675 research outputs found
Scattering states of a particle, with position-dependent mass, in a double heterojunction
In this work we obtain the exact analytical scattering solutions of a
particle (electron or hole) in a semiconductor double heterojunction -
potential well / barrier - where the effective mass of the particle varies with
position inside the heterojunctions. It is observed that the spatial dependence
of mass within the well / barrier introduces a nonlinear component in the plane
wave solutions of the continuum states. Additionally, the transmission
coefficient is found to increase with increasing energy, finally approaching
unity, whereas the reflection coefficient follows the reverse trend and goes to
zero.Comment: 7 pages, 6 figure
Detection Efficiency of NaI(Tl) Detector in 511–1332 keV Energy Range
As it is important to obtain accurate analytical result in an experimental research, this required quality control of the experimental system. Gamma spectrometry system can be used in a variety of different fields such as radiation and medical physics. In this paper the absolute efficiency, peak to valley ratio, and energy resolution of a 3′′×3′′ NaI(Tl) detector were determined experimentally for 511, 662, 835, 1173, 1275, and 1332 keV photon energies obtained from 22Na, 54Mn, 60Co, and 137Cs radioactive sources
Randomized, Placebo-Controlled Trial of Transplacental Antibiotic Prophylaxis of Neonatal Group B Streptococcal Colonization and Bacteremia in Rabbits
Objective: We evaluated the effect of maternal administration of ampicillin/sulbactam on colonization and bacteremia in newborn rabbits after intracervical inoculation of mothers with group B streptococci (GBS)
Effective-mass Klein-Gordon Equation for non-PT/non-Hermitian Generalized Morse Potential
The one-dimensional effective-mass Klein-Gordon equation for the real, and
non-\textrm{PT}-symmetric/non-Hermitian generalized Morse potential is solved
by taking a series expansion for the wave function. The energy eigenvalues, and
the corresponding eigenfunctions are obtained. They are also calculated for the
constant mass case.Comment: 14 page
Effective-Mass Dirac Equation for Woods-Saxon Potential: Scattering, Bound States and Resonances
Approximate scattering and bound state solutions of the one-dimensional
effective-mass Dirac equation with the Woods-Saxon potential are obtained in
terms of the hypergeometric-type functions. Transmission and reflection
coefficients are calculated by using behavior of the wave functions at
infinity. The same analysis is done for the constant mass case. It is also
pointed out that our results are in agreement with those obtained in
literature. Meanwhile, an analytic expression is obtained for the transmission
resonance and observed that the expressions for bound states and resonances are
equal for the energy values .Comment: 20 pages, 6 figure
New exact solution of the one dimensional Dirac Equation for the Woods-Saxon potential within the effective mass case
We study the one-dimensional Dirac equation in the framework of a position
dependent mass under the action of a Woods-Saxon external potential. We find
that constraining appropriately the mass function it is possible to obtain a
solution of the problem in terms of the hypergeometric function. The mass
function for which this turns out to be possible is continuous. In particular
we study the scattering problem and derive exact expressions for the reflection
and transmission coefficients which are compared to those of the constant mass
case. For the very same mass function the bound state problem is also solved,
providing a transcendental equation for the energy eigenvalues which is solved
numerically.Comment: Version to match the one which has been accepted for publication by
J. Phys. A: Math. Theor. Added one figure, several comments and few
references. (24 pages and 7 figures
Hybrid State Space-based Learning for Sequential Data Prediction with Joint Optimization
We investigate nonlinear prediction/regression in an online setting and
introduce a hybrid model that effectively mitigates, via a joint mechanism
through a state space formulation, the need for domain-specific feature
engineering issues of conventional nonlinear prediction models and achieves an
efficient mix of nonlinear and linear components. In particular, we use
recursive structures to extract features from raw sequential sequences and a
traditional linear time series model to deal with the intricacies of the
sequential data, e.g., seasonality, trends. The state-of-the-art ensemble or
hybrid models typically train the base models in a disjoint manner, which is
not only time consuming but also sub-optimal due to the separation of modeling
or independent training. In contrast, as the first time in the literature, we
jointly optimize an enhanced recurrent neural network (LSTM) for automatic
feature extraction from raw data and an ARMA-family time series model (SARIMAX)
for effectively addressing peculiarities associated with time series data. We
achieve this by introducing novel state space representations for the base
models, which are then combined to provide a full state space representation of
the hybrid or the ensemble. Hence, we are able to jointly optimize both models
in a single pass via particle filtering, for which we also provide the update
equations. The introduced architecture is generic so that one can use other
recurrent architectures, e.g., GRUs, traditional time series-specific models,
e.g., ETS or other optimization methods, e.g., EKF, UKF. Due to such novel
combination and joint optimization, we demonstrate significant improvements in
widely publicized real life competition datasets. We also openly share our code
for further research and replicability of our results.Comment: Submitted to the IEEE TNNLS journa
Volume CVI, Number 10, January 13, 1989
WOS: 000188054500005Two subspecies of mistletoe (Viscum album L. ssp. album and ssp. abietis) growing on lime and pine trees, respectively, were investigated for the monosaccharides and polyols by GC-MS spectrometry. Arabinose, xylose, glucose, galactose, mannose, xylitol and inositol were determined in methanol extracts following the acidic hydrolysis. Sugar contents of the leaves were expressed as percentage on dry weight. Xylose content was the same (1.5%) in each species, whereas the other saccharides varied. V. album ssp. abietis (collected from pine trees) were found containing significantly higher percentage of glucose (29.0%) and galactose (44.0%) than V. album ssp. album (collected from lime trees) (9.0% and 17.0%, respectively). In contrast, mannose, arabinose and sugar alcohol percentages were higher in ssp. album. Mannose content was 3.5% for ssp. album whereas 1.0% for ssp. abietis. 3.0% arabinose were determined in the former and 2.0% in the latter. Xylitol and inositol percentages were 8.0% and 58.0% for ssp. album and 1.5% and 21.0% for ssp. abietis, respectively. These results indicate that saccharide composition of mistletoes depends upon the subspecies of the plant and the host tree
Variations on Hammersley's interacting particle process
The longest increasing subsequence problem for permutations has been studied
extensively in the last fifty years. The interpretation of the longest
increasing subsequence as the longest 21-avoiding subsequence in the context of
permutation patterns leads to many interesting research directions. We
introduce and study the statistical properties of Hammersleytype interacting
particle processes related to these generalizations and explore the finer
structures of their distributions. We also propose three different interacting
particle systems in the plane analogous to the Hammersley process in one
dimension and obtain estimates for the asymptotic orders of the mean and
variance of the number of particles in the systems.Comment: 6 pages, 6 figures, accepted for publication in Discrete Mathematics
Letter
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