DanQ: a hybrid convolutional and recurrent deep neural network for quantifying the function of DNA sequences.

Modeling the properties and functions of DNA sequences is an important, but challenging task in the broad field of genomics. This task is particularly difficult for non-coding DNA, the vast majority of which is still poorly understood in terms of function. A powerful predictive model for the function of non-coding DNA can have enormous benefit for both basic science and translational research because over 98% of the human genome is non-coding and 93% of disease-associated variants lie in these regions. To address this need, we propose DanQ, a novel hybrid convolutional and bi-directional long short-term memory recurrent neural network framework for predicting non-coding function de novo from sequence. In the DanQ model, the convolution layer captures regulatory motifs, while the recurrent layer captures long-term dependencies between the motifs in order to learn a regulatory 'grammar' to improve predictions. DanQ improves considerably upon other models across several metrics. For some regulatory markers, DanQ can achieve over a 50% relative improvement in the area under the precision-recall curve metric compared to related models. We have made the source code available at the github repository http://github.com/uci-cbcl/DanQ

Estimation of De Facto Flexibility Parameter and Basket Weights in Evolving Exchange Rate Regimes

A new technique for estimating countries' de facto exchange rate regimes synthesizes two approaches. One approach estimates the implicit de facto basket weights in an OLS regression of the local currency value rate against major currency values. Here the hypothesis is a basket peg with little flexibility. The second estimates the de facto degree of exchange rate flexibility by observing how exchange market pressure is allowed to show up. Here the hypothesis is an anchor to the dollar or some other single major currency, but with a possibly substantial degree of exchange rate flexibility around that anchor. It is important to have available a technique that can cover both dimensions: inferring anchor weights and the flexibility parameter. We test the synthesis technique on a variety of fixers, floaters, and basket peggers. We find that real world data demand a statistical technique that allows parameters and regimes to shift frequently. Accordingly we here take the next step in estimation of de facto exchange rate regimes: endogenous estimation of parameter breakpoints, following Bai and Perron.

Two-photon Rabi model: Analytic solutions and spectral collapse

The two-photon quantum Rabi model with quadratic coupling is studied using extended squeezed states and we derive $G$-functions for Bargmann index $q=1/4$ and $3/4$. The simple singularity structure of the $G$-function allows to draw conclusions about the distribution of eigenvalues along the real axis. The previously found picture of the spectral collapse at critical coupling $g_{\mathrm{c}}$ has to be modified regarding the low lying states, especially the ground state: We obtain a finite gap between ground state and the continuum of excited states at the collapse point. For large qubit splitting, also other low lying states may be separated from the continuum at $g_{\mathrm{c}}$. We have carried out a perturbative analysis allowing for explicit and simple formulae of the eigenstates. Interestingly, a vanishing of the gap between ground state and excited continuum at $g_{\mathrm{c}}$ is obtained in each finite order of approximation. This demonstrates cleary the non-pertubative nature of the excitation gap. We corroborate these findings with a variational calculation for the ground state.Comment: 13 pages, 4 figure

A Generalized Fact and Model of Long-Run Economic Growth: Kaldor Fact as a Special Case

This paper provides new evidence on the long-run relationship between economic growth and labor's share in national income, based on a comprehensive panel data set for 123 countries from 1950 to 2004. Xie's primary finding is that labor's share follows a cubic relationship with real GDP per capita over the long process of development. At the beginning of the modern economic growth process, the share of labor in national income first decreases until an initial threshold is reached. After that, labor's share keeps increasing until the country's GDP per capita reaches a second threshold before falling again. Xie argues that these dynamics apply not only to the less developed countries in the postwar years, but also to the advanced countries like the United States and the United Kingdom during their early economic take-offs, starting in the late 18th and 19th century, respectively. Finally, he proposes a two-sector constant elasticity of substitution (CES)-type growth model and simulate the model to replicate and explain the possible mechanism behind such a nonlinear pattern of movements in labor's share.Constant elasticity of substitution, Kaldor fact, Kuznets curve, Labor's share, Structural change

Anelastic sensitivity kernels with parsimonious storage for adjoint tomography and full waveform inversion

We introduce a technique to compute exact anelastic sensitivity kernels in the time domain using parsimonious disk storage. The method is based on a reordering of the time loop of time-domain forward/adjoint wave propagation solvers combined with the use of a memory buffer. It avoids instabilities that occur when time-reversing dissipative wave propagation simulations. The total number of required time steps is unchanged compared to usual acoustic or elastic approaches. The cost is reduced by a factor of 4/3 compared to the case in which anelasticity is partially accounted for by accommodating the effects of physical dispersion. We validate our technique by performing a test in which we compare the $K_\alpha$ sensitivity kernel to the exact kernel obtained by saving the entire forward calculation. This benchmark confirms that our approach is also exact. We illustrate the importance of including full attenuation in the calculation of sensitivity kernels by showing significant differences with physical-dispersion-only kernels