1,157 research outputs found
Self-compressed inhomogeneous stabilized jellium model and surface relaxation of simple metal thin films
The interlayer spacings near the surface of a crystal are different from that
of the bulk. As a result, the value of the ionic density in the normal
direction and near to the surface shows some oscillations around the bulk
value. To describe this behavior in a simple way, we have formulated the
self-compressed inhomogeneous stabilized jellium model and have applied it to
simple metal thin films. In this model, for a -layered slab, each ionic
layer is replaced by a jellium slice of constant density. The equilibrium
densities of the slices can be determined by minimizing the total energy per
electron of the slab with respect to the slice densities. To avoid the
complications that arise due to the number of independent slice-density
parameters for large- slabs, we consider a simplified version of the model
with three jellium slices: one inner bulk slice with density and two
similar surface slices of densities . In this simplified model, each
slice may contain more than one ionic layer. Application of this model to the
-layered slabs () of Al, Na, and Cs shows that, in the
equilibrium state, and assume different values, which is
significant in the Al case, and the state is more stable than that predicted in
the homogeneous model in which only one global jellium density is used for the
whole system. In addition, we have calculated the overall relaxations, the work
functions, and the surface energies, and compared with the results of the
earlier works.Comment: 19 pages, 9 figures, in pdf forma
Self-consistent iterative solution of the exchange-only OEP equations for simple metal clusters in jellium model
In this work, employing the exchange-only orbital-dependent functional, we
have obtained the optimized effective potential using the simple iterative
method proposed by K\"ummel and Perdew [S. K\"ummel and J. P. Perdew, Phys.
Rev. Lett. {\bf 90}, 43004-1 (2003)]. Using this method, we have solved the
self-consistent Kohn-Sham equations for closed-shell simple metal clusters of
Al, Li, Na, K, and Cs in the context of jellium model. The results are in good
agreement with those obtained by the different method of Engel and Vosko [E.
Engel and S. H. Vosko, Phys. Rev. B {\bf 50}, 10498 (1994)].Comment: RevTex, 6 pages, 5 eps figures. To appear in Journal of
Physics:Condensed Matter (2005
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Versatile stochastic dot product circuits based on nonvolatile memories for high performance neurocomputing and neurooptimization.
The key operation in stochastic neural networks, which have become the state-of-the-art approach for solving problems in machine learning, information theory, and statistics, is a stochastic dot-product. While there have been many demonstrations of dot-product circuits and, separately, of stochastic neurons, the efficient hardware implementation combining both functionalities is still missing. Here we report compact, fast, energy-efficient, and scalable stochastic dot-product circuits based on either passively integrated metal-oxide memristors or embedded floating-gate memories. The circuit's high performance is due to mixed-signal implementation, while the efficient stochastic operation is achieved by utilizing circuit's noise, intrinsic and/or extrinsic to the memory cell array. The dynamic scaling of weights, enabled by analog memory devices, allows for efficient realization of different annealing approaches to improve functionality. The proposed approach is experimentally verified for two representative applications, namely by implementing neural network for solving a four-node graph-partitioning problem, and a Boltzmann machine with 10-input and 8-hidden neurons
On including quality in applied automatic gait recognition
Many gait recognition approaches use silhouette data. Imperfections in silhouette extraction have a negative effect on the performance of a gait recognition system. In this paper we extend quality metrics for gait recognition and evaluate new ways of using quality to improve a recognition system. We demonstrate use of quality to improve silhouette data and select gait cycles of best quality. The potential of the new approaches has been demonstrated experimentally on a challenging dataset, showing how recognition capability can be dramatically improved. Our practical study also shows that acquiring samples of adequate quality in arbitrary environments is difficult and that including quality analysis can improve performance markedly
Association of Maternal Working Condition with Low Birth Weight: The Social Determinants of Health Approach
Background: The socioeconomic conditions have made more job opportunities available to women. This has created interest to conduct studies on the effect of working lifestyle on pregnancy outcomes. Aim: This study was conducted with the aim to assess the relationship between mothers’ working status as a social determinant and the incidence of low birth weight (LBW) of the newborn. Subjects and Methods: This case–control study was conducted on 500 women with normal weight infants (control group) and 250 women with LBW infants (case group) in selected hospitals in Tehran. Data were collected using a researcher‑made questionnaire, designed to assess the effect of mothers’ prenatal lifestyle, as a social determinant, on LBW of the newborn. A section of the questionnaire involved assessment of mother’s working condition in terms of the work environment, activities, and job satisfaction. Data were analyzed using Chi‑square and logistic regression tests. Results: LBW among employed mothers was 5 times more likely than unemployed ones (odds ratio = 5.35, P < 0.001). Unfavorable work conditions such as humid environment, contact with detergents, and being in one standing or sitting position for long hours were significantly associated with LBW (P < 0.001). Conclusion: The present study showed that unfavorable work conditions were associated with LBW; therefore, they need special attention.Keywords: Low birth weight, Pregnancy, Socioeconomic factors, Working condition
The relationship of social support and quality of life with the level of stress in pregnant women using the PATH model
Background: Lack of adequate social support, stress, and generally poor quality of life during pregnancy leads to adverse pregnancy outcomes for both the mother and the baby. Objectives: This study aimed to investigate the relationship of social support and quality of life with level of stress during pregnancy. Materials and Methods: This was a descriptive-correlative study conducted on 210 pregnant women (meeting study criteria), attending Shahriar Social Services Hospital during 2012. Purposive convenient sampling was used. Study subjects completed questionnaires of obstetrics and demographics, VAUX social support, World Health Organization quality of life, and stress during pregnancy. Data were analyzed with SPSS-19 and Lisrel 8.8, utilizing statistical path analysis. Results: The final path model fitted well (CF1 = 1, RMSEA = 0.00) and showed that direct quality of life paths with β = -0.2, and indirect social support with β = -0.088 had the most effects on reduction of stress during pregnancy. Conclusion: Social support indirectly and quality of life directly affect stress during pregnancy. Thus, health officials should attempt to establish measures to further enhance social support and quality of life of pregnant women to reduce stress and its consequences during this time. © 2013, Iranian Red Crescent Medical Journal
Practical Fss-Based Sensor Sensitivity
Frequency selective surfaces are a periodic array of unit cells that, when illuminated externally, have a specific frequency response that depends on element geometry, spacing, and substrate properties. Theoretically, FSS is assumed as an infinite array of unit cells with a plane wave excitation. However, in practice, an FSS is finite and hence, due to edge effects, the limited number of unit cells, and non-uniform illumination, the response will deviate from the theoretical. As it relates to FSS-based sensing in particular, a localized illumination is often used in order to improve the sensing resolution. However, due to the aforementioned factors, the sensitivity of the sensor may suffer as a result. Hence, the effect of these factors is studied on the FSS sensor response. Then, taking strain measurement as an example, the degradation in the sensor sensitivity to strain is evaluated in comparison with that of a theoretical FSS. The simulation results show that a finite FSS with non-uniform illumination has reduced sensitivity to strain. This degradation in sensitivity of reduces as the number of illuminated unit cells increases. However, the sensitivity of a finite FSS with uniform illumination is nearly constant with respect to the number of illuminated unit cells
Two-Dimensional In-Plane Strain Fss-Based Sensor
Frequency selective surface (FSS) based sensors have found application as sensors in the last decade. In this paper, a new sensor design is proposed for two-dimensional in-plane strain sensing. The unit cell of the FSS-based sensor includes two slot dipoles, oriented normal to one another and each with different dimensions, to create two unique resonant frequencies when interrogated with an incident electric field normal to the direction of measured strain. In this way, 2D strain can be characterized concurrently and independently. The error due to strain orthogonal to the direction of interest, along with the error due to the presence of shear strain, has also been characterized. The sensor has a maximum of 12% error for an applied strain due to 4% strain orthogonal to the measurement direction, and no more than 8% error for a maximum of 4% of shear strain
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