The recurrent neural networks (RNN) with richly distributed internal states and flexible non-linear transition functions, have overtaken the dynamic Bayesian networks such as the hidden Markov models (HMMs) in the task of modeling highly structured s
equential data. These data, such as from speech and handwriting, often contain complex relationships between the underlaying variational factors and the observed data. The standard RNN model has very limited randomness or variability in its structure, coming from the output conditional probability model. This paper will present different ways of using high level latent random variables in RNN to model the variability in the sequential data, and the training method of such RNN model under the VAE (Variational Autoencoder) principle. We will explore possible ways of using adversarial method to train a variational RNN model. Contrary to competing approaches, our approach has theoretical optimum in the model training and provides better model training stability. Our approach also improves the posterior approximation in the variational inference network by a separated adversarial training step. Numerical results simulated from TIMIT speech data show that reconstruction loss and evidence lower bound converge to the same level and adversarial training loss converges to 0.
We report the results of reverberation mapping three bright Seyfert galaxies, Mrk 79, NGC 3227, and Mrk 841, from a campaign conducted from December 2016 to May 2017 with the Wyoming Infrared Observatory (WIRO) 2.3-meter telescope. All three of these
targets have shown asymmetric broad H$beta$ emission lines in the past, although their emission lines were relatively symmetric during our observations. We measured Hbeta time lags for all three targets and estimated masses of their black holes -- for the first time in the case of Mrk 841. For Mrk 79 and NGC 3227, the data are of sufficient quality to resolve distinct time lags as a function of velocity and to compute two-dimensional velocity-delay maps. Mrk 79 shows smaller time lags for high-velocity gas but the distribution is not symmetric, and its complex velocity-delay map could result from the combination of both inflowing and outflowing Hbeta emitting disks that may be part of a single larger structure. NGC 3227 shows the largest time lags for blueshifted gas and the two-dimensional velocity-delay map suggests a disk with some inflow. We compare our results with previous work and find evidence for different time lags despite similar luminosities, as well as evolving broad line region structures.
Deep brain stimulation (DBS) is an effective therapy as an alternative to pharmaceutical treatments for Parkinsons disease (PD). Aside from factors such as instrumentation, treatment plans, and surgical protocols, the success of the procedure depends
heavily on the accurate placement of the electrode within the optimal therapeutic targets while avoiding vital structures that can cause surgical complications and adverse neurologic effects. While specific surgical techniques for DBS can vary, interventional guidance with medical imaging has greatly contributed to the development, outcomes, and safety of the procedure. With rapid development in novel imaging techniques, computational methods, and surgical navigation software, as well as growing insights into the disease and mechanism of action of DBS, modern image guidance is expected to further enhance the capacity and efficacy of the procedure in treating PD. This article surveys the state-of-the-art techniques in image-guided DBS surgery to treat PD, and discuss their benefits and drawbacks, as well as future directions on the topic.
In brain tumor surgery, the quality and safety of the procedure can be impacted by intra-operative tissue deformation, called brain shift. Brain shift can move the surgical targets and other vital structures such as blood vessels, thus invalidating t
he pre-surgical plan. Intra-operative ultrasound (iUS) is a convenient and cost-effective imaging tool to track brain shift and tumor resection. Accurate image registration techniques that update pre-surgical MRI based on iUS are crucial but challenging. The MICCAI Challenge 2018 for Correction of Brain shift with Intra-Operative UltraSound (CuRIOUS2018) provided a public platform to benchmark MRI-iUS registration algorithms on newly released clinical datasets. In this work, we present the data, setup, evaluation, and results of CuRIOUS 2018, which received 6 fully automated algorithms from leading academic and industrial research groups. All algorithms were first trained with the public RESECT database, and then ranked based on test dataset of 10 additional cases with identical data curation and annotation protocols as the RESECT database. The article compares the results of all participating teams and discusses the insights gained from the challenge, as well as future work.
NGC 5548 has been well spectroscopically monitored for reverberation mapping of the central kinematics by 19 campaigns. Using the maximum entropy method in this Letter, we build up a high-quality velocity-delay map of the H$beta$ emission line in the
light curves of the continuum and the line variations observed between 2015-2016. The map shows the response strength and lags of the velocity fields of the H$beta$ emitting regions. The velocity-delay structure of the map is generally symmetric, with strong red and blue wings at time lag $tau leq 15$ days, a narrower velocity distribution at $tau geq 15$ days, and a deficit of response in the core. This is suggestive of a disk geometry of the broad-line region (BLR). The relatively weaker H$beta$ response at the longer lags in the red side indicates anisotropic emission from the outer part of the BLR. We also recover the velocity-delay maps of NGC 5548 from the historical data of 13 years to investigate the long-term variability of its BLR. In general, the BLR of NGC 5548 was switching between the inflow and virialized phases in the past years. The resultant maps of seven years reveal inflow signatures and show decreasing lags, indicating that the changes in the BLR size are related to the infalling BLR gas. The other four maps show potential disk signatures which are similar to our map.
As one of the series of papers reporting on a large reverberation mapping campaign, we apply the maximum entropy method (MEM) to 9 narrow-line Seyfert 1 galaxies with super-Eddington accretion rates observed during 2012-2013 for the velocity-delay ma
ps of their Hbeta and Hgamma emission lines. The maps of 6 objects are reliably reconstructed using MEM. The maps of Hbeta and Hgamma emission lines of Mrk 335 indicate that the gas of its broad-line region (BLR) is infalling. For Mrk 142, its Hbeta and Hgamma lines show signatures of outflow. The Hbeta and Hgamma maps of Mrk 1044 demonstrate complex kinematics -- a virialized motion accompanied by an outflow signature, and the Hbeta map of IRAS F12397+3333 is consistent with a disk or a spherical shell. The Hbeta maps of Mrk 486 and MCG +06-26-012 suggest the presence of an inflow and outflow, respectively. These super-Eddington accretors show diverse geometry and kinematics. Brief discussions of their BLRs are provided for each individual object.
Let $f:{mathbb B}^n to {mathbb B}^N$ be a holomorphic map. We study subgroups $Gamma_f subseteq {rm Aut}({mathbb B}^n)$ and $T_f subseteq {rm Aut}({mathbb B}^N)$. When $f$ is proper, we show both these groups are Lie subgroups. When $Gamma_f$ contain
s the center of ${bf U}(n)$, we show that $f$ is spherically equivalent to a polynomial. When $f$ is minimal we show that there is a homomorphism $Phi:Gamma_f to T_f$ such that $f$ is equivariant with respect to $Phi$. To do so, we characterize minimality via the triviality of a third group $H_f$. We relate properties of ${rm Ker}(Phi)$ to older results on invariant proper maps between balls. When $f$ is proper but completely non-rational, we show that either both $Gamma_f$ and $T_f$ are finite or both are noncompact.
Millimeter wave (mmWave) communication has attracted increasing attention as a promising technology for 5G networks. One of the key architectural features of mmWave is the use of massive antenna arrays at both the transmitter and the receiver sides.
Therefore, by employing directional beamforming (BF), both mmWave base stations (MBSs) and mmWave users (MUEs) are capable of supporting multi-beam simultaneous transmissions. However, most researches have only considered a single beam, which means that they do not make full potential of mmWave. In this context, in order to improve the performance of short-range indoor mmWave networks with multiple reflections, we investigate the challenges and potential solutions of downlink multi-user multi-beam transmission, which can be described as a high-dimensional (i.e., beamspace) multi-user multiple-input multiple-output (MU-MIMO) technique, including multi-user BF training, simultaneous users grouping, and multi-user multibeam power allocation. Furthermore, we present the theoretical and numerical results to demonstrate that beamspace MU-MIMO compared with single beam transmission can largely improve the rate performance of mmWave systems.
We introduce the Hermitian-invariant group $Gamma_f$ of a proper rational map $f$ between the unit ball in complex Euclidean space and a generalized ball in a space of typically higher dimension. We use properties of the groups to define the crucial
new concepts of essential map and the source rank of a map. We prove that every finite subgroup of the source automorphism group is the Hermitian-invariant group of some rational proper map between balls. We prove that $Gamma_f$ is non-compact if and only if $f$ is a totally geodesic embedding. We show that $Gamma_f$ contains an $n$-torus if and only if $f$ is equivalent to a monomial map. We show that $Gamma_f$ contains a maximal compact subgroup if and only if $f$ is equivalent to the juxtaposition of tensor powers. We also establish a monotonicity result; the group, after intersecting with the unitary group, does not decrease when a tensor product operation is applied to a polynomial proper map. We give a necessary condition for $Gamma_f$ (when the target is a generalized ball) to contain automorphisms that move the origin.
We study proper rational maps from the unit disk to balls in higher dimensions. After gathering some known results, we study the moduli space of unitary equivalence classes of polynomial proper maps from the disk to a ball, and we establish a normal
form for these equivalence classes. We also prove that all rational proper maps from the disk to a ball are homotopic in target dimension at least $2$.
