2,586 research outputs found

    Automated Slope Stability Analysis of Zoned Dams

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    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

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    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

    LVQ and backpropagation neural networks applied to NASA SSME data

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    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.

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    Radial basis function neural networks applied to NASA SSME data

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    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

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    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

    Male factor infertility with Azoospermia: our experience in a tertiary care centre

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    Azoospermia is the absence of spermatozoa in two separate centrifuged semen samples. It is one of the major contributors of male factor infertility. Usually detected in the course of infertility evaluation. Many forms of azoospermia are amenable to medical treatment. Authors report a case series of 16 cases of infertility with Azoospermia which were managed in the Assisted reproductive technology centre of a tertiary care teaching hospital of the Indian Navy in Mumbai between Jun 2022 to Jul 2023. Out of the 16 cases 13 cases underwent surgical sperm retrieval by PESA/TESE. We could retrieve sperms in 11 cases. In 5 cases the retrieved sperms were motile and in 6 cases immotile sperms were obtained. ICSI done with both motile and immotile sperms resulted in fertilization. Our study shows that IVF-ICSI can produce successful fertilization even with Immature sperms or sperms obtained directly from the testicular tissue and IVF-ICSI allows for pregnancy in couple where the man has irreversible azoospermia as long as it is possible to recover sperm from the testes

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

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    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
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