Distributed Recovery of Jointly Sparse Signals Under Communication Constraints

The problem of the distributed recovery of jointly sparse signals has attracted much attention recently. Let us assume that the nodes of a network observe different sparse signals with common support; starting from linear, compressed measurements, and exploiting network communication, each node aims at reconstructing the support and the non-zero values of its observed signal. In the literature, distributed greedy algorithms have been proposed to tackle this problem, among which the most reliable ones require a large amount of transmitted data, which barely adapts to realistic network communication constraints. In this work, we address the problem through a reweighted l1 soft thresholding technique, in which the threshold is iteratively tuned based on the current estimate of the support. The proposed method adapts to constrained networks, as it requires only local communication among neighbors, and the transmitted messages are indices from a finite set. We analytically prove the convergence of the proposed algorithm and we show that it outperforms the state-of-the-art greedy methods in terms of balance between recovery accuracy and communication load

Distributed ADMM for In-Network Reconstruction of Sparse Signals With Innovations

In this paper, we tackle the in-network recovery of sparse signals with innovations. We assume that the nodes of the network measure a signal composed by a common component and an innovation, both sparse and unknown, according to the joint sparsity model 1 (JSM-1). Acquisition is performed as in compressed sensing, hence the number of measurements is reduced. Our goal is to show that distributed algorithms based on the alternating direction method of multipliers (ADMM) can be efficient in this framework to recover both the common and the individual components. Specifically, we define a suitable functional and we show that ADMM can be implemented to minimize it in a distributed way, leveraging local communication between nodes. Moreover, we develop a second version of the algorithm, which requires only binary messaging, significantly reducing the transmission load

Distributed algorithms for in-network recovery of jointly sparse signals

We propose a new class of distributed algorithms for the in-network reconstruction of jointly sparse signals. We consider a network in which each node has to reconstruct a different signal, but all the signals share the same support. The problem is formulated as follows: each node iteratively solves a lasso, in which the weight of the l1-norm is tuned based on information on the support gathered from the other nodes. This promotes consensus on the support, and allows the single nodes to recover their signals, even when the number of measurements is not sufficient for individual reconstruction. Numerical simulations prove that our method outperforms the state-of-the-art greedy algorithms

Non-Einstein geometries in Chiral Gravity

We analyze the asymptotic solutions of Chiral Gravity (Topologically Massive Gravity at \mu l = 1 with Brown-Henneaux boundary conditions) focusing on non-Einstein metrics. A class of such solutions admits curvature singularities in the interior which are reflected as singularities or infinite bulk energy of the corresponding linear solutions. A non-linear solution is found exactly. The back-reaction induces a repulsion of geodesics and a shielding of the singularity by an event horizon but also introduces closed timelike curves.Comment: 11 pages, 3 figures. v2: references and comments on linear stability (Sect.2) adde

An Evaluation of Image Velocimetry Techniques under Low Flow Conditions and High Seeding Densities Using Unmanned Aerial Systems

Image velocimetry has proven to be a promising technique for monitoring river flows using remotely operated platforms such as Unmanned Aerial Systems (UAS). However, the application of various image velocimetry algorithms has not been extensively assessed. Therefore, a sensitivity analysis has been conducted on five different image velocimetry algorithms including Large Scale Particle Image Velocimetry (LSPIV), Large-Scale Particle Tracking Velocimetry (LSPTV), Kanade−Lucas Tomasi Image Velocimetry (KLT-IV or KLT), Optical Tracking Velocimetry (OTV) and Surface Structure Image Velocimetry (SSIV), during low river flow conditions (average surface velocities of 0.12−0.14 m s - 1 , Q60) on the River Kolubara, Central Serbia. A DJI Phantom 4 Pro UAS was used to collect two 30-second videos of the surface flow. Artificial seeding material was distributed homogeneously across the rivers surface, to enhance the conditions for image velocimetry techniques. The sensitivity analysis was performed on comparable parameters between the different algorithms, including the particle identification area parameters (such as Interrogation Area (LSPIV, LSPTV and SSIV), Block Size (KLT-IV) and Trajectory Length (OTV)) and the feature extraction rate. Results highlighted that KLT and SSIV were sensitive to changing the feature extraction rate; however, changing the particle identification area did not affect the surface velocity results significantly. OTV and LSPTV, on the other hand, highlighted that changing the particle identification area presented higher variability in the results, while changing the feature extraction rate did not affect the surface velocity outputs. LSPIV proved to be sensitive to changing both the feature extraction rate and the particle identification area. This analysis has led to the conclusions that for surface velocities of approximately 0.12 m s - 1 image velocimetry techniques can provide results comparable to traditional techniques such as ADCPs. However, LSPIV, LSPTV and OTV require additional effort for calibration and selecting the appropriate parameters when compared to KLT-IV and SSIV. Despite the varying levels of sensitivity of each algorithm to changing parameters, all configuration image velocimetry algorithms provided results that were within 0.05 m s - 1 of the ADCP measurements, on average

Identification of limb-specific Lmx1b auto-regulatory modules with Nail-patella syndrome pathogenicity

© The Author(s) 2021.LMX1B haploinsufficiency causes Nail-patella syndrome (NPS; MIM 161200), characterized by nail dysplasia, absent/hypoplastic patellae, chronic kidney disease, and glaucoma. Accordingly in mice, Lmx1b has been shown to play crucial roles in the development of the limb, kidney and eye. Although one functional allele of Lmx1b appears adequate for development, Lmx1b null mice display ventral-ventral distal limbs with abnormal kidney, eye and cerebellar development, more disruptive, but fully concordant with NPS. In Lmx1b functional knockouts (KOs), Lmx1b transcription in the limb is decreased nearly 6-fold, indicating autoregulation. Herein, we report on two conserved Lmx1b-associated cis-regulatory modules (LARM1 and LARM2) that are bound by Lmx1b, amplify Lmx1b expression with unique spatial modularity in the limb, and are necessary for Lmx1b-mediated limb dorsalization. These enhancers, being conserved across vertebrates (including coelacanth, but not other fish species), and required for normal locomotion, provide a unique opportunity to study the role of dorsalization in the fin to limb transition. We also report on two NPS patient families with normal LMX1B coding sequence, but with loss-of-function variations in the LARM1/2 region, stressing the role of regulatory modules in disease pathogenesis.This work was supported in part by grants from the Spanish Ministerio de Ciencia, Innovación y Universidades (M.A.R) (BFU2017-88265-P); the National Organization for Rare Disorders (K.C.O.), and the Loma Linda University Pathology Research Endowment Fund (K.C.O.)

Long acting risperidone in Australian patients with chronic schizophrenia: 24-month data from the e-STAR database

<p>Abstract</p> <p>Background</p> <p>This observational study was designed to collect treatment outcomes data in patients using the electronic Schizophrenia Treatment Adherence Registry (e-STAR).</p> <p>Methods</p> <p>Patients with schizophrenia or schizoaffective disorder in Australia who were prescribed risperidone long-acting injection (RLAI) between 2003 and 2007 were assessed 12-months retrospectively, at baseline and 24-months prospectively at 3-monthly intervals. The intent-to-treat population, defined as all patients who received at least one dose of RLAI at baseline, was used for the efficacy and safety analyses.</p> <p>Results</p> <p>At total of 784 patients (74% with schizophrenia, 69.8% male) with a mean age of 37.1 ± 12.5 years and 10.6 ± 9.5 years since diagnosis were included in this Australian cohort. A significant improvement in mean Clinical Global Impression - severity score was observed at 24-months (4.52 ± 1.04 at baseline, 3.56 ± 1.10 at 24-months). Most of this improvement was seen by 3-months and was also reflected in mean Global Assessment of Functioning score, which improved significantly at 24-months (42.9 ± 14.5 at baseline, 59 ± 15.4 at 24-months). For patients still receiving RLAI at 24-months there was an increase from a mean baseline RLAI dose of 26.4 ± 5 mg to 43.4 ± 15.7 mg. Sixty-six percent of patients discontinued RLAI before the 24-month period--this decreased to 46% once patients lost to follow-up were excluded.</p> <p>Conclusion</p> <p>Over the 24-month period, initiation of RLAI was associated with improved patient functioning and illness severity in patients with schizophrenia or schizoaffective disorder. Improved outcomes were observed early and sustained throughout the study.</p> <p>Trial Registration</p> <p>Clinical Trials Registration Number, <a href="http://www.clinicaltrials.gov/ct2/show/NCT00283517">NCT00283517</a>.</p

Mast Cell Diseases in Practice and Research:Issues and Perspectives Raised by Patients and Their Recommendations to the Scientific Community and Beyond

Background: Since 2010, patients and physicians have collaborated to understand unmet needs of patients with mast cell diseases, incorporating mastocytosis and mast cell activation disorders, which include mast cell activation syndromes. Objective: This Open Innovation in Science project aims to expand understanding of the needs of patients affected by mast cell diseases, and encourage global communication among patient advocacy groups, physicians, researchers, industry, and government. A major aim is to support the scientific community's efforts to improve diagnosis, management, therapy, and patients’ quality of life by addressing unmet needs. Methods: In collaboration with mast cell disease specialists, 13 patient advocacy groups from 12 countries and regions developed lists of top patient needs. A core team of leaders from patient advocacy groups collected and analyzed the data and proposed possible actions to address patient needs. Results: Findings identified similarities and differences among participating countries in unmet needs between patients with mastocytosis and those with mast cell activation syndromes. Issues emphasized struggles relating to the nature and rarity of mast cell diseases, their impact on quality of life, the diagnostic process, access to appropriate care, more effective treatment, and the need for research. Conclusions: Solutions vary across countries because situations differ, in particular regarding the existence of and access to centers of excellence and reference centers. Multifaceted mast cell activation syndrome barriers necessitate innovative approaches to improve access to appropriate care. The outcomes of this project should greatly support scientists and clinicians in their efforts to improve diagnosis, management, and treatment of patients with mastocytosis and mast cell activation disorders

Towards harmonization of image velocimetry techniques for river surface velocity observations

Since the turn of the 21st Century, image based velocimetry techniques have become an increasingly popular approach for determining open-channel flow in a range of hydrological settings across Europe, and beyond. Simultaneously, a range of large-scale image velocimetry algorithms have been developed, equipped with differing image pre-processing, and analytical capabilities. Yet in operational hydrometry, these techniques are utilised by few competent authorities. Therefore, imagery collected for image velocimetry analysis, along with validation data is required both to enable inter-comparisons between these differing approaches and to test their overall efficacy. Through benchmarking exercises, it will be possible to assess which approaches are best suited for a range of fluvial settings, and to focus future software developments. Here we collate, and describe datasets acquired from six countries across Europe and Asia, consisting of videos that have been subjected to a range of pre-processing, and image velocimetry analysis (Perks et al., 2019, https://doi.org/10.4121/uuid:34764be1-31f9-4626-8b11-705b4f66b95a). Validation data is available for 12 of the 13 case studies presented enabling these data to be used for validation and accuracy assessment

Hyperoxemia and excess oxygen use in early acute respiratory distress syndrome : Insights from the LUNG SAFE study

Publisher Copyright: © 2020 The Author(s). Copyright: Copyright 2020 Elsevier B.V., All rights reserved.Background: Concerns exist regarding the prevalence and impact of unnecessary oxygen use in patients with acute respiratory distress syndrome (ARDS). We examined this issue in patients with ARDS enrolled in the Large observational study to UNderstand the Global impact of Severe Acute respiratory FailurE (LUNG SAFE) study. Methods: In this secondary analysis of the LUNG SAFE study, we wished to determine the prevalence and the outcomes associated with hyperoxemia on day 1, sustained hyperoxemia, and excessive oxygen use in patients with early ARDS. Patients who fulfilled criteria of ARDS on day 1 and day 2 of acute hypoxemic respiratory failure were categorized based on the presence of hyperoxemia (PaO2 > 100 mmHg) on day 1, sustained (i.e., present on day 1 and day 2) hyperoxemia, or excessive oxygen use (FIO2 ≥ 0.60 during hyperoxemia). Results: Of 2005 patients that met the inclusion criteria, 131 (6.5%) were hypoxemic (PaO2 < 55 mmHg), 607 (30%) had hyperoxemia on day 1, and 250 (12%) had sustained hyperoxemia. Excess FIO2 use occurred in 400 (66%) out of 607 patients with hyperoxemia. Excess FIO2 use decreased from day 1 to day 2 of ARDS, with most hyperoxemic patients on day 2 receiving relatively low FIO2. Multivariate analyses found no independent relationship between day 1 hyperoxemia, sustained hyperoxemia, or excess FIO2 use and adverse clinical outcomes. Mortality was 42% in patients with excess FIO2 use, compared to 39% in a propensity-matched sample of normoxemic (PaO2 55-100 mmHg) patients (P = 0.47). Conclusions: Hyperoxemia and excess oxygen use are both prevalent in early ARDS but are most often non-sustained. No relationship was found between hyperoxemia or excessive oxygen use and patient outcome in this cohort. Trial registration: LUNG-SAFE is registered with ClinicalTrials.gov, NCT02010073publishersversionPeer reviewe