scholarly journals Topological analysis reveals state transitions in human gut and marine bacterial communities

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
William K. Chang ◽  
David VanInsberghe ◽  
Libusha Kelly
Keyword(s):  
Large Scale ◽  
Topological Analysis ◽  
Topological Data Analysis ◽  
State Transitions ◽  
Small Scale ◽  
Healthy Human ◽  
Microbiome Composition ◽  
Topological Features ◽  
Large Numbers ◽  
Underlying Mechanisms

Abstract Microbiome dynamics influence the health and functioning of human physiology and the environment and are driven in part by interactions between large numbers of microbial taxa, making large-scale prediction and modeling a challenge. Here, using topological data analysis, we identify states and dynamical features relevant to macroscopic processes. We show that gut disease processes and marine geochemical events are associated with transitions between community states, defined as topological features of the data density. We find a reproducible two-state succession during recovery from cholera in the gut microbiomes of multiple patients, evidence of dynamic stability in the gut microbiome of a healthy human after experiencing diarrhea during travel, and periodic state transitions in a marine Prochlorococcus community driven by water column cycling. Our approach bridges small-scale fluctuations in microbiome composition and large-scale changes in phenotype without details of underlying mechanisms, and provides an assessment of microbiome stability and its relation to human and environmental health.

scholarly journals Topological analysis reveals state transitions in human gut and marine bacterial communities

2019 ◽  
Author(s):  
William K. Chang ◽  
Dave VanInsberghe ◽  
Libusha Kelly
Keyword(s):  
Large Scale ◽  
Topological Analysis ◽  
Topological Data Analysis ◽  
State Transitions ◽  
Small Scale ◽  
Healthy Human ◽  
Microbiome Composition ◽  
Topological Features ◽  
Large Numbers ◽  
Underlying Mechanisms

AbstractMicrobiome dynamics influence the health and functioning of human physiology and the environment and are driven in part by interactions between large numbers of microbial taxa, making large-scale prediction and modeling a challenge. Here, using topological data analysis, we identify states and dynamical features relevant to macroscopic processes.We show that gut disease processes and marine geochemical events are associated with transitions between community states, defined as topological features of the data density. We find a reproducible two-state succession during recovery from cholera in the gut microbiomes of multiple patients, evidence of dynamic stability in the gut microbiome of a healthy human after experiencing diarrhea during travel, and periodic state transitions in a marine Prochlorococcus community driven by water column cycling. Our approach bridges small-scale fluctuations in microbiome composition and large-scale changes in phenotype without details of underlying mechanisms, and provides a novel assessment of microbiome stability and its relation to human and environmental health.

scholarly journals Values-Based Management of Archaeological Resources at a Landscape Scale

2016 ◽  
Vol 4 (2) ◽  
pp. 132-148 ◽  
Author(s):  
Francis P. McManamon ◽  
John Doershuk ◽  
William D. Lipe ◽  
Tom McCulloch ◽  
Christopher Polglase ◽  
...  
Keyword(s):  
Transmission Lines ◽  
Large Scale ◽  
Research Question ◽  
Regional Scale ◽  
Small Scale ◽  
Forest Land ◽  
Public Agencies ◽  
Large Area ◽  
Military Installation ◽  
Large Numbers

AbstractPublic agencies at all levels of government and other organizations that manage archaeological resources often face the problem of many undertakings that collectively impact large numbers of individually significant archaeological resources. Such situations arise when an agency is managing a large area, such as a national forest, land management district, park unit, wildlife refuge, or military installation. These situations also may arise in regard to large-scale development projects, such as energy developments, highways, reservoirs, transmission lines, and other major infrastructure projects that cover substantial areas. Over time, the accumulation of impacts from small-scale projects to individual archaeological resources may degrade landscape or regional-scale cultural phenomena. Typically, these impacts are mitigated at the site level without regard to how the impacts to individual resources affect the broader population of resources. Actions to mitigate impacts rarely are designed to do more than avoid resources or ensure some level of data recovery at single sites. Such mitigation activities are incapable of addressing research question at a landscape or regional scale.

scholarly journals Comparison of Gaseous and Water-Based Medium-Expansion Foam Depopulation Methods in Cull Sows

Animals ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 3179
Author(s):  
Joshua N. Lorbach ◽  
Magnus R. Campler ◽  
Brad Youngblood ◽  
Morgan B. Farnell ◽  
Tariku J. Beyene ◽  
...  
Keyword(s):  
Large Scale ◽  
Small Scale ◽  
Swine Industry ◽  
Nitrogen Gas ◽  
State Of Emergency ◽  
Carbon Dioxide Gas ◽  
Large Numbers ◽  
Nitrogen Foam ◽  
Large Scale Field ◽  
Cull Sows

The U.S. swine industry is currently inadequately prepared to counteract the increasing threat of high-consequence diseases. Although approved and preferred depopulation guidelines exist, ventilation shutdown (VSD+) is currently the only method being deployed during a state of emergency to depopulate large swine populations. However, the permitted use of VSD+ during constrained circumstances has been criticized due to raised swine welfare concerns. The objective of this study was to investigate the effectiveness of carbon dioxide gas (CO2), nitrogen gas (N2), compressed air foam (CAF), compressed nitrogen foam (CAF-N2) and aspirated foam (AF) during a 15-min dwell time on adult swine in an emergency depopulation situation. A small-scale trial using 12 sows per depopulation method showed the highest efficiency to induce cessation of movement for AF and CO2 (186.0 ± 48 vs. 202.0 ± 41, s ± SD). The ease of implementation and safety favored AF for further investigation. A large-scale field study using AF to depopulate 134 sows in modified rendering trailers showed a mean fill time of 103.8 s (SD: 5.0 s) and cessation of movement of 128.0 s (SD: 18.6 s) post filling. All sows were confirmed dead post-treatment for both trials. The implementation of AF in modified rendering trailers may allow for a safe and reliable method that allows for the expedient and mobile depopulation of both small and large numbers of sows during an emergency.

scholarly journals Interactive visualization and topology-based analysis of large-scale time-varying remote-sensing data: challenges and opportunities

2021 ◽  
Author(s):  
Riccardo Fellegara ◽  
Markus Flatken ◽  
Francesco De Zan ◽  
Andreas Gerndt
Keyword(s):  
Remote Sensing ◽  
Critical Points ◽  
Large Scale ◽  
Interactive Visualization ◽  
Remote Sensing Data ◽  
Topological Data Analysis ◽  
Complex Data ◽  
Visualization Tool ◽  
Sensing Data ◽  
Topological Features

<p>Over the last few years, the amount of large and complex data in the public domain has increased enormously and new challenges arose in the representation, analysis and visualization of such data. Considering the number of space missions that provided and will provide remote sensing data, there is still the need of a system that can be dispatched in several remote repositories and being accessible from a single client of commodity hardware.</p><p>To tackle this challenge, at the DLR Institute for Software Technology we have defined a dual backend frontend system, enabling the interactive analysis and visualization of large-scale remote sensing data. The basis for all visualization and interaction approaches is CosmoScout VR, a visualization tool developed internally at DLR, and publicly available on Github, that allows the visualization of complex planetary data and large simulation data in real-time. The dual component of this system is based on an MPI framework, called Viracocha, that enables the analysis of large data remotely, and allows the efficient network usage about sending compact and partial results for interactive visualization in CosmoScout as soon as they are computed.</p><p>A node-based interface is defined within the visualization tool, and this lets a domain expert to easily define customized pipelines for processing and visualizing the remote data. Each “node” of this interface is either linked with a feature extraction module, defined in Viracocha, or to a rendering module defined directly in CosmoScout. Being this interface completely customizable by a user, multiple pipelines can be defined over the same dataset to enhance even more the visualization feedback for analysis purposes.</p><p>Being an ongoing project, on top of these tools, as a novel strategy in EO data processing and visualization, we plan to define and implement strategies based on Topological Data Analysis (TDA). TDA is an emerging set of technique for processing the data considering its topological features. These include both the geometric information associated to a point, as well all the non-geometric scalar values, like temperature and pressure, to name a few, that can be captured during a monitoring mission. One of the major theories behind TDA is Discrete Morse Theory, that, given a scalar value, is used to define a gradient on such function, extract the critical points, identify the region-of-influence of each critical point, and so on. This strategy is parameter free and enables a domain scientist to process large datasets without a prior knowledge of it.</p><p>An interesting research question, that it will be investigated during this project is the correlation of changes of critical points at different time steps, and the identification of deformation (or changes) across time in the original dataset.</p>

scholarly journals Spectral and topological analysis of the cortical representation of the head position: does hypnotizability matter?

2018 ◽  
Author(s):  
Esther Ibanez-Marcelo ◽  
Lisa Campioni ◽  
Diego Manzoni ◽  
Enrica L Santarcangelo ◽  
Giovanni Petri
Keyword(s):  
Spectral Analysis ◽  
Data Analysis ◽  
Large Scale ◽  
Topological Analysis ◽  
Head Position ◽  
Topological Data Analysis ◽  
Proprioceptive Information ◽  
Head Positions ◽  
First Time ◽  
Topological Data

The aim of the study was to assess the EEG correlates of head positions, which have never been studied in humans, in participants with different psychophysiological characteristics, as encoded by their hypnotizability scores. This choice is motivated by earlier studies suggesting different processing of the vestibular/neck proprioceptive information in subjects with high (highs) and low (lows) hypnotizability scores maintaining their head rotated toward one side (RH). We analysed EEG signals recorded in 20 highs and 19 lows in basal conditions (head forward) and during RH, using spectral analysis, which captures changes localized to specific recording sites, and Topological Data Analysis (TDA), which instead describes large-scale differences in processing and representing sensorimotor information. Spectral analysis revealed significant differences related to the head position for alpha1, beta2, beta3, gamma bands, but not to hypnotizability. TDA instead revealed global hypnotizability-related differences in the strengths of the correlations among recording sites during RH. Significant changes were observed in lows on the left parieto-occipital side and in highs in right fronto-parietal region. Significant differences between the two groups were found in the occipital region, where changes were larger in lows than in highs. The study reports findings of the EEG correlates of the head posture for the first time, indicates that hypnotizability modulates its representation/processing on large-scale and that spectral and topological data analysis provide complementary results.

Leave no one behind? Transitioning from the military to civilian life in New Zealand

2021 ◽  
pp. 1-18
Author(s):  
Andrew Cardow ◽  
Jean-Sebastien Imbeau ◽  
Bill Willie Apiata ◽  
Jenny Martin
Keyword(s):  
New Zealand ◽  
Large Scale ◽  
Small Scale ◽  
Civilian Life ◽  
Body Of Knowledge ◽  
Transition Experience ◽  
Large Numbers ◽  
Wide Range ◽  
The Military ◽  
Military Transition

Abstract Transition from the military environment into a civilian environment is a topic that has seen increasing attention within the last two decades. There is, in the literature, a clearly articulated issue that transition from the military to the civilian world is somewhat different to transitioning from school to work, or from career to career, or from work to retirement. Many, but not all, of the extant examples regarding military transition are case studies, focus groups or small-scale qualitative surveys. The following article details a large-scale survey that took place in New Zealand in 2019. From just over 1400 responses, a wide range of information was gathered. The aim of the survey was to uncover the experiences of military who had undergone transition within New Zealand. In this respect, the survey was exploratory. We report here the qualitative results that expand the existing body of knowledge of military transition. Our results are in line with international results and demonstrate that a large majority of respondents had a less than desirable transition experience. The contribution made therefore is a reinforcement that current practice in this area is needing a great deal of attention. The following outlines the experiences our New Zealand-based respondents had and how this mirrors the extant international literature. As this was the first survey of its kind to attract large numbers of respondents within New Zealand, the results and discussion that follow present aspects of transition that the Ministry of Defence and the New Zealand Defence Force may wish to consider when planning future transition programmes.

scholarly journals Identification of Stem Cells from Large Cell Populations with Topological Scoring

2020 ◽  
Author(s):  
Mihaela E. Sardiu ◽  
Box C. Andrew ◽  
Jeff Haug ◽  
Michael P. Washburn
Keyword(s):  
Machine Learning ◽  
Flow Cytometry ◽  
Data Analysis ◽  
Large Scale ◽  
Topological Analysis ◽  
Topological Data Analysis ◽  
Cell Populations ◽  
Hematopoietic Stem ◽  
Flow Cytometry Data ◽  
Genomics And Proteomics

AbstractMachine learning and topological analysis methods are becoming increasingly used on various large-scale omics datasets. Modern high dimensional flow cytometry data sets share many features with other omics datasets like genomics and proteomics. For example, genomics or proteomics datasets can be sparse and have high dimensionality, and flow cytometry datasets can also share these features. This makes flow cytometry data potentially a suitable candidate for employing machine learning and topological scoring strategies, for example, to gain novel insights into patterns within the data. We have previously developed the Topological Score (TopS) and implemented it for the analysis of quantitative protein interaction network datasets. Here we show that the TopS approach for large scale data analysis is applicable to the analysis of a previously described flow cytometry sorted human hematopoietic stem cell dataset. We demonstrate that TopS is capable of effectively sorting this dataset into cell populations and identify rare cell populations. We demonstrate the utility of TopS when coupled with multiple approaches including topological data analysis, X-shift clustering, and t-Distributed Stochastic Neighbor Embedding (t-SNE). Our results suggest that TopS could be effectively used to analyze large scale flow cytometry datasets to find rare cell populations.

Technology and Politics in the Ecology of the Sahel

1986 ◽  
Vol 4 (2) ◽  
pp. 155-164 ◽  
Author(s):  
Ernest L. Schusky ◽  
Peter Heinricher
Keyword(s):  
Large Scale ◽  
Small Scale ◽  
Subsistence Farming ◽  
Perceived Needs ◽  
Cash Crops ◽  
Large Numbers ◽  
Cattle Herds ◽  
The 1960S ◽  
Capital Intensive ◽  
Intensive Development

Recent technological and political changes in the Sahel resemble earlier innovations that have failed to increase production or achieve equity in distribution, but perceived needs for large-scale changes remain, based on numerous misperceptions of what occurred in the famine of the late 1960s and early 1970s. Drought, large numbers of deaths, and decimation of cattle herds have been stereotyped to justify large capital-intensive development projects. Large dams, cash crops, and complex controls of the desert are among the projected schemes to increase production. The thesis of this article is that if a valid perspective of what occurred to the Sahel ecology in the 1960s is constructed, then capital-intensive projects frequently encouraging commercialization of agriculture will be replaced by labor-intensive, small-scale projects that involve primarily subsistence farming. The possible surplus from subsistence patterns is likely to exceed the surplus of large-scale efforts for a variety of reasons.

scholarly journals tmap: topological analysis of population-scale microbiome data

2018 ◽  
Author(s):  
Tianhua Liao ◽  
Yuchen Wei ◽  
Mingjing Luo ◽  
Guoping Zhao ◽  
Haokui Zhou
Keyword(s):  
Data Analysis ◽  
Large Scale ◽  
Topological Analysis ◽  
Topological Data Analysis ◽  
Link Type ◽  
Online Documentation ◽  
Microbiome Research ◽  
Population Scale ◽  
Microbiome Data ◽  
Complex Dataset

AbstractPopulation-scale microbiome study poses specific challenges in data analysis, from enterotype analysis, identification of driver species, to microbiome-wide association of host covariates. Application of advanced data mining techniques to high-dimensional complex dataset is expected to meet the rapid advancement in large scale and integrative microbiome research. Here, we present tmap, a topological data analysis framework for population-scale microbiome study. This framework can capture complex shape of large scale microbiome data into a compressive network representation. We also develop network-based statistical analysis for driver species identification and microbiome-wide association analysis. tmap can be used for exploring variations in a population-scale microbiome landscape to study host-microbiome association.Availability and implementationtmap is available at GitHub (https://github.com/GPZ-Bioinfo/tmap), accompanied with online documentation and tutorial (http://tmap.readthedocs.io).Contacthttp://[email protected]

scholarly journals Large-scale cooperation in small-scale foraging societies

2021 ◽  
Author(s):  
Robert Boyd ◽  
Peter J Richerson
Keyword(s):  
Cultural Adaptation ◽  
Evolutionary History ◽  
Large Scale ◽  
Local Environment ◽  
Small Scale ◽  
Small Contribution ◽  
Group Interactions ◽  
Distinctive Features ◽  
Collective Goods ◽  
Large Numbers

We present evidence that people in small-scale, mobile hunter-gatherer societies cooperated in large numbers to produce collective goods. Foragers engaged in large-scale communal hunts, constructed shared capital facilities; they made shared investments in improving the local environment; and they participated in warfare, alliance, and trade. Large-scale collective action often played a crucial role in subsistence. The provision of public goods involved the cooperation of many individuals, so each person made only a small contribution. This evidence suggests that large-scale cooperation occurred in the Pleistocene societies that encompass most of human evolutionary history, and therefore it is unlikely that large-scale cooperation in Holocene food producing societies results from an evolved psychology shaped only in small group interactions. Instead, large scale human cooperation needs to be explained as an adaptation, likely rooted in the distinctive features of human biology, grammatical language, increased cognitive ability, and cumulative cultural adaptation.

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