8,225 research outputs found
General expressions for extra-dimensional tree amplitudes and all-plus 1-loop integrands in Q-cut representaion
In this paper, we give the general expressions for a special series of tree
amplitudes of the Yang-Mills theory. This series of amplitudes have two
adjacent massless spin-1 particles with extra-dimensional momenta and any
number of positive helicity gluons. With special helicity choices, we use the
spinor helicity formalism to express these n-point amplitudes in compact forms,
and find a clever way to use the BCFW recursion relations to prove the results.
Then these amplitudes are used to form the complete 1-loop all-plus integrand
with any number of gluons, expressed in the Q-cut representation.Comment: Published version with 20 pages, 8 figure, and 1 new referenc
Child Health and the Income Gradient: Evidence from China
Though the positive income gradient of child health is well documented in developed countries, evidence from developing countries is rare. Few studies attempt to identify a causal link between family income and child health. Utilizing unique longitudinal data from the China Health and Nutrition Survey, we have found a positive, age-enhancing income gradient of child health, measured by height-for-age z scores. The gradient is robust to alternative specifications and a comprehensive set of controls. Using the fact that the rural tax reform implemented since 2000 created an exogenous variation in family income across regions and over time, we explore a causal explanation for the income gradient, and find that it has a very strong independent causal effect on child health.child health, income gradient, rural tax reform
Particle-number conserving analysis for the 2-quasiparticle and high- multi-quasiparticle states in doubly-odd Lu
Two-quasiparticle bands and low-lying excited high- four-, six-, and
eight-quasiparticle bands in the doubly-odd Lu are analyzed by
using the cranked shell model (CSM) with the pairing correlations treated by a
particle-number conserving (PNC) method, in which the blocking effects are
taken into account exactly. The proton and neutron Nilsson level schemes for
Lu are taken from the adjacent odd- Lu and Hf isotopes, which
are adopted to reproduce the experimental bandhead energies of the
one-quasiproton and one-quasineutron bands of these odd- Lu and Hf nuclei,
respectively. Once the quasiparticle configurations are determined, the
experimental bandhead energies and the moments of inertia of these two- and
multi-quasiparticle bands are well reproduced by PNC-CSM calculations. The
Coriolis mixing of the low- () two-quasiparticle band
of the Gallagher-Moszkowski doublet with one nucleon in the
orbital is analyzed.Comment: 8 pages, 5 figures, 2 tables, to be published at Chinese Physics
Revisiting the problem of audio-based hit song prediction using convolutional neural networks
Being able to predict whether a song can be a hit has impor- tant
applications in the music industry. Although it is true that the popularity of
a song can be greatly affected by exter- nal factors such as social and
commercial influences, to which degree audio features computed from musical
signals (whom we regard as internal factors) can predict song popularity is an
interesting research question on its own. Motivated by the recent success of
deep learning techniques, we attempt to ex- tend previous work on hit song
prediction by jointly learning the audio features and prediction models using
deep learning. Specifically, we experiment with a convolutional neural net-
work model that takes the primitive mel-spectrogram as the input for feature
learning, a more advanced JYnet model that uses an external song dataset for
supervised pre-training and auto-tagging, and the combination of these two
models. We also consider the inception model to characterize audio infor-
mation in different scales. Our experiments suggest that deep structures are
indeed more accurate than shallow structures in predicting the popularity of
either Chinese or Western Pop songs in Taiwan. We also use the tags predicted
by JYnet to gain insights into the result of different models.Comment: To appear in the proceedings of 2017 IEEE International Conference on
Acoustics, Speech and Signal Processing (ICASSP
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