Results of bottom trawl surveys carried out in Vietnamese waters (20-200 m) in 1996-1997

Bottom trawl surveys were conducted in the southwest monsoon season in 1996 (survey 1) and in the northeast monsoon season in 1996-97 (survey 2) throughout Vietnamese waters. The surveys mainly covered the depth zone 50-200 m but in the northeast monsoon season the depth zone 20-50 m was included in the northern and southern areas. Overall, 273 trawl hauls were conducted. The total biomass for Vietnamese waters in the depth zone 20-200 m was estimated at 700 000 t . Biomass estimates are given for the most abundant species. A relatively higher mean catch-per-unit effort (CPUE) was obtained from survey 2 than from survey 1 and in partcular at depth ranges 50-100 and 100-200 m in south Vietnam. Overall, the dominant families were Monacanthidae (34%), Carangidae (15%), Trichiuridae (9%) and Synodontidae (6%)

Optimization of scale-free network for random failures

It has been found that the networks with scale-free distribution are very resilient to random failures. The purpose of this work is to determine the network design guideline which maximize the network robustness to random failures with the average number of links per node of the network is constant. The optimal value of the distribution exponent and the minimum connectivity to different network size are given in this paper. Finally, the optimization strategy how to improve the evolving network robustness is given.Comment: 6 pages, 1 figur

Optimization of robustness of scale-free network to random and targeted attacks

The scale-fee networks, having connectivity distribution $P(k)\sim k^{-\alpha}$ (where $k$ is the site connectivity), is very resilient to random failures but fragile to intentional attack. The purpose of this paper is to find the network design guideline which can make the robustness of the network to both random failures and intentional attack maximum while keeping the average connectivity per node constant. We find that when $=3$ the robustness of the scale-free networks reach its maximum value if the minimal connectivity $m=1$, but when is larger than four, the networks will become more robust to random failures and targeted attacks as the minimal connectivity $m$ gets larger

Higgs-gauge boson interactions in the economical 3-3-1 model

Interactions among the standard model gauge bosons and scalar fields in the framework of SU(3)_C X SU(3)_L X U(1)_X gauge model with minimal (economical) Higgs content are presented. From these couplings, all scalar fields including the neutral scalar $h$ and the Goldstone bosons can be identified and their couplings with the usual gauge bosons such as the photon, the charged $W^\pm$ and the neutral $Z$, without any additional condition, are recovered. In the effective approximation, full content of scalar sector can be recognized. The CP-odd part of Goldstone associated with the neutral non-Hermitian bilepton gauge boson $G_{X^0}$ is decouple, while its CP-even counterpart has the mixing by the same way in the gauge boson sector. Masses of the new neutral Higgs boson $H^0_1$ and the neutral non-Hermitian bilepton $X^0$ are dependent on a coefficient of Higgs self-coupling ($\lambda_1$). Similarly, masses of the singly-charged Higgs boson $H_2^\pm$ and of the charged bilepton $Y^\pm$ are proportional through a coefficient of Higgs self-interaction ($\lambda_4$). The hadronic cross section for production of this Higgs boson at the LHC in the effective vector boson approximation is calculated. Numerical evaluation shows that the cross section can exceed 260 $fb$.Comment: 22 pages, 1 figure, submitted to Phys. Rev.

Calculation of the properties of the rotational bands of 155,157^{155,157}Gd

We reexamine the long-standing problem of the microscopic derivation of a particle-core coupling model. We base our research on the Klein-Kerman approach, as amended by D\"onau and Frauendorf. We describe the formalism to calculate energy spectra and transition strengths in some detail. We apply our formalism to the rotational nuclei $^{155,157}$Gd, where recent experimental data requires an explanation. We find no clear evidence of a need for Coriolis attenuation.Comment: 27 pages, 13 uuencoded postscript figures. Uses epsf.st

Quantum theory of large amplitude collective motion and the Born-Oppenheimer method

We study the quantum foundations of a theory of large amplitude collective motion for a Hamiltonian expressed in terms of canonical variables. In previous work the separation into slow and fast (collective and non-collective) variables was carried out without the explicit intervention of the Born Oppenheimer approach. The addition of the Born Oppenheimer assumption not only provides support for the results found previously in leading approximation, but also facilitates an extension of the theory to include an approximate description of the fast variables and their interaction with the slow ones. Among other corrections, one encounters the Berry vector and scalar potential. The formalism is illustrated with the aid of some simple examples, where the potentials in question are actually evaluated and where the accuracy of the Born Oppenheimer approximation is tested. Variational formulations of both Hamiltonian and Lagrangian type are described for the equations of motion for the slow variables.Comment: 29 pages, 1 postscript figure, preprint no UPR-0085NT. Latex + epsf styl

Angle-resonant stimulated polariton amplifier

We experimentally demonstrate resonant coupling between photons and excitons in microcavities which can efficiently generate enormous single-pass optical gains approaching 100. This new parametric phenomenon appears as a sharp angular resonance of the incoming pump beam, at which the moving excitonic polaritons undergo very large changes in momentum. Ultrafast stimulated scattering is clearly identified from the exponential dependence on pump intensity. This device utilizes boson amplification induced by stimulated energy relaxation

Enhancement of Rabi Splitting in a Microcavity with an Embedded Superlattice

We have observed a large coupling between the excitonic and photonic modes of an AlAs/AlGaAs microcavity filled with an 84-({\rm {\AA}})/20({\rm {\AA}}) GaAs/AlGaAs superlattice. Reflectivity measurements on the coupled cavity-superlattice system in the presence of a moderate electric field yielded a Rabi splitting of 9.5 meV at T = 238 K. This splitting is almost 50% larger than that found in comparable microcavities with quantum wells placed at the antinodes only. We explain the enhancement by the larger density of optical absorbers in the superlattice, combined with the quasi-two-dimensional binding energy of field-localized excitons.Comment: 5 pages, 4 figures, submitted to PR

Relaxation bottleneck and its suppression in semiconductor microcavities

A polariton relaxation bottleneck is observed in angle-resolved measurements of photoluminescence emission from a semiconductor microcavity. For low power laser excitation, low k polariton states are found to have a very small population relative to those at high k. The bottleneck is found to be strongly suppressed at higher powers in the regime of superlinear emission of the lower polariton states. Evidence for the important role of carrier-carrier scattering in suppression of the bottleneck is presented

Vessel-CAPTCHA: An efficient learning framework for vessel annotation and segmentation

Deep learning techniques for 3D brain vessel image segmentation have not been as successful as in the segmentation of other organs and tissues. This can be explained by two factors. First, deep learning techniques tend to show poor performances at the segmentation of relatively small objects compared to the size of the full image. Second, due to the complexity of vascular trees and the small size of vessels, it is challenging to obtain the amount of annotated training data typically needed by deep learning methods. To address these problems, we propose a novel annotation-efficient deep learning vessel segmentation framework. The framework avoids pixel-wise annotations, only requiring weak patch-level labels to discriminate between vessel and non-vessel 2D patches in the training set, in a setup similar to the CAPTCHAs used to differentiate humans from bots in web applications. The user-provided weak annotations are used for two tasks: (1) to synthesize pixel-wise pseudo-labels for vessels and background in each patch, which are used to train a segmentation network, and (2) to train a classifier network. The classifier network allows to generate additional weak patch labels, further reducing the annotation burden, and it acts as a second opinion for poor quality images. We use this framework for the segmentation of the cerebrovascular tree in Time-of-Flight angiography (TOF) and Susceptibility-Weighted Images (SWI). The results show that the framework achieves state-of-the-art accuracy, while reducing the annotation time by 77% w.r.t. learning-based segmentation methods using pixel-wise labels for training