SVM in predicting landslide prone areas considering precipitation in the wettest month whereas 91% and 94% accuracy were obtained from GARP and SVM considering precipitation in the wettest quarter of the year.