scholarly journals HYPER: Group testing via hypergraph factorization applied to COVID-19

2021 ◽  
Author(s):  
David Hong ◽  
Rounak Dey ◽  
Xihong Lin ◽  
Brian Cleary ◽  
Edgar Dobriban
Keyword(s):  
Large Scale ◽  
Resource Constraints ◽  
Group Testing ◽  
Viral Kinetics ◽  
Online Tool ◽  
Constrained Environments ◽  
Substantial Resource ◽  
The Face ◽  
Important Challenge ◽  
Global Nature

AbstractLarge scale screening is a critical tool in the life sciences, but is often limited by reagents, samples, or cost. An important challenge in screening has recently manifested in the ongoing effort to achieve widespread testing for individuals with SARS-CoV-2 infection in the face of substantial resource constraints. Group testing methods utilize constrained testing resources more efficiently by pooling specimens together, potentially allowing larger populations to be screened with fewer tests. A key challenge in group testing is to design an effective pooling strategy. The global nature of the ongoing pandemic calls for something simple (to aid implementation) and flexible (to tailor for settings with differing needs) that remains efficient. Here we propose HYPER, a new group testing method based on hypergraph factorizations. We provide characterizations under a general theoretical model, and exhaustively evaluate HYPER and proposed alternatives for SARS-CoV-2 screening under realistic simulations of epidemic spread and within-host viral kinetics. We demonstrate that HYPER performs at least as well as other methods in scenarios that are well-suited to each method, while outperforming those methods across a broad range of resource-constrained environments, and being more flexible and simple in design, and taking no expertise to implement. An online tool to implement these designs in the lab is available at http://hyper.covid19-analysis.org.

scholarly journals Efficient prevalence estimation and infected sample identification with group testing for SARS-CoV-2

2020 ◽  
Author(s):  
Brian Cleary ◽  
James A. Hay ◽  
Brendan Blumenstiel ◽  
Stacey Gabriel ◽  
Aviv Regev ◽  
...  
Keyword(s):  
Resource Constraints ◽  
Large Population ◽  
Group Testing ◽  
Individual Identification ◽  
Viral Kinetics ◽  
Community Screening ◽  
Identification Rate ◽  
Individual Level ◽  
Viral Loads ◽  
Prevalence Estimation

The ongoing pandemic of SARS-CoV-2, a novel coronavirus, caused over 3 million reported cases of coronavirus disease 2019 (COVID-19) and 200,000 reported deaths between December 2019 and April 20201. Cases and deaths will increase as the virus continues its global march outward. In the absence of effective pharmaceutical interventions or a vaccine, wide-spread virological screening is required to inform where restrictive isolation measures should be targeted and when they can be lifted2–6. However, limitations on testing capacity have restricted the ability of governments and institutions to identify individual clinical cases, appropriately measure community prevalence, and mitigate transmission. Group testing offers a way to increase efficiency, by combining samples and testing a small number of pools7–9. Here, we evaluate the effectiveness of group testing designs for individual identification or prevalence estimation of SARS-CoV-2 infection when testing capacity is limited. To do this, we developed mathematical models for epidemic spread, incorporating empirically measured individual-level viral kinetics to simulate changing viral loads in a large population over the course of an epidemic. We used these to construct representative populations and assess pooling strategies for community screening, accounting for variability in viral load samples, dilution effects, changing prevalence and resource constraints. We confirmed our group testing framework through pooled tests on de-identified human nasopharyngeal specimens with viral loads representative of the larger population. We show that group testing designs can both accurately estimate overall prevalence using a small number of measurements and substantially increase the identification rate of infected individuals in resource-limited settings.

scholarly journals Using viral load and epidemic dynamics to optimize pooled testing in resource-constrained settings

2021 ◽  
Vol 13 (589) ◽  
pp. eabf1568 ◽  
Author(s):  
Brian Cleary ◽  
James A. Hay ◽  
Brendan Blumenstiel ◽  
Maegan Harden ◽  
Michelle Cipicchio ◽  
...  
Keyword(s):  
Time Course ◽  
Resource Constraints ◽  
Group Testing ◽  
Individual Identification ◽  
Pooling Designs ◽  
Viral Kinetics ◽  
Viral Loads ◽  
Pooled Testing ◽  
Epidemic Dynamics ◽  
Resource Limited

Virological testing is central to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) containment, but many settings face severe limitations on testing. Group testing offers a way to increase throughput by testing pools of combined samples; however, most proposed designs have not yet addressed key concerns over sensitivity loss and implementation feasibility. Here, we combined a mathematical model of epidemic spread and empirically derived viral kinetics for SARS-CoV-2 infections to identify pooling designs that are robust to changes in prevalence and to ratify sensitivity losses against the time course of individual infections. We show that prevalence can be accurately estimated across a broad range, from 0.02 to 20%, using only a few dozen pooled tests and using up to 400 times fewer tests than would be needed for individual identification. We then exhaustively evaluated the ability of different pooling designs to maximize the number of detected infections under various resource constraints, finding that simple pooling designs can identify up to 20 times as many true positives as individual testing with a given budget. Crucially, we confirmed that our theoretical results can be translated into practice using pooled human nasopharyngeal specimens by accurately estimating a 1% prevalence among 2304 samples using only 48 tests and through pooled sample identification in a panel of 960 samples. Our results show that accounting for variation in sampled viral loads provides a nuanced picture of how pooling affects sensitivity to detect infections. Using simple, practical group testing designs can vastly increase surveillance capabilities in resource-limited settings.

Ban Ki-moon, 2007–2016

2018 ◽  
Author(s):  
Richard Gowan
Keyword(s):  
United States ◽  
Decision Making ◽  
Security Council ◽  
Large Scale ◽  
Central African Republic ◽  
The United States ◽  
Cautious Approach ◽  
Peacekeeping Operations ◽  
Council Decision ◽  
The Face

During Ban Ki-moon’s tenure, the Security Council was shaken by P5 divisions over Kosovo, Georgia, Libya, Syria, and Ukraine. Yet it also continued to mandate and sustain large-scale peacekeeping operations in Africa, placing major burdens on the UN Secretariat. The chapter will argue that Ban initially took a cautious approach to controversies with the Council, and earned a reputation for excessive passivity in the face of crisis and deference to the United States. The second half of the chapter suggests that Ban shifted to a more activist pressure as his tenure went on, pressing the Council to act in cases including Côte d’Ivoire, Libya, and Syria. The chapter will argue that Ban had only a marginal impact on Council decision-making, even though he made a creditable effort to speak truth to power over cases such as the Central African Republic (CAR), challenging Council members to live up to their responsibilities.

scholarly journals Reframing refugee crisis: A “European crisis of migration” or a “crisis of protection”?

2021 ◽  
pp. 239965442198970
Author(s):  
Maissaa Almustafa
Keyword(s):  
Large Scale ◽  
Global South ◽  
Global Media ◽  
Developing Regions ◽  
International Protection ◽  
High Commissioner ◽  
The Face ◽  
Global North ◽  
Displaced People ◽  
Resettlement Programs

The end of 2015 witnessed a global record in the number of forcibly displaced people fleeing because of wars and persecution. The unprecedented total of 65.3 million displaced individuals, out of which 21.3 million were refugees, was the highest number that the United Nations High Commissioner for Refugees (UNHCR) has recorded since its establishment in 1950. During the same year and in the face of this large-scale crisis, only 107,100 refugees were admitted for resettlement through official resettlement programs, whereas 3.2 million people applied for asylum globally. And in spite of the fact that the majority of the world refugees are hosted in ten developing regions, the dominant narrative in the global media was about the “unauthorized” arrival of more than one million asylum seekers in Europe by sea during 2015. This paper argues that the unexpected nature of refugees’ arrivals has proven that refugees were supposed to be contained in their camps in the Global South, deterred from reaching the territories of the Global North, represented here by Europe. Thus, the paper proposes that these arrivals are rather reflections of a crisis of protection that developed in the Global South where containment and deterrence strategies against refugees from the Global South exacerbate their inhumane displacement conditions in home regions. In the same context, the paper discusses how international protection structures have been reconstructed to serve the same goals of containment and deterrence, with the ultimate aim of putting people ‘back in place’ with minimal access to protection and rights.

Conservation of animal genetic resources: approaches and technologies for in situ and ex situ conservation

2008 ◽  
Vol 42 ◽  
pp. 71-85 ◽  
Author(s):  
J.A. Woolliams ◽  
O. Matika ◽  
J. Pattison
Keyword(s):  
Rural Communities ◽  
Genetic Resources ◽  
Large Scale ◽  
Production Systems ◽  
Regional Distribution ◽  
Livestock Production ◽  
Ex Situ ◽  
Animal Genetic Resources ◽  
The Face ◽  
Livestock Products

SummaryLivestock production faces major challenges through the coincidence of major drivers of change, some with conflicting directions. These are:1. An unprecedented global change in demands for traditional livestock products such as meat, milk and eggs.2. Large changes in the demographic and regional distribution of these demands.3. The need to reduce poverty in rural communities by providing sustainable livelihoods.4. The possible emergence of new agricultural outputs such as bio-fuels making a significant impact upon traditional production systems.5. A growing awareness of the need to reduce the environmental impact of livestock production.6. The uncertainty in the scale and impact of climate change. This paper explores these challenges from a scientific perspective in the face of the large-scale and selective erosion of our animal genetic resources, and concludes thai there is a stronger and more urgent need than ever before to secure the livestock genetic resources available to humankind through a comprehensive global conservation programme.

Analyzing and optimizing the carbon utilization and lipid yield at different light intensities for Scenedesmus arcuatus

2021 ◽  
Vol 25 (11) ◽  
pp. 1-10
Author(s):  
K. Vasumathi ◽  
Raja Vadivu G. Nadana ◽  
E.M. Nithiya ◽  
K. Sundar ◽  
M. Premalatha
Keyword(s):  
Light Intensity ◽  
Large Scale ◽  
Biomass Yield ◽  
Osmotic Shock ◽  
High Light Intensity ◽  
Carbon Utilization ◽  
Lipid Yield ◽  
The Face ◽  
Photosynthetic Microorganism ◽  
Pre Treatment

Microalgae, the photosynthetic microorganism growing abundantly in marine and aquatic ecosystems, are potential source for biological sequestration of CO2. The carbon uptake differs in the presence of other nutrients, light intensity etc. The biomass yield of Scenedesmus arcuatus var capitatus was studied based on the Face Centred Central Composite design (FCCD) of Response Surface Methodology (RSM) for nitrate, phosphate and carbonate under different conditions (laboratory, room and sunlight conditions). Various pre-treatments (osmotic shock, autoclaving, microwave and ultrasonication) were employed to find the best method for maximum lipid yield. The biomass yield reached a maximum of 1 g/L under sunlight conditions of nitrate concentration 500 ppm and carbonate 2000 ppm. The laboratory conditions resulted in a biomass yield of 0.59 g/L at 500 ppm nitrate, 1000 ppm carbonate and 250 ppm phosphate. Under room conditions, the yield was very low (0.11 g/L). Osmotic shock resulted in higher lipid yield than the other pre-treatment methods. The ability of Scenedesmus arcuatus to uptake high carbon under sunlight conditions and to adapt to high light intensity and fluctuations in light intensity concludes that this species is suitable for large-scale open pond cultivation for CO2 sequestration and production of metabolites.

Context-aware Adaptive Surgery

2021 ◽  
Vol 5 (3) ◽  
pp. 1-22
Author(s):  
Hongli Wang ◽  
Bin Guo ◽  
Jiaqi Liu ◽  
Sicong Liu ◽  
Yungang Wu ◽  
...  
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Resource Constraints ◽  
Search Algorithm ◽  
Search Time ◽  
State Graph ◽  
Context Aware ◽  
Optimal Partition ◽  
Research Attention ◽  
Neighbor Effect

Deep Neural Networks (DNNs) have made massive progress in many fields and deploying DNNs on end devices has become an emerging trend to make intelligence closer to users. However, it is challenging to deploy large-scale and computation-intensive DNNs on resource-constrained end devices due to their small size and lightweight. To this end, model partition, which aims to partition DNNs into multiple parts to realize the collaborative computing of multiple devices, has received extensive research attention. To find the optimal partition, most existing approaches need to run from scratch under given resource constraints. However, they ignore that resources of devices (e.g., storage, battery power), and performance requirements (e.g., inference latency), are often continuously changing, making the optimal partition solution change constantly during processing. Therefore, it is very important to reduce the tuning latency of model partition to realize the real-time adaption under the changing processing context. To address these problems, we propose the Context-aware Adaptive Surgery (CAS) framework to actively perceive the changing processing context, and adaptively find the appropriate partition solution in real-time. Specifically, we construct the partition state graph to comprehensively model different partition solutions of DNNs by import context resources. Then "the neighbor effect" is proposed, which provides the heuristic rule for the search process. When the processing context changes, CAS adopts the runtime search algorithm, Graph-based Adaptive DNN Surgery (GADS), to quickly find the appropriate partition that satisfies resource constraints under the guidance of the neighbor effect. The experimental results show that CAS realizes adaptively rapid tuning of the model partition solutions in 10ms scale even for large DNNs (2.25x to 221.7x search time improvement than the state-of-the-art researches), and the total inference latency still keeps the same level with baselines.

scholarly journals Large-scale unsupervised clustering of Orca vocalizations: a model for describing orca communication systems

2019 ◽  
Author(s):  
Marion Poupard ◽  
Paul Best ◽  
Jan Schlüter ◽  
Helena Symonds ◽  
Paul Spong ◽  
...  
Keyword(s):  
Communication Systems ◽  
Large Scale ◽  
Pitch Contour ◽  
Call Type ◽  
Recording Station ◽  
The Face ◽  
Multichannel Recordings ◽  
Type Classification ◽  
Anthropic Pressure

Killer whales (Orcinus orca) can produce 3 types of signals: clicks, whistles and vocalizations. This study focuses on Orca vocalizations from northern Vancouver Island (Hanson Island) where the NGO Orcalab developed a multi-hydrophone recording station to study Orcas. The acoustic station is composed of 5 hydrophones and extends over 50 km 2 of ocean. Since 2015 we are continuously streaming the hydrophone signals to our laboratory in Toulon, France, yielding nearly 50 TB of synchronous multichannel recordings. In previous work, we trained a Convolutional Neural Network (CNN) to detect Orca vocalizations, using transfer learning from a bird activity dataset. Here, for each detected vocalization, we estimate the pitch contour (fundamental frequency). Finally, we cluster vocalizations by features describing the pitch contour. While preliminary, our results demonstrate a possible route towards automatic Orca call type classification. Furthermore, they can be linked to the presence of particular Orca pods in the area according to the classification of their call types. A large-scale call type classification would allow new insights on phonotactics and ethoacoustics of endangered Orca populations in the face of increasing anthropic pressure.

Sign in / Sign up

Export Citation Format

Share Document