BioDeepTime : a database of biodiversity time series for modern and fossil assemblages

We thank the Paleosynthesis Project and the Volkswagen Stiftung for funding that supported this project (Az 96 796). M.C.R. acknowledges the German Research Foundation (DFG) for funding through the Cluster of Excellence ‘The Ocean Floor – Earth's Uncharted Interface’ (EXC 2077, grant no. 390741603). E.E.S. acknowledges funding from Leverhulme Trust grant RPG-201170, the Leverhulme Prize and the National Science Research Council grant NE/V011405/1. Q.J.L. and L.N. acknowledge support from the Youth Innovation Promotion Association (2019310) and the Chinese Academy of Sciences (CAS-WX2021SF-0205). A.M.P. acknowledges funding from the Leverhulme Trust through research grant RPG-2019-402. M.D. acknowledges funding from Leverhulme Trust through the Leverhulme Centre for Anthropocene Biodiversity (RC-2018-021) and a research grant (RPG-2019-402), and the European Union (ERC coralINT, 101044975). L. H. L. acknowledges funding from the European Research Council (macroevolution.abc ERC grant no. 724324). K.H.P acknowledges funding from the National Science Foundation Graduate Research Fellowship Program (DGE-2139841). H.H.M.H. acknowledges support from Peter Buck Postdoc Fellowship, Smithsonian Institution. A.T. acknowledges funding from the Slovak Research and Development Agency (APVV 22-0523) and the Slovak Scientific Grant Agency (VEGA 02/0106/23).Motivation We have little understanding of how communities respond to varying magnitudes and rates of environmental perturbations across temporal scales. BioDeepTime harmonizes assemblage time series of presence and abundance data to help facilitate investigations of community dynamics across timescales and the response of communities to natural and anthropogenic stressors. BioDeepTime includes time series of terrestrial and aquatic assemblages of varying spatial and temporal grain and extent from the present-day to millions of years ago. Main Types of Variables Included BioDeepTime currently contains 7,437,847 taxon records from 10,062 assemblage time series, each with a minimum of 10 time steps. Age constraints, sampling method, environment and taxonomic scope are provided for each time series. Spatial Location and Grain The database includes 8752 unique sampling locations from freshwater, marine and terrestrial ecosystems. Spatial grain represented by individual samples varies from quadrats on the order of several cm2 to grid cells of ~100 km2. Time Period and Grain BioDeepTime in aggregate currently spans the last 451?million years, with the 10,062 modern and fossil assemblage time series ranging in extent from years to millions of years. The median extent of modern time series is 18.7?years and for fossil series is 54,872?years. Temporal grain, the time encompassed by individual samples, ranges from days to tens of thousands of years. Major Taxa and Level of Measurement The database contains information on 28,777 unique taxa with 4,769,789 records at the species level and another 271,218 records known to the genus level, including time series of benthic and planktonic foraminifera, coccolithophores, diatoms, ostracods, plants (pollen), radiolarians and other invertebrates and vertebrates. There are to date 7012 modern and 3050 fossil time series in BioDeepTime. Software Format SQLite, Comma-separated values.Publisher PDFPeer reviewe

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Multi-messenger Observations of a Binary Neutron Star Merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ∼ 1.7 {{s}} with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of {40}-8+8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 {M}ȯ . An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ∼ 40 {{Mpc}}) less than 11 hours after the merger by the One-Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ∼10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ∼ 9 and ∼ 16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC 4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta.</p

On the mismatch in the strength of competition among fossil and modern species of planktonic Foraminifera

AimMany clades display the macroevolutionary pattern of a negative relationship between standing diversity and diversification rates. Competition among species has been proposed as the main mechanism that explains this pattern. However, we currently lack empirical insight into how the effects of individual‐level ecological interactions scale up to affect species diversification. Here, we investigate a clade that shows evidence for negative diversity‐dependent diversification in the fossil record and test whether the clade's modern communities show a corresponding signal of interspecific competition.LocationWorld's oceans.Time periodHolocene.Major taxa studiedPlanktonic Foraminifera (Rhizaria).MethodsWe explore spatial and temporal ecological patterns expected under interspecific competition. Firstly, we use a community phylogenetics approach to test for signs of local competitive exclusion among ecologically similar species (defined as closely related or of similar shell sizes) by combining species relative abundances in seafloor sediments. Secondly, we analyse whether population abundances of co‐occurring species covary negatively through time using sediment trap time‐series spanning 1–12 years.ResultsThe great majority of the assemblages are indistinguishable from randomly assembled communities, showing no significant spatial co‐occurrence patterns regarding phylogeny or size similarity. Through time, most species pairs correlated positively, indicating synchronous rather than compensatory population dynamics.Main conclusionsWe found no detectable evidence for interspecific competition structuring extant planktonic Foraminifera communities. Species co‐occurrences and population dynamics are likely regulated by the abiotic environment and/or distantly related species, rather than intra‐clade density‐dependent processes. This interpretation contradicts the idea that competition drives the clade's macroevolutionary dynamics. One way to better integrate community ecology and macroevolution is to consider that diversification dynamics are influenced by groups that interact ecologically even when distantly related

BioDeepTime:a database of biodiversity time series for modern and fossil assemblages

Motivation We have little understanding of how communities respond to varying magnitudes and rates of environmental perturbations across temporal scales. BioDeepTime harmonizes assemblage time series of presence and abundance data to help facilitate investigations of community dynamics across timescales and the response of communities to natural and anthropogenic stressors. BioDeepTime includes time series of terrestrial and aquatic assemblages of varying spatial and temporal grain and extent from the present-day to millions of years ago. Main Types of Variables Included BioDeepTime currently contains 7,437,847 taxon records from 10,062 assemblage time series, each with a minimum of 10 time steps. Age constraints, sampling method, environment and taxonomic scope are provided for each time series. Spatial Location and Grain The database includes 8752 unique sampling locations from freshwater, marine and terrestrial ecosystems. Spatial grain represented by individual samples varies from quadrats on the order of several cm2 to grid cells of ~100 km2. Time Period and Grain BioDeepTime in aggregate currently spans the last 451 million years, with the 10,062 modern and fossil assemblage time series ranging in extent from years to millions of years. The median extent of modern time series is 18.7 years and for fossil series is 54,872 years. Temporal grain, the time encompassed by individual samples, ranges from days to tens of thousands of years. Major Taxa and Level of Measurement The database contains information on 28,777 unique taxa with 4,769,789 records at the species level and another 271,218 records known to the genus level, including time series of benthic and planktonic foraminifera, coccolithophores, diatoms, ostracods, plants (pollen), radiolarians and other invertebrates and vertebrates. There are to date 7012 modern and 3050 fossil time series in BioDeepTime. Software Format SQLite, Comma-separated values

Majority-Rule Opinion Dynamics with Differential Latency: A Mechanism for Self-Organized Collective Decision-Making

Collective decision-making is a process whereby the members of a group decide on a course of action by consensus. In this paper, we propose a collective decision-making mechanism for robot swarms deployed in scenarios in which robots can choose between two actions that have the same effects but that have different execution times. The proposed mechanism allows a swarm composed of robots with no explicit knowledge about the difference in execution times between the two actions to choose the one with the shorter execution time. We use an opinion formation model that captures important elements of the scenarios in which the proposed mechanism can be used in order to predict the system's behavior. The model predicts that when the two actions have different average execution times, the swarm chooses with high probability the action with the shorter average execution time. We validate the model's predictions through a swarm robotics experiment in which robot teams must choose one of two paths of different length that connect two locations. Thanks to the proposed mechanism, a swarm made of robot teams that do not measure time or distance is able to choose the shorter path. © 2011 Springer Science + Business Media, LLC.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Prodrugs available on the Brazilian pharmaceutical market and their corresponding bioactivation pathways

The aim of this paper was to emphasize the importance of prodrug design to therapy, by examining examples available on the Brazilian pharmaceutical market. The principles of prodrug design are briefly discussed herein. Examples of prodrugs from many important therapeutic classes are shown and their advantages relative to the drugs they are derived from are also discussed. Considering the importance of these therapeutic classes, from both therapy and economic standpoints, prodrug design is a very valuable aspect in the research of new drugs and for the pharmaceutical industry as a whole.<br>O objetivo do trabalho foi ressaltar a importância do planejamento de pró-fármacos para a terapia, por meio de exemplos disponíveis no mercado farmacêutico brasileiro. Os princípios da latenciação são sucintamente discutidos. Apresentam-se exemplos de pró-fármacos de muitas classes terapêuticas importantes e as vantagens relativas aos fármacos dos quais derivam são, também, discutidas. Considerando-se a importância dessas classes terapêuticas, tanto do aspecto terapêutico quanto do econômico, o planejamento de pró-fármacos representa aspecto de grande valor na busca de novos fármacos e na indústria farmacêutica como um todo