Tracking by Animation: Unsupervised Learning of Multi-Object Attentive Trackers

Online Multi-Object Tracking (MOT) from videos is a challenging computer vision task which has been extensively studied for decades. Most of the existing MOT algorithms are based on the Tracking-by-Detection (TBD) paradigm combined with popular machine learning approaches which largely reduce the human effort to tune algorithm parameters. However, the commonly used supervised learning approaches require the labeled data (e.g., bounding boxes), which is expensive for videos. Also, the TBD framework is usually suboptimal since it is not end-to-end, i.e., it considers the task as detection and tracking, but not jointly. To achieve both label-free and end-to-end learning of MOT, we propose a Tracking-by-Animation framework, where a differentiable neural model first tracks objects from input frames and then animates these objects into reconstructed frames. Learning is then driven by the reconstruction error through backpropagation. We further propose a Reprioritized Attentive Tracking to improve the robustness of data association. Experiments conducted on both synthetic and real video datasets show the potential of the proposed model. Our project page is publicly available at: https://github.com/zhen-he/tracking-by-animationComment: CVPR 201

Phase structure of lattice QCD with two flavors of Wilson quarks at finite temperature and chemical potential

We present results for phase structure of lattice QCD with two degenerate flavors ($N_f=2$) of Wilson quarks at finite temperature $T$ and small baryon chemical potential $\mu_B$. Using the imaginary chemical potential for which the fermion determinant is positive, we perform simulations at points where the ratios of pseudo-scalar meson mass to the vector meson mass $m_\pi/m_\rho$ are between $0.943(3)$ and $0.899(4)$ as well as in the quenched limit. By analytic continuation to real quark chemical potential $\mu$, we obtain the transition temperature as a function of small $\mu_B$. We attempt to determine the nature of transition at imaginary chemical potential by histogram, MC history, and finite size scaling. In the infinite heavy quark limit, the transition is of first order. At intermediate values of quark mass $m_q$ corresponding to the ratio of $m_\pi/m_\rho$ in the range from $0.943(3)$ to $0.899(4)$ at $a\mu_I=0.24$, the MC simulations show absence of phase transition.Comment: 10 pages, 17 figures;16 figures;9 pages,10 figures;10 pages,11 figure

Wider and Deeper, Cheaper and Faster: Tensorized LSTMs for Sequence Learning

Long Short-Term Memory (LSTM) is a popular approach to boosting the ability of Recurrent Neural Networks to store longer term temporal information. The capacity of an LSTM network can be increased by widening and adding layers. However, usually the former introduces additional parameters, while the latter increases the runtime. As an alternative we propose the Tensorized LSTM in which the hidden states are represented by tensors and updated via a cross-layer convolution. By increasing the tensor size, the network can be widened efficiently without additional parameters since the parameters are shared across different locations in the tensor; by delaying the output, the network can be deepened implicitly with little additional runtime since deep computations for each timestep are merged into temporal computations of the sequence. Experiments conducted on five challenging sequence learning tasks show the potential of the proposed model

Series Expansions for Excited States of Quantum Lattice Models

We show that by means of connected-graph expansions one can effectively generate exact high-order series expansions which are informative of low-lying excited states for quantum many-body systems defined on a lattice. In particular, the Fourier series coefficients of elementary excitation spectra are directly obtained. The numerical calculations involved are straightforward extensions of those which have already been used to calculate series expansions for ground-state correlations and $T=0$ susceptibilities in a wide variety of models. As a test, we have reproduced the known elementary excitation spectrum of the transverse-field Ising chain in its disordered phase.Comment: 9 pages, no figures, Revtex 3.0 The revised version corrects the incorrect (and unnecessary) statement in the original that H and H^eff are related by a unitary transformation; in fact they are related by via a similarity transformation. This has no implications for the calculations of spectra, but is important for matrix element

Chronic Kidney Disease in Cats and the Risk of Total Hypercalcemia

BACKGROUND: Chronic kidney disease (CKD) is a common comorbidity in cats with hypercalcemia, but whether CKD is a risk factor for hypercalcemia is unclear. Hypercalcemia often is diagnosed based on total calcium concentration (tCa), which tends to underestimate the ionized calcium concentration (iCa) in cats. OBJECTIVES: Assessment of the performance of tCa for the diagnosis of ionized hypercalcemia, and exploration of factors influencing the relationship between iCa and tCa. Determination of risk factors for incident total hypercalcemia (ie, the development of hypercalcemia based on tCa during follow‐up). ANIMALS: Records of a cross‐section (n = 477) and observational cohort (n = 367) of client‐owned cats with and without azotemic CKD from first opinion practice. METHODS: Retrospective cross‐sectional and retrospective cohort study. The diagnostic accuracy of tCa as an index test for ionized hypercalcemia was evaluated, and risk factors for underestimation were explored by binary logistic and linear regression in a cross‐section of cats with and without azotemic CKD. Chronic kidney disease and clinicopathological variables were assessed as predictors of incident total hypercalcemia by both time‐invariant and time‐dependent Cox regression in a cohort of cats. RESULTS: Specificity of tCa for identification of ionized hypercalcemia was high (100%), but sensitivity was low. Underestimation was associated with lower venous bicarbonate concentrations. Cats with CKD had increased risk for incident total hypercalcemia (hazard ratio, 4.29; 95% confidence interval, 1.96–9.37; P < .001). Higher tCa predicted incident total hypercalcemia in both azotemic and nonazotemic cats (P < .001). CONCLUSIONS AND CLINICAL IMPORTANCE: Chronic kidney disease is a risk factor for incident total hypercalcemia, and most cats with increased tCa had concurrent ionized hypercalcemia. Higher baseline tCa predicts incident total hypercalcemia. Prospective studies assessing changes in iCa are warranted

Longitudinal diffusion tensor imaging in dementia with Lewy bodies and Alzheimer's disease.

OBJECTIVE: Changes in the white matter of dementia with Lewy bodies (DLB) and Alzheimer's disease (AD) have been reported using diffusion weighted MRI, though few longitudinal studies have been done. METHODS: We performed diffusion weighted MRI twice, a year apart on 23 AD, 14 DLB, and 32 healthy control subjects. Mean diffusivity (MD) and fractional anisotropy (FA) were calculated. RESULTS: In AD, there were widespread regions where the longitudinal MD increase was greater than in controls, and small areas in the parietal and temporal lobes where it was greater in AD than DLB. In AD, decrease in brain volume correlated with increased MD. There were no significant differences in progression between DLB and controls. CONCLUSIONS: In AD the white matter continues to degenerate during the disease process, whereas in DLB, changes in the white matter structure are a relatively early feature. Different mechanisms are likely to underpin changes in diffusivity.The study was supported by the NIHR Biomedical Research Unit in Dementia and the Biomedical Research Centre awarded to Cambridge University Hospitals NHS Foundation Trust and the University of Cambridge, and the NIHR Biomedical Research Unit in Dementia and the Biomedical Research Centre awarded to Newcastle upon Tyne Hospitals NHS Foundation Trust and Newcastle University. Elijah Mak was in receipt of a Gates Cambridge PhD studentship.This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.parkreldis.2016.01.00

The DSF family of quorum sensing signals: diversity, biosynthesis, and turnover

The diffusible signaling factor (DSF)-based quorum sensing (QS) system has emerged as a widely conserved cell–cell communication mechanism in Gram-negative bacteria. Typically, signals from the DSF family are cis-2-unsaturated fatty acids which regulate diverse biological functions. Recently, substantial progress has been made on the characterization of new members of this family of signals. There have also been new developments in the understanding of the biosynthesis of these molecules where dual enzymatic activities of the DSF synthase and the use of various substrates have been described. The recent discovery of a naturally occurring DSF turnover mechanism and its regulation provides a new dimension in our understanding of how DSF-dependent microorganisms modulate virulence gene expression in response to changes in the surrounding environment

Series Expansions for the Massive Schwinger Model in Hamiltonian lattice theory

It is shown that detailed and accurate information about the mass spectrum of the massive Schwinger model can be obtained using the technique of strong-coupling series expansions. Extended strong-coupling series for the energy eigenvalues are calculated, and extrapolated to the continuum limit by means of integrated differential approximants, which are matched onto a weak-coupling expansion. The numerical estimates are compared with exact results, and with finite-lattice results calculated for an equivalent lattice spin model with long-range interactions. Both the heavy fermion and the light fermion limits of the model are explored in some detail.Comment: RevTeX, 10 figures, add one more referenc