Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Abrupt rise of new machine ecology beyond human response time.

ABSTRACT: Society's techno-social systems are becoming ever faster and more computer-orientated. However, far from simply generating faster versions of existing behaviour, we show that this speed-up can generate a new behavioural regime as humans lose the ability to intervene in real time. Analyzing millisecond-scale data for the world's largest and most powerful techno-social system, the global financial market, we uncover an abrupt transition to a new all-machine phase characterized by large numbers of subsecond extreme events. The proliferation of these subsecond events shows an intriguing correlation with the onset of the system-wide financial collapse in 2008. Our findings are consistent with an emerging ecology of competitive machines featuring 'crowds' of predatory algorithms, and highlight the need for a new scientific theory of subsecond financial phenomena.

SUBMITTER: Johnson N

PROVIDER: S-EPMC3769652 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Abrupt rise of new machine ecology beyond human response time.

Johnson Neil N Zhao Guannan G Hunsader Eric E Qi Hong H Johnson Nicholas N Meng Jing J Tivnan Brian B

Scientific reports 20130101

Society's techno-social systems are becoming ever faster and more computer-orientated. However, far from simply generating faster versions of existing behaviour, we show that this speed-up can generate a new behavioural regime as humans lose the ability to intervene in real time. Analyzing millisecond-scale data for the world's largest and most powerful techno-social system, the global financial market, we uncover an abrupt transition to a new all-machine phase characterized by large numbers of ...[more]

PMID: 24022120

Similar Datasets

Machine Learning as Ecology.

Project description:Machine learning methods have had spectacular success on numerous problems. Here we show that a prominent class of learning algorithms - including Support Vector Machines (SVMs) - have a natural interpretation in terms of ecological dynamics. We use these ideas to design new online SVM algorithms that exploit ecological invasions, and benchmark performance using the MNIST dataset. Our work provides a new ecological lens through which we can view statistical learning and opens the possibility of designing ecosystems for machine learning.

| S-EPMC7779242 | biostudies-literature

Abrupt transitions in time series with uncertainties.

Project description:Identifying abrupt transitions is a key question in various disciplines. Existing transition detection methods, however, do not rigorously account for time series uncertainties, often neglecting them altogether or assuming them to be independent and qualitatively similar. Here, we introduce a novel approach suited to handle uncertainties by representing the time series as a time-ordered sequence of probability density functions. We show how to detect abrupt transitions in such a sequence using the community structure of networks representing probabilities of recurrence. Using our approach, we detect transitions in global stock indices related to well-known periods of politico-economic volatility. We further uncover transitions in the El Niño-Southern Oscillation which coincide with periods of phase locking with the Pacific Decadal Oscillation. Finally, we provide for the first time an 'uncertainty-aware' framework which validates the hypothesis that ice-rafting events in the North Atlantic during the Holocene were synchronous with a weakened Asian summer monsoon.

| S-EPMC5752700 | biostudies-literature

Evolutionary ecology during the rise of dioxygen in the Earth's atmosphere.

Project description:Pre-photosynthetic niches were meagre with a productivity of much less than 10(-4) of modern photosynthesis. Serpentinization, arc volcanism and ridge-axis volcanism reliably provided H(2). Methanogens and acetogens reacted CO(2) with H(2) to obtain energy and make organic matter. These skills pre-adapted a bacterium for anoxygenic photosynthesis, probably starting with H(2) in lieu of an oxygen 'acceptor'. Use of ferrous iron and sulphide followed as abundant oxygen acceptors, allowing productivity to approach modern levels. The 'photobacterium' proliferated rooting much of the bacterial tree. Land photosynthetic microbes faced a dearth of oxygen acceptors and nutrients. A consortium of photosynthetic and soil bacteria aided weathering and access to ferrous iron. Biologically enhanced weathering led to the formation of shales and, ultimately, to granitic rocks. Already oxidized iron-poor sedimentary rocks and low-iron granites provided scant oxygen acceptors, as did freshwater in their drainages. Cyanobacteria evolved dioxygen production that relieved them of these vicissitudes. They did not immediately dominate the planet. Eventually, anoxygenic and oxygenic photosynthesis oxidized much of the Earth's crust and supplied sulphate to the ocean. Anoxygenic photosynthesis remained important until there was enough O(2) in downwelling seawater to quantitatively oxidize massive sulphides at mid-ocean ridge axes.

| S-EPMC2606762 | biostudies-literature

The Ecology of Acidobacteria: Moving beyond Genes and Genomes.

Project description:The phylum Acidobacteria is one of the most widespread and abundant on the planet, yet remarkably our knowledge of the role of these diverse organisms in the functioning of terrestrial ecosystems remains surprisingly rudimentary. This blatant knowledge gap stems to a large degree from the difficulties associated with the cultivation of these bacteria by classical means. Given the phylogenetic breadth of the Acidobacteria, which is similar to the metabolically diverse Proteobacteria, it is clear that detailed and functional descriptions of acidobacterial assemblages are necessary. Fortunately, recent advances are providing a glimpse into the ecology of members of the phylum Acidobacteria. These include novel cultivation and enrichment strategies, genomic characterization and analyses of metagenomic DNA from environmental samples. Here, we couple the data from these complementary approaches for a better understanding of their role in the environment, thereby providing some initial insights into the ecology of this important phylum. All cultured acidobacterial type species are heterotrophic, and members of subdivisions 1, 3, and 4 appear to be more versatile in carbohydrate utilization. Genomic and metagenomic data predict a number of ecologically relevant capabilities for some acidobacteria, including the ability to: use of nitrite as N source, respond to soil macro-, micro nutrients and soil acidity, express multiple active transporters, degrade gellan gum and produce exopolysaccharide (EPS). Although these predicted properties allude to a competitive life style in soil, only very few of these prediction shave been confirmed via physiological studies. The increased availability of genomic and physiological information, coupled to distribution data in field surveys and experiments, should direct future progress in unraveling the ecology of this important but still enigmatic phylum.

| S-EPMC4885859 | biostudies-literature

Abrupt Bolling warming and ice saddle collapse contributions to the Meltwater Pulse 1a rapid sea level rise.

Project description:Elucidating the source(s) of Meltwater Pulse 1a, the largest rapid sea level rise caused by ice melt (14-18 m in less than 340 years, 14,600 years ago), is important for understanding mechanisms of rapid ice melt and the links with abrupt climate change. Here we quantify how much and by what mechanisms the North American ice sheet could have contributed to Meltwater Pulse 1a, by driving an ice sheet model with two transient climate simulations of the last 21,000 years. Ice sheet perturbed physics ensembles were run to account for model uncertainties, constraining ice extent and volume with reconstructions of 21,000 years ago to present. We determine that the North American ice sheet produced 3-4 m global mean sea level rise in 340 years due to the abrupt Bølling warming, but this response is amplified to 5-6 m when it triggers the ice sheet saddle collapse.

| S-EPMC5053285 | biostudies-literature

Reverse chemical ecology in a moth: machine learning on odorant receptors identifies new behaviorally active agonists.

Project description:The concept of reverse chemical ecology (exploitation of molecular knowledge for chemical ecology) has recently emerged in conservation biology and human health. Here, we extend this concept to crop protection. Targeting odorant receptors from a crop pest insect, the noctuid moth Spodoptera littoralis, we demonstrate that reverse chemical ecology has the potential to accelerate the discovery of novel crop pest insect attractants and repellents. Using machine learning, we first predicted novel natural ligands for two odorant receptors, SlitOR24 and 25. Then, electrophysiological validation proved in silico predictions to be highly sensitive, as 93% and 67% of predicted agonists triggered a response in Drosophila olfactory neurons expressing SlitOR24 and SlitOR25, respectively, despite a lack of specificity. Last, when tested in Y-maze behavioral assays, the most active novel ligands of the receptors were attractive to caterpillars. This work provides a template for rational design of new eco-friendly semiochemicals to manage crop pest populations.

| S-EPMC8558168 | biostudies-literature

Beyond bar and line graphs: time for a new data presentation paradigm.

Project description:Figures in scientific publications are critically important because they often show the data supporting key findings. Our systematic review of research articles published in top physiology journals (n = 703) suggests that, as scientists, we urgently need to change our practices for presenting continuous data in small sample size studies. Papers rarely included scatterplots, box plots, and histograms that allow readers to critically evaluate continuous data. Most papers presented continuous data in bar and line graphs. This is problematic, as many different data distributions can lead to the same bar or line graph. The full data may suggest different conclusions from the summary statistics. We recommend training investigators in data presentation, encouraging a more complete presentation of data, and changing journal editorial policies. Investigators can quickly make univariate scatterplots for small sample size studies using our Excel templates.

| S-EPMC4406565 | biostudies-literature

Response of seafloor ecosystems to abrupt global climate change.

Project description:Anthropogenic climate change is predicted to decrease oceanic oxygen (O2) concentrations, with potentially significant effects on marine ecosystems. Geologically recent episodes of abrupt climatic warming provide opportunities to assess the effects of changing oxygenation on marine communities. Thus far, this knowledge has been largely restricted to investigations using Foraminifera, with little being known about ecosystem-scale responses to abrupt, climate-forced deoxygenation. We here present high-resolution records based on the first comprehensive quantitative analysis, to our knowledge, of changes in marine metazoans (Mollusca, Echinodermata, Arthropoda, and Annelida; >5,400 fossils and trace fossils) in response to the global warming associated with the last glacial to interglacial episode. The molluscan archive is dominated by extremophile taxa, including those containing endosymbiotic sulfur-oxidizing bacteria (Lucinoma aequizonatum) and those that graze on filamentous sulfur-oxidizing benthic bacterial mats (Alia permodesta). This record, from 16,100 to 3,400 y ago, demonstrates that seafloor invertebrate communities are subject to major turnover in response to relatively minor inferred changes in oxygenation (>1.5 to <0.5 mL?L(-1) [O2]) associated with abrupt (<100 y) warming of the eastern Pacific. The biotic turnover and recovery events within the record expand known rates of marine biological recovery by an order of magnitude, from <100 to >1,000 y, and illustrate the crucial role of climate and oceanographic change in driving long-term successional changes in ocean ecosystems.

| S-EPMC4403169 | biostudies-literature

Dynamic response of desert wetlands to abrupt climate change.

Project description:Desert wetlands are keystone ecosystems in arid environments and are preserved in the geologic record as groundwater discharge (GWD) deposits. GWD deposits are inherently discontinuous and stratigraphically complex, which has limited our understanding of how desert wetlands responded to past episodes of rapid climate change. Previous studies have shown that wetlands responded to climate change on glacial to interglacial timescales, but their sensitivity to short-lived climate perturbations is largely unknown. Here, we show that GWD deposits in the Las Vegas Valley (southern Nevada, United States) provide a detailed and nearly complete record of dynamic hydrologic changes during the past 35 ka (thousands of calibrated (14)C years before present), including cycles of wetland expansion and contraction that correlate tightly with climatic oscillations recorded in the Greenland ice cores. Cessation of discharge associated with rapid warming events resulted in the collapse of entire wetland systems in the Las Vegas Valley at multiple times during the late Quaternary. On average, drought-like conditions, as recorded by widespread erosion and the formation of desert soils, lasted for a few centuries. This record illustrates the vulnerability of desert wetland flora and fauna to abrupt climate change. It also shows that GWD deposits can be used to reconstruct paleohydrologic conditions at millennial to submillennial timescales and informs conservation efforts aimed at protecting these fragile ecosystems in the face of anthropogenic warming.

| S-EPMC4664373 | biostudies-literature

Beyond playing games: nephrologist vs machine in pediatric dialysis prescribing.

Project description:In a recent article in Pediatric Nephrology, Olivier Niel and colleagues applied an artificial intelligence algorithm to a clinical problem that continues to challenge experienced pediatric nephrologists: optimizing the target weight of children on dialysis. They compared blood pressure, antihypertensive medication and intradialytic symptoms in children whose target weight was prescribed firstly by a nephrologist, then subsequently using a machine learning algorithm. Improvements in all outcome measures are reported. Their innovative approach to tackling this important clinical problem appears promising. In this editorial, we discuss the strengths and weaknesses of their study and consider to what extent machine learning strategies are suited to optimizing pediatric dialysis outcomes.

| S-EPMC6132900 | biostudies-other

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data