Direct measurement of superluminal group velocity and of signal velocity in an optical fiber

We present an easy way of observing superluminal group velocities using a birefringent optical fiber and other standard devices. In the theoretical analysis, we show that the optical properties of the setup can be described using the notion of "weak value". The experiment shows that the group velocity can indeed exceed c in the fiber; and we report the first direct observation of the so-called "signal velocity", the speed at which information propagates and that cannot exceed c.Comment: 5 pages, 5 figure

PatDNN: Achieving Real-Time DNN Execution on Mobile Devices with Pattern-based Weight Pruning

With the emergence of a spectrum of high-end mobile devices, many applications that formerly required desktop-level computation capability are being transferred to these devices. However, executing the inference of Deep Neural Networks (DNNs) is still challenging considering high computation and storage demands, specifically, if real-time performance with high accuracy is needed. Weight pruning of DNNs is proposed, but existing schemes represent two extremes in the design space: non-structured pruning is fine-grained, accurate, but not hardware friendly; structured pruning is coarse-grained, hardware-efficient, but with higher accuracy loss. In this paper, we introduce a new dimension, fine-grained pruning patterns inside the coarse-grained structures, revealing a previously unknown point in design space. With the higher accuracy enabled by fine-grained pruning patterns, the unique insight is to use the compiler to re-gain and guarantee high hardware efficiency. In other words, our method achieves the best of both worlds, and is desirable across theory/algorithm, compiler, and hardware levels. The proposed PatDNN is an end-to-end framework to efficiently execute DNN on mobile devices with the help of a novel model compression technique (pattern-based pruning based on extended ADMM solution framework) and a set of thorough architecture-aware compiler- and code generation-based optimizations (filter kernel reordering, compressed weight storage, register load redundancy elimination, and parameter auto-tuning). Evaluation results demonstrate that PatDNN outperforms three state-of-the-art end-to-end DNN frameworks, TensorFlow Lite, TVM, and Alibaba Mobile Neural Network with speedup up to 44.5x, 11.4x, and 7.1x, respectively, with no accuracy compromise. Real-time inference of representative large-scale DNNs (e.g., VGG-16, ResNet-50) can be achieved using mobile devices.Comment: To be published in the Proceedings of Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS 20

Contribution of electroactive humic substances to the iron-binding ligands released during microbial remineralisation of sinking particles

Microscopic plants and animals in seawater require nutrients to survive. One of these key nutrients is iron, dissolved in seawater at very low concentrations. The growth of around half of the microscopic life in the upper ocean is dependent on the availability of this dissolved iron. These organisms form the bottom of the food chain, and their growth is linked to marine productivity and the drawdown of carbon into the deep ocean, in turn influencing climate change. Because iron tends to not dissolve easily in seawater, it must bind with compounds known as ligands, which help keep iron dissolved. However, processes controlling the composition of this ligand pool are poorly understood. As material sinks through the water column, it is broken down by marine microbes, releasing iron and ligands. Here we have studied the release of iron, ligands, and a specific type of ligand known as humic substances, during the microbial degradation of sinking particles. By doing this, we have identified a large fraction of the released ligand pool. This furthers our understanding of the processes controlling dissolved iron concentrations and distributions in ocean waters, providing key information for biogeochemical modeling and for calculating carbon sequestration in seawater

Fast dating using least-squares criteria and algorithms

International audiencePhylogenies provide a useful way to understand the evolutionary history of genetic samples, and data sets with more than a thousand taxa are becoming increasingly common, notably with viruses (e.g., human immunodeficiency virus (HIV)). Dating ancestral events is one of the first, essential goals with such data. However, current sophisticated probabilistic approaches struggle to handle data sets of this size. Here, we present very fast dating algorithms, based on a Gaussian model closely related to the Langley–Fitch molecular-clock model. We show that this model is robust to uncorrelated violations of the molecular clock. Our algorithms apply to serial data, where the tips of the tree have been sampled through times. They estimate the substitution rate and the dates of all ancestral nodes. When the input tree is unrooted, they can provide an estimate for the root position, thus representing a new, practical alternative to the standard rooting methods (e.g., midpoint). Our algorithms exploit the tree (recursive) structure of the problem at hand, and the close relationships between least-squares and linear algebra. We distinguish between an unconstrained setting and the case where the temporal precedence constraint (i.e., an ancestral node must be older that its daughter nodes) is accounted for. With rooted trees, the former is solved using linear algebra in linear computing time (i.e., proportional to the number of taxa), while the resolution of the latter, constrained setting, is based on an active-set method that runs in nearly linear time. With unrooted trees the computing time becomes (nearly) quadratic (i.e., proportional to the square of the number of taxa). In all cases, very large input trees (>10,000 taxa) can easily be processed and transformed into time-scaled trees. We compare these algorithms to standard methods (root-to-tip, r8s version of Langley–Fitch method, and BEAST). Using simulated data, we show that their estimation accuracy is similar to that of the most sophisticated methods, while their computing time is much faster. We apply these algorithms on a large data set comprising 1194 strains of Influenza virus from the pdm09 H1N1 Human pandemic. Again the results show that these algorithms provide a very fast alternative with results similar to those of other computer programs. These algorithms are implemented in the LSD software (least-squares dating), which can be downloaded from http://www.atgc-montpellier.fr/LSD/, along with all our data sets and detailed results. An Online Appendix, providing additional algorithm descriptions, tables, and figures can be found in the Supplementary Material available on Dryad at http://dx.doi.org/10.5061/dryad.968t3

Secret Sharing over Fast-Fading MIMO Wiretap Channels

Secret sharing over the fast-fading MIMO wiretap channel is considered. A source and a destination try to share secret information over a fast-fading MIMO channel in the presence of a wiretapper who also makes channel observations that are different from but correlated to those made by the destination. An interactive authenticated unrestricted public channel is also available for use by the source and destination in the secret sharing process. This falls under the "channel-type model with wiretapper" considered by Ahlswede and Csiszar. A minor extension of their result (to continuous channel alphabets) is employed to evaluate the key capacity of the fast-fading MIMO wiretap channel. The effects of spatial dimensionality provided by the use of multiple antennas at the source, destination, and wiretapper are then investigated.Comment: Revision submitted to EURASIP Journal on Wireless Communications and Networking, Special Issue on Wireless Physical Layer Security, Sept. 2009. v.3: Fixes to proofs. Matthieu Bloch added as co-author for contributions to proof

End-expiratory occlusion maneuver to predict fluid responsiveness in the intensive care unit : an echocardiographic study

Background In mechanically ventilated patients, an increase in cardiac index during an end-expiratory-occlusion test predicts fluid responsiveness. To identify this rapid increase in cardiac index, continuous and instantaneous cardiac index monitoring is necessary, decreasing its feasibility at the bedside. Our study was designed to investigate whether changes in velocity time integral and in peak velocity obtained using transthoracic echocardiography during an end-expiratory-occlusion maneuver could predict fluid responsiveness. Methods This single-center, prospective study included 50 mechanically ventilated critically ill patients. Velocity time integral and peak velocity were assessed using transthoracic echocardiography before and at the end of a 12-sec end-expiratory-occlusion maneuver. A third set of measurements was performed after volume expansion (500 mL of saline 0.9% given over 15 minutes). Patients were considered as responders if cardiac output increased by 15% or more after volume expansion. Results Twenty-eight patients were responders. At baseline, heart rate, mean arterial pressure, cardiac output, velocity time integral and peak velocity were similar between responders and non-responders. End-expiratory-occlusion maneuver induced a significant increase in velocity time integral both in responders and non-responders, and a significant increase in peak velocity only in responders. A 9% increase in velocity time integral induced by the end-expiratory-occlusion maneuver predicted fluid responsiveness with sensitivity of 89% (95% CI 72% to 98%) and specificity of 95% (95% CI 77% to 100%). An 8.5% increase in peak velocity induced by the end-expiratory-occlusion maneuver predicted fluid responsiveness with sensitivity of 64% (95% CI 44% to 81%) and specificity of 77% (95% CI 55% to 92%). The area under the receiver operating curve generated for changes in velocity time integral was significantly higher than the one generated for changes in peak velocity (0.96 ± 0.03 versus 0.70 ± 0.07, respectively, P = 0.0004 for both). The gray zone ranged between 6 and 10% (20% of the patients) for changes in velocity time integral and between 1 and 13% (62% of the patients) for changes in peak velocity. Conclusions In mechanically ventilated and sedated patients in the neuro Intensive Care Unit, changes in velocity time integral during a 12-sec end-expiratory-occlusion maneuver were able to predict fluid responsiveness and perform better than changes in peak velocity

Proceedings of the 3rd Biennial Conference of the Society for Implementation Research Collaboration (SIRC) 2015: advancing efficient methodologies through community partnerships and team science

It is well documented that the majority of adults, children and families in need of evidence-based behavioral health interventionsi do not receive them [1, 2] and that few robust empirically supported methods for implementing evidence-based practices (EBPs) exist. The Society for Implementation Research Collaboration (SIRC) represents a burgeoning effort to advance the innovation and rigor of implementation research and is uniquely focused on bringing together researchers and stakeholders committed to evaluating the implementation of complex evidence-based behavioral health interventions. Through its diverse activities and membership, SIRC aims to foster the promise of implementation research to better serve the behavioral health needs of the population by identifying rigorous, relevant, and efficient strategies that successfully transfer scientific evidence to clinical knowledge for use in real world settings [3]. SIRC began as a National Institute of Mental Health (NIMH)-funded conference series in 2010 (previously titled the “Seattle Implementation Research Conference”; $150,000 USD for 3 conferences in 2011, 2013, and 2015) with the recognition that there were multiple researchers and stakeholdersi working in parallel on innovative implementation science projects in behavioral health, but that formal channels for communicating and collaborating with one another were relatively unavailable. There was a significant need for a forum within which implementation researchers and stakeholders could learn from one another, refine approaches to science and practice, and develop an implementation research agenda using common measures, methods, and research principles to improve both the frequency and quality with which behavioral health treatment implementation is evaluated. SIRC’s membership growth is a testament to this identified need with more than 1000 members from 2011 to the present.ii SIRC’s primary objectives are to: (1) foster communication and collaboration across diverse groups, including implementation researchers, intermediariesi, as well as community stakeholders (SIRC uses the term “EBP champions” for these groups) – and to do so across multiple career levels (e.g., students, early career faculty, established investigators); and (2) enhance and disseminate rigorous measures and methodologies for implementing EBPs and evaluating EBP implementation efforts. These objectives are well aligned with Glasgow and colleagues’ [4] five core tenets deemed critical for advancing implementation science: collaboration, efficiency and speed, rigor and relevance, improved capacity, and cumulative knowledge. SIRC advances these objectives and tenets through in-person conferences, which bring together multidisciplinary implementation researchers and those implementing evidence-based behavioral health interventions in the community to share their work and create professional connections and collaborations

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Developing a test-bed for robust research governance of geoengineering: the contribution of ocean iron biogeochemistry

International audienceGeoengineering to mitigate climate change has long been proposed, but remains nebulous. Exploration of the feasibility of geoengineering first requires the development of research governance to move beyond the conceptual towards scientifically designed pilot studies. Fortuitously, 12 mesoscale (approx. 1000 km 2 ) iron enrichments, funded to investigate how ocean iron biogeochemistry altered Earth's carbon cycle in the geological past, provide proxies to better understand the benefits and drawbacks of geoengineering. The utility of these iron enrichments in the geoengineering debate is enhanced by the GEOTRACES global survey. Here, we outline how GEOTRACES surveys and process studies can provide invaluable insights into geoengineering. Surveys inform key unknowns including the regional influence and magnitude of modes of iron supply, and stimulate iron biogeochemical modelling. These advances will enable quantification of interannual variability of iron supply to assess whether any future purposeful multi-year iron-fertilization meets the principle of ‘additionality’ ( sensu Kyoto protocol). Process studies address issues including upscaling of geoengineering, and how differing iron-enrichment strategies could stimulate wide-ranging biogeochemical outcomes. In summary, the availability of databases on both mesoscale iron-enrichment studies and the GEOTRACES survey, along with modelling, policy initiatives and legislation have positioned the iron-enrichment approach as a robust multifaceted test-bed to assess proposed research into climate intervention. This article is part of the themed issue ‘Biological and climatic impacts of ocean trace element chemistry’