Automated Slope Stability Analysis of Zoned Dams

The study pertains to the pseudo-static stability analysis of zoned dams with geologic discontinuities in the foundation. Sequential unconstrained minimization technique in conjunction with Janbu\u27s generalized procedure of slices has been used for finding the critical slip surface and the corresponding minimum factor of safety. The method has been found to be quite efficient in solving such problems

From fusion to total disassembly: global stopping in heavy-ion collisions

Using the quantum molecular dynamics model, we aim to investigate the emis- sion of light complex particles, and degree of stopping reached in heavy-ion colli- sions. We took incident energies between 50 and 1000 MeV/nucleon. In addition, central and peripheral collisions and different masses are also considered. We ob- serve that the light complex particles act in almost similar manner as anisotropic ratio. In other words, multiplicity of light complex particles is an indicator of global stopping in heavy-ion collisions. We see that maximum light complex particles and stopping is obtained for heavier masses in central collisions

EMP2 regulates angiogenesis in endometrial cancer cells through induction of VEGF.

Understanding tumor-induced angiogenesis is a challenging problem with important consequences for the diagnosis and treatment of cancer. In this study, we define a novel function for epithelial membrane protein-2 (EMP2) in the control of angiogenesis. EMP2 functions as an oncogene in endometrial cancer, and its expression has been linked to decreased survival. Using endometrial cancer xenografts, modulation of EMP2 expression resulted in profound changes to the tumor microvasculature. Under hypoxic conditions, upregulation of EMP2 promoted vascular endothelial growth factors (VEGF) expression through a HIF-1α-dependent pathway and resulted in successful capillary-like tube formation. In contrast, reduction of EMP2 correlated with reduced HIF-1α and VEGF expression with the net consequence of poorly vascularized tumors in vivo. We have previously shown that targeting of EMP2 using diabodies in endometrial cancer resulted in a reduction of tumor load, and since then we have constructed a fully human EMP2 IgG1. Treatment of endometrial cancer cells with EMP2-IgG1 reduced tumor load with a significant improvement in survival. These results support the role of EMP2 in the control of the tumor microenvironment and confirm the cytotoxic effects observed by EMP2 treatment in vivo

LVQ and backpropagation neural networks applied to NASA SSME data

Feedfoward neural networks with backpropagation learning have been used as function approximators for modeling the space shuttle main engine (SSME) sensor signals. The modeling of these sensor signals is aimed at the development of a sensor fault detection system that can be used during ground test firings. The generalization capability of a neural network based function approximator depends on the training vectors which in this application may be derived from a number of SSME ground test-firings. This yields a large number of training vectors. Large training sets can cause the time required to train the network to be very large. Also, the network may not be able to generalize for large training sets. To reduce the size of the training sets, the SSME test-firing data is reduced using the learning vector quantization (LVQ) based technique. Different compression ratios were used to obtain compressed data in training the neural network model. The performance of the neural model trained using reduced sets of training patterns is presented and compared with the performance of the model trained using complete data. The LVQ can also be used as a function approximator. The performance of the LVQ as a function approximator using reduced training sets is presented and compared with the performance of the backpropagation network

Emergence of metronidazole-resistant Bacteroides fragilis, India.

This article does not have an abstract

Radial basis function neural networks applied to NASA SSME data

This paper presents a brief report on the application of Radial Basis Function Neural Networks (RBFNN) to the prediction of sensor values for fault detection and diagnosis of the Space Shuttle's Main Engines (SSME). The location of the Radial Basis Function (RBF) node centers was determined with a K-means clustering algorithm. A neighborhood operation about these center points was used to determine the variances of the individual processing notes

The first accurate parallax distance to a black hole

Using astrometric VLBI observations, we have determined the parallax of the black hole X-ray binary V404 Cyg to be 0.418 +/- 0.024 milliarcseconds, corresponding to a distance of 2.39 +/- 0.14 kpc, significantly lower than the previously accepted value. This model-independent estimate is the most accurate distance to a Galactic stellar-mass black hole measured to date. With this new distance, we confirm that the source was not super-Eddington during its 1989 outburst. The fitted distance and proper motion imply that the black hole in this system likely formed in a supernova, with the peculiar velocity being consistent with a recoil (Blaauw) kick. The size of the quiescent jets inferred to exist in this system is less than 1.4 AU at 22 GHz. Astrometric observations of a larger sample of such systems would provide useful insights into the formation and properties of accreting stellar-mass black holes.Comment: Accepted for publication in ApJ Letters. 6 pages, 2 figure

Guest Editorial to the Special Letters Issue on Emerging Technologies in Multiparameter Biomedical Optical Imaging and Image Analysis

The past two decades have witnessed revolutionary advances in biomedical imaging modalities capable of providing biological and physiological information from the cellular scale to the organ level. Recent advances have also been focused on cost-effective, noninvasive, portable, and molecularimaging technologies for imaging at microscopic, mesoscopic, and macroscopic levels. These technologies have significant potential to advance biomedical research and clinical practice. They can also provide a better understanding and monitoring of physiological and functional disorders, which could lead to mainstream diagnostic technologies of the future

Positive correlation between menthol content and in vitro menthol tolerance in Mentha arvensis L. cultivars

Menthol is a highly valued monoterpene produced by Japanese mint (Mentha arvensis) as a natural product with wide applications in cosmetics, confectionery, flavours, beverages and therapeutics. Selection of high menthol yielding genotypes is therefore the ultimate objective of all genetic improvement programmes in Mentha arvensis. A positive correlation was observed in the present study between menthol content in oils of evaluated genotypes and the level of tolerance to externally supplied menthol of explants of these genotypes in culture medium. The easy use of this relationship as a selectable biochemical marker opens the practical applicability of largescalein vitro screening of the germplasm, clones and breeders' material for selection of elite genotypes