3,170 research outputs found
Characterizing small-scale migration behavior of sequestered CO2 in a realistic geological fabric
For typical reservoir conditions, buoyancy and capillary forces grow dominant over viscous forces within a few hundred meters of the injection wells as the pressure gradient due to injection decreases, resulting in qualitatively different plume migration regimes. The migration regime depends on two factors: the capillary pressure of the leading edge of the plume and the range of
threshold entry pressures within the rock at the leading edge of the plume. A capillary channel regime arises when these two factors have the same magnitude. Flow patterns within this regime vary from finger-like structures with minimal rock contact to back-filling structures with compact volumes of saturation distributed between fingers. Reservoir heterogeneity is one of the
principal factors influencing CO2 migration pathway in the capillary channel regime. Here we characterize buoyancy-driven migration in a natural 2D geologic domain (1 m × 0.5 m peel from an alluvium) in which sedimentologic heterogeneity has been resolved at sub-millimeter (depositional) resolution. The relevant features of the heterogeneity are grain size distribution, which determines the mean and range of threshold pressures and correlation lengths of threshold pressures in horizontal and vertical directions. The relevant physics for this migration regime is invasion percolation, and simulations indicate that CO2 migrates through the peel in a few narrow pathways which cannot be captured by conventional coarse-grid simulations. The storage
efficiency of the capillary channel regime would be low and consequently CO2 would also migrate greater distances than expected from models or simulations that neglect the capillary channel flow regime.Bureau of Economic Geolog
CCD BVRI and 2MASS Photometry of the Poorly Studied Open Cluster NGC 6631
Here we have obtained the {\it BVRI CCD} photometry down to a limiting
magnitude of 20 for the southern poorly studied open cluster NGC 6631.
It is observed from the {\it 1.88 m} Telescope of Kottamia Observatory in
Egypt. About 3300 stars have been observed in an area of around the cluster center. The main photometric parameters
have been estimated and compared with the results that determined for the
cluster using {\it JHKs 2MASS} photometric database. The cluster's diameter is
estimated to be 10 arcmin; the reddening E(B-V)= 0.68 0.10 mag, E(J-H)=
0.21 0.10 mag, the true modulus (m-M)= 12.16 0.10 mag, which
corresponds to a distance of 2700 125 pc and age of 500 50 Myr.Comment: 13 pages, 6 figure
Human T Lymphotropic Virus Type 1 (HTLV-1): Molecular Biology and Oncogenesis
Human T lymphotropic viruses (HTLVs) are complex deltaretroviruses that do not contain a proto-oncogene in their genome, yet are capable of transforming primary T lymphocytes both in vitro and in vivo. There are four known strains of HTLV including HTLV type 1 (HTLV-1), HTLV-2, HTLV-3 and HTLV-4. HTLV-1 is primarily associated with adult T cell leukemia (ATL) and HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP). HTLV-2 is rarely pathogenic and is sporadically associated with neurological disorders. There have been no diseases associated with HTLV-3 or HTLV-4 to date. Due to the difference in the disease manifestation between HTLV-1 and HTLV-2, a clear understanding of their individual pathobiologies and the role of various viral proteins in transformation should provide insights into better prognosis and prevention strategies. In this review, we aim to summarize the data accumulated so far in the transformation and pathogenesis of HTLV-1, focusing on the viral Tax and HBZ and citing appropriate comparisons to HTLV-2
Early Disease Detection Through Nail Image Processing Based on Ensemble of Classifier Models
Medical science has progressed in many ways and different methods have been developed for the diagnosis of diseases in the human body and one of the ways to identify the diseases is through the close examination of nails of the human palm. The main aim of this study is to compare the performance of various classifier models that are used for the prediction of various diseases. The Performance analysis is done by applying image processing, different data mining and machine learning techniques to the extracted nail image through our proposed system which does nail analysis using a combination of 13 features (Nail Color, Shape and Texture) extracted from the nail image. In this paper we have compared different machine learning classifiers like Support Vector Machine, Multiclass SVM and K-Nearest Neighbor through ensemble of these classifiers with different features so as to classify patients with different diseases like Psoriasis, Red Lunula, Beau�s Lines, Clubbing, etc. These approaches were tested with data images from Hospitals and workplaces. The performance of the different classifiers have been measured in terms of Accuracy, Sensitivity and Specificity
Low-Temperature Spin Dynamics of Doped Manganites: roles of Mn-t2g and eg and O-2p states
The low-temperature spin dynamics of doped manganites have been analyzed
within a tight-binding model, the parameters of which are estimated by mapping
the results of ab initio density functional calculations onto the model. This
approach is found to provide a good description of the spin dynamics of the
doped manganites, observed earlier within the ab initio calculations. Our
analysis not only provides some insight into the roles of the eg and the t2g
states but also indicates that the oxygen p states play an important role in
the spin dynamics. This may cast doubt on the adaptability of the conventional
model Hamiltonian approaches to the analysis of spin dynamics of doped
manganites.Comment: 12 pages; Includes 5 figure
VAr Compensation Based Stability Enhancement Of Wind Turbine Using STATCOM
Maintenance of power system stability becomes vital during disturbances like faults, contingency etc. This work deals with a novel priority oriented optimal reactive power compensation of Doubly-Fed Induction Generator (DFIG) based wind turbine using Static Synchronous Compensator (STATCOM). A multi-objective problem will be formulated to maintain voltage within its tolerance levels using Voltage Severity Index (VSI) and to mitigate low frequency oscillations by using Transient Power Severity Index (TPSI) during post-fault conditions. An optimal solution to this proposed problem will be obtained using Fuzzy Logic. In order to justify the proposed methodology it is simulated and tested using 2 MW DFIG with MATLAB- Simulink.nbs
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