On Neural Architectures for Deep Learning-based Source Separation of Co-Channel OFDM Signals

We study the single-channel source separation problem involving orthogonal frequency-division multiplexing (OFDM) signals, which are ubiquitous in many modern-day digital communication systems. Related efforts have been pursued in monaural source separation, where state-of-the-art neural architectures have been adopted to train an end-to-end separator for audio signals (as 1-dimensional time series). In this work, through a prototype problem based on the OFDM source model, we assess -- and question -- the efficacy of using audio-oriented neural architectures in separating signals based on features pertinent to communication waveforms. Perhaps surprisingly, we demonstrate that in some configurations, where perfect separation is theoretically attainable, these audio-oriented neural architectures perform poorly in separating co-channel OFDM waveforms. Yet, we propose critical domain-informed modifications to the network parameterization, based on insights from OFDM structures, that can confer about 30 dB improvement in performance

Diagnosing space telescope misalignment and jitter using stellar images

Accurate knowledge of the telescope's point spread function (PSF) is essential for the weak gravitational lensing measurements that hold great promise for cosmological constraints. For space telescopes, the PSF may vary with time due to thermal drifts in the telescope structure, and/or due to jitter in the spacecraft pointing (ground-based telescopes have additional sources of variation). We describe and simulate a procedure for using the images of the stars in each exposure to determine the misalignment and jitter parameters, and reconstruct the PSF at any point in that exposure's field of view. The simulation uses the design of the SNAP (http://snap.lbl.gov) telescope. Stellar-image data in a typical exposure determines secondary-mirror positions as precisely as $20 {\rm nm}$. The PSF ellipticities and size, which are the quantities of interest for weak lensing are determined to $4.0 \times 10^{-4}$ and $2.2 \times 10^{-4}$ accuracies respectively in each exposure, sufficient to meet weak-lensing requirements. We show that, for the case of a space telescope, the PSF estimation errors scale inversely with the square root of the total number of photons collected from all the usable stars in the exposure.Comment: 20 pages, 6 figs, submitted to PAS

Exploiting Temporal Structures of Cyclostationary Signals for Data-Driven Single-Channel Source Separation

We study the problem of single-channel source separation (SCSS), and focus on cyclostationary signals, which are particularly suitable in a variety of application domains. Unlike classical SCSS approaches, we consider a setting where only examples of the sources are available rather than their models, inspiring a data-driven approach. For source models with underlying cyclostationary Gaussian constituents, we establish a lower bound on the attainable mean squared error (MSE) for any separation method, model-based or data-driven. Our analysis further reveals the operation for optimal separation and the associated implementation challenges. As a computationally attractive alternative, we propose a deep learning approach using a U-Net architecture, which is competitive with the minimum MSE estimator. We demonstrate in simulation that, with suitable domain-informed architectural choices, our U-Net method can approach the optimal performance with substantially reduced computational burden

Data-Driven Blind Synchronization and Interference Rejection for Digital Communication Signals

We study the potential of data-driven deep learning methods for separation of two communication signals from an observation of their mixture. In particular, we assume knowledge on the generation process of one of the signals, dubbed signal of interest (SOI), and no knowledge on the generation process of the second signal, referred to as interference. This form of the single-channel source separation problem is also referred to as interference rejection. We show that capturing high-resolution temporal structures (nonstationarities), which enables accurate synchronization to both the SOI and the interference, leads to substantial performance gains. With this key insight, we propose a domain-informed neural network (NN) design that is able to improve upon both "off-the-shelf" NNs and classical detection and interference rejection methods, as demonstrated in our simulations. Our findings highlight the key role communication-specific domain knowledge plays in the development of data-driven approaches that hold the promise of unprecedented gains.Comment: 9 pages, 6 figures, accepted at IEEE GLOBECOM 2022 (this version contains extended proofs

Multiparametric magnetic resonance imaging in mucosal primary head and neck cancer: A prospective imaging biomarker study

Background: Radical radiotherapy, with or without concomitant chemotherapy forms the mainstay of organ preservation approaches in mucosal primary head and neck cancer. Despite technical advances in cancer imaging and radiotherapy administration, a significant proportion of patients fail to achieve a complete response to treatment. For those patients who do achieve a complete response, acute and late toxicities remain a cause of morbidity. A critical need therefore exists for imaging biomarkers which are capable of informing patient selection for both treatment intensification and de-escalation strategies. Methods/design: A prospective imaging study has been initiated, aiming to recruit patients undergoing radical radiotherapy (RT) or chemoradiotherapy (CRT) for mucosal primary head and neck cancer (MPHNC). Eligible patients are imaged using FDG-PET/CT before treatment, at the end of week 3 of treatment and 12 weeks after treatment completion according to local imaging policy. Functional MRI using diffusion weighted (DWI), blood oxygen level-dependent (BOLD ) and dynamic contrast enhanced (DCE) sequences is carried out prior to, during and following treatment. Information regarding treatment outcomes will be collected, as well as physician-scored and patient-reported toxicity. Discussion: The primary objective is to determine the correlation of functional MRI sequences with tumour response as determined by FDG-PET/CT and clinical findings at 12 weeks post-treatment and with local control at 12 months post-treatment. Secondary objectives include prospective correlation of functional MRI and PET imaging with disease-free survival and overall survival, defining the optimal time points for functional MRI assessment of treatment response, and determining the sensitivity and specificity of functional MRI sequences for assessment of potential residual disease following treatment. If the study is able to successfully characterise tumours based on their functional MRI scan characteristics, this would pave the way for further studies refining treatment approaches based on prognostic and predictive imaging data

Versatile Virus-Like Particle Carrier for Epitope Based Vaccines

BACKGROUND: Recombinant proteins and in particular single domains or peptides are often poorly immunogenic unless conjugated to a carrier protein. Virus-like-particles are a very efficient means to confer high immunogenicity to antigens. We report here the development of virus-like-particles (VLPs) derived from the RNA bacteriophage AP205 for epitope-based vaccines. METHODOLOGY/PRINCIPAL FINDINGS: Peptides of angiotensin II, S.typhi outer membrane protein (D2), CXCR4 receptor, HIV1 Nef, gonadotropin releasing hormone (GnRH), Influenza A M2-protein were fused to either N- or C-terminus of AP205 coat protein. The A205-peptide fusions assembled into VLPs, and peptides displayed on the VLP were highly immunogenic in mice. GnRH fused to the C-terminus of AP205 induced a strong antibody response that inhibited GnRH function in vivo. Exposure of the M2-protein peptide at the N-terminus of AP205 resulted in a strong M2-specific antibody response upon immunization, protecting 100% of mice from a lethal influenza infection. CONCLUSIONS/SIGNIFICANCE: AP205 VLPs are therefore a very efficient and new vaccine system, suitable for complex and long epitopes, of up to at least 55 amino acid residues in length. AP205 VLPs confer a high immunogenicity to displayed epitopes, as shown by inhibition of endogenous GnRH and protective immunity against influenza infection

Photoemission "experiments" on holographic superconductors

We study the effects of a superconducting condensate on holographic Fermi surfaces. With a suitable coupling between the fermion and the condensate, there are stable quasiparticles with a gap. We find some similarities with the phenomenology of the cuprates: in systems whose normal state is a non-Fermi liquid with no stable quasiparticles, a stable quasiparticle peak appears in the condensed phase.Comment: 14 pages, 13 figures; v2: typos corrected and some clarification adde

Re-examining the consumption-wealth relationship : the role of model uncertainty

This paper discusses the consumption-wealth relationship. Following the recent influential workof Lettau and Ludvigson [e.g. Lettau and Ludvigson (2001), (2004)], we use data on consumption, assets andlabor income and a vector error correction framework. Key …ndings of their work are that consumption doesrespond to permanent changes in wealth in the expected manner, but that most changes in wealth are transitoryand have no e¤ect on consumption. We investigate the robustness of these results to model uncertainty andargue for the use of Bayesian model averaging. We …nd that there is model uncertainty with regards to thenumber of cointegrating vectors, the form of deterministic components, lag length and whether the cointegratingresiduals a¤ect consumption and income directly. Whether this uncertainty has important empirical implicationsdepends on the researcher's attitude towards the economic theory used by Lettau and Ludvigson. If we workwith their model, our findings are very similar to theirs. However, if we work with a broader set of models andlet the data speak, we obtain somewhat di¤erent results. In the latter case, we …nd that the exact magnitudeof the role of permanent shocks is hard to estimate precisely. Thus, although some support exists for the viewthat their role is small, we cannot rule out the possibility that they have a substantive role to play

Morphology and density of post-CME current sheets

Eruption of a coronal mass ejection (CME) drags and "opens" the coronal magnetic field, presumably leading to the formation of a large-scale current sheet and the field relaxation by magnetic reconnection. We analyze physical characteristics of ray-like coronal features formed in the aftermath of CMEs, to check if the interpretation of this phenomenon in terms of reconnecting current sheet is consistent with the observations. The study is focused on measurements of the ray width, density excess, and coronal velocity field as a function of the radial distance. The morphology of rays indicates that they occur as a consequence of Petschek-like reconnection in the large scale current sheet formed in the wake of CME. The hypothesis is supported by the flow pattern, often showing outflows along the ray, and sometimes also inflows into the ray. The inferred inflow velocities range from 3 to 30 km s$^{-1}$, consistent with the narrow opening-angle of rays, adding up to a few degrees. The density of rays is an order of magnitude larger than in the ambient corona. The density-excess measurements are compared with the results of the analytical model in which the Petschek-like reconnection geometry is applied to the vertical current sheet, taking into account the decrease of the external coronal density and magnetic field with height. The model results are consistent with the observations, revealing that the main cause of the density excess in rays is a transport of the dense plasma from lower to larger heights by the reconnection outflow

Bacterial infection elicits heat shock protein 72 release from pleural mesothelial cells

Heat shock protein 70 (HSP70) has been implicated in infection-related processes and has been found in body fluids during infection. This study aimed to determine whether pleural mesothelial cells release HSP70 in response to bacterial infection in vitro and in mouse models of serosal infection. In addition, the in vitro cytokine effects of the HSP70 isoform, Hsp72, on mesothelial cells were examined. Further, Hsp72 was measured in human pleural effusions and levels compared between non-infectious and infectious patients to determine the diagnostic accuracy of pleural fluid Hsp72 compared to traditional pleural fluid parameters. We showed that mesothelial release of Hsp72 was significantly raised when cells were treated with live and heat-killed Streptococcus pneumoniae. In mice, intraperitoneal injection of S. pneumoniae stimulated a 2-fold increase in Hsp72 levels in peritoneal lavage (p,0.01). Extracellular Hsp72 did not induce or inhibit mediator release from cultured mesothelial cells. Hsp72 levels were significantly higher in effusions of infectious origin compared to non-infectious effusions (p,0.05). The data establish that pleural mesothelial cells can release Hsp72 in response to bacterial infection and levels are raised in infectious pleural effusions. The biological role of HSP70 in pleural infection warrants exploration