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The following results are related to European Marine Science. Are you interested to view more results? Visit OpenAIRE - Explore.

  • European Marine Science
  • 2013-2022
  • Open Access
  • Research data
  • Other research products
  • European Commission
  • EU
  • DE
  • English
  • European Marine Science

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Wass, Sam;

    Experimental participant details The project was approved by the Research Ethics Committee at the University of East London (Approval number: EXP 1617 04). Informed consent, and intent to publish, were obtained in the usual manner. Participants were recruited from the London, Essex, Hertfordshire and Cambridge regions of the UK. In total, 91 infant-caregiver dyads were recruited to participate in the study, of whom usable autonomic data were recorded from 82. Of these, usable paired autonomic data (from both caregiver and child) were obtained from 74 participants. Further details, including exclusion criteria, and detailed demographic details on the sample, are given in Appendix 1 section 1.1. The sample size was selected following power calculations presented in the original funding application ES/N017560/1. Of note, we excluded families in which the primary day-time care was performed by the male caregiver because the numbers were insufficient to provide an adequately gender-matched sample. All participating caregivers were, therefore, female. Participants received £30 in gift vouchers as a token of gratitude for participation, split over two visits. Experimental method details Participating caregivers were invited to select a day during which they would be spending the entire day with their child but which was otherwise, as far as possible, typical for them and their child. The researcher visited the participants’ homes in the morning (c. 7:30–10am) to fit the equipment, and returned later (c. 4–7pm) to pick it up. The mean (std) recording time per day was 7.3 (1.4) hours. The equipment consisted of two wearable layers, for both infant and caregiver. For the infant, a specially designed baby-grow was worn next to the skin, which contained a built-in Electrocardiogram (ECG) recording device (recording at 250Hz), accelerometer (30Hz), Global Positioning System (GPS) (1Hz), and microphone (11.6kHz). A T-shirt, worn on top of the device, contained a pocket to hold the microphone and a miniature video camera (a commercially available Narrative Clip 2 camera). For the caregiver, a specially designed chest strap was also worn next to the skin, containing the same equipment. A cardigan, worn as a top layer, contained the microphone and video camera. The clothes were comfortable when worn and, other than a request to keep the equipment dry, participants were encouraged to behave exactly as they would do on a normal day. At the start and end of each recording session, before the devices were inserted into the clothes worn by the participants, the researchers synchronised the two devices by holding them on top of one another and moving them sharply from side to side, once per second for 10 consecutive seconds. Post hoc trained coders identified the timings of these movements in the accelerometer data from each device independently. This information was used to synchronise the two recording devices. Quantification and statistical analysis Autonomic data parsing and calculation of the autonomic composite measure. Further details on the parsing of the heart rate, heart rate variability, and actigraphy are given here: https://tinyurl.com/yckzfxf8. Here we present our motivation for collapsing these three measures into a single composite measure of autonomic arousal. Home/Awake coding. Our preliminary analyses suggested that infants tended to be strapped-in to either a buggy or car seat for much of the time that they were outdoors, which strongly influenced their autonomic data. For this reason, all of the analyses presented in the paper only include data segments in which the dyad was at home and the infant was awake. A description of how these segments were identified is given in Appendix 1 (section 1.7). Following these exclusions, the mean (std) total amount of data available per dyad was 3.7 (1.7) hours, corresponding to 221.5 (102.4) 60-second epochs per dyad. Vocal coding. The microphone recorded a 5-second snapshot of the auditory environment every 60 seconds. Post hoc, trained coders identified samples in which the infant or caregiver was vocalising, and the following codings were applied. For each coding scheme, consistency of rating between coders was achieved through discussions and joint coding sessions based on an ersatz dataset, before the actual dataset was coded. All coders were blind to study design and hypothesised study outcome. Importantly, analyses conducted on a separate, continuous dataset (see Appendix 1, section S10) suggest that the temporal structure of our vocalisations was maintained despite this ‘sparse sampling’ approach. Furthermore, our analyses examine how arousal changes relative to observed vocalisations, and any arousal changes that we do observe time-locked to vocalisations would be weakened (not strengthened) by the fact that the vocalisation data were sparsely sampled (because power would have been reduced by missing vocalizations through the sparse sampling method, rather than increased). Infant data. i) vocalisation type. A morphological coding scheme was applied with the following categories: cry, laugh, squeal, growl, quasi-resonant vowel, fully-resonant vowel, marginal syllable, canonical syllable. Overall, 29% of vocalisations were cries; 1% laughs; 1% squeal; 3% growl; 18% quasi-resonant vowel; 18% fully-resonant vowel; 6% marginal syllable; 23% canonical syllable. For analyses presented in the main text these were collapsed into cries and speech-like vocalisations, which included the following non-cry categories: quasi-resonant vowel; fully-resonant vowel; marginal syllable; canonical syllable. Laughs, squeals and growls were excluded due to rarity. ii) vocal affect was coded on a three-point scale for vocal affect (negative (fussy and difficult), neutral or positive (happy and engaged). In order to assess inter-rater reliability, 11% of the sample was double coded; Cohen’s kappa was 0.70, which is considered substantial agreement. iii) vocal intensity was coded on a three-point scale from low emotional intensity, neutral, or high emotional intensity. Adult data. i) vocalisation type. A trained coder listened to vocalisations one by one and categorised them into the following categories: Imperative, Question, Praise, Singing, Imitation of Baby Vocalisation, Laughter, Reassurance, Sighing, Storytelling. These were then further collapsed into four supraordinate categories: Positive (Singing, Laughter); Stimulating (Question); Intrusive/negative affect (Imperative, Sighing); Sensitive (Praise, Imitation of Baby Vocalisation, Reassurance, Storytelling). Overall, 14% of vocalisations were Positive; 30% were Stimulating; 41% were Intrusive; 15% were Praise. In addition, ii) vocal affect and iii) vocal intensity were coded in the same way as for the infant data. In order to assess inter-rater reliability, 24% of the sample was double coded; Cohen’s kappa was 0.60, which is considered acceptable. Physical positions while vocalising. We also ascertained the physical position of our participants while vocalising (Appendix 1 section 1.8). Permutation-based temporal clustering analyses. To estimate the significance of time-series relationships, a permutation-based temporal clustering approach was used. This procedure, which is adapted from neuroimaging, allows us to estimate the probability of temporally contiguous relationships being observed in our results, a fact that standard approaches to correcting for multiple comparisons fail to account for. See further details in Appendix 1 section 1.9. ROC analyses. In order to assess the selection of visual features we employed a signal detection framework based on the Receiver Operator Characteristic (ROC) . This analyses the degree to which arousal levels predict the timings of vocalisations relative to the timings of randomly sampled comparison samples, epoch by epoch. See Results section and 67 for more details. Arousal stability. Arousal stability was measured by calculating the auto-correlation in infant and caregiver arousal, considered separately. The auto-correlation was calculated using the Matlab function nanautocorr.m, written by Fabio Oriani. Only the first lag term was reported as previous analyses have shown that autocorrelation data show a strong first order autoregressive tendency. Arousal coupling. Arousal coupling was measured by calculating the zero-lag cross-correlation between infant and caregiver arousal. The cross-correlation was calculated by first applying a linear detrend to each measure independently and then calculating the Spearman’s correlation between the infant and caregiver arousal data within that window. Moving window analyses. To estimate how stability and coupling changed relative to vocalisations, we used a moving window analysis (see Figure 8). Arousal data were downsampled to 1-minute epochs (0.016 Hz) (which was the sampling frequency of our microphone data). The size of the moving window was set arbitrarily at 10 epochs, with a shift of 5 epochs between windows. We excerpted the stability and coupling values around each individual vocalisation, and averaged these across all vocalisations. Control analysis. Participant by participant, for each vocalisation that was observed, a random ‘non-vocalisation’ moment was selected as a moment during the day when the dyad was at home and the infant was awake but no vocalisation occurred. The same moving window analysis described above was then repeated to examine change relative to this ‘non-vocalisation event’. The same procedure was repeated 1000 times and the results averaged. Real and observed data were compared using the permutation-based temporal clustering analyses described above. Appendices available here: https://doi.org/10.31234/osf.io/gmfk7 It has been argued that a necessary condition for the emergence of speech in humans is the ability to vocalize irrespectively of underlying affective states, but when and how this happens during development remains unclear. To examine this, we used wearable microphones and autonomic sensors to collect multimodal naturalistic datasets from 12-month-olds and their caregivers. We observed that, across the day, clusters of vocalisations occur during elevated infant and caregiver arousal. This relationship is stronger in infants than caregivers: caregivers' vocalizations show greater decoupling with their own states of arousal, and their vocal production is more influenced by the infant’s arousal than their own. Different types of vocalisation elicit different patterns of change across the dyad. Cries occur following reduced infant arousal stability and lead to increased child-caregiver arousal coupling, and decreased infant arousal. Speech-like vocalisations also occur at elevated arousal, but lead to longer-lasting increases in arousal, and elicit more parental verbal responses. Our results suggest that: 12-month-old infants’ vocalisations are strongly contingent on their arousal state (for both cries and speech-like vocalisations), whereas adults’ vocalisations are more flexibly tied to their own arousal; that cries and speech-like vocalisations alter the intra-dyadic dynamics of arousal in different ways, which may be an important factor driving speech development; and that this selection mechanism which drives vocal development is anchored in our stress physiology. These data files and associated processing scripts are designed to be run in Matlab R2022a. Only the Statistics and Machine Learning Toolbox is required. Details on open-source alternatives to Matlab are given here: https://opensource.com/alternatives/matlab.

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    DRYAD; ZENODO
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    Authors: Stefanidis Fotios; Stefanou Evangelos; Boulougouris Evangelos; Karagiannidis Lazaros; +4 Authors

    Despite the current high level of safety and the efforts to make passenger ships resilient to most fire and flooding scenarios, there are still gaps and challenges in the marine emergency response and ship evacuation processes. Those challenges arise from the fact that both processes are complex, multi-variable problems that rely on parameters involving not only people and technology but also procedural and managerial issues. SafePASS Project, funded under EU’s Horizon 2020 Research and Innovation Programme, is set to radically redefine the evacuation processes by introducing new equipment, expanding the capabilities of legacy systems on-board, proposing new Life-Saving Appliances and ship layouts, and challenging the current international regulations, hence reducing the uncertainty, and increasing the efficiency in all the stages of ship evacuation and abandonment process.

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    https://doi.org/10.5281/zenodo...
    Other ORP type . 2022
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      Other ORP type . 2022
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    Authors: Lumbierres, Maria; Dahal, Prabhat Raj; Soria, Carmen D.; Di Marco, Moreno; +3 Authors

    Area of Habitat (AOH) is 'the habitat available to a species, that is, habitat within its range'. It complements a geographic range map for a species by showing potential occupancy and reducing commission errors. AOH maps are produced by subtracting areas considered unsuitable for the species from their range map, using information on each species' associations with habitat and elevation. We present AOH maps for 5,481 terrestrial mammal and 10,651 terrestrial bird species (including 1,816 migratory bird species for which we present separate maps for the resident, breeding, and non-breeding areas). Our maps have a resolution of 100 m. On average, AOH covered 66±28% of the range maps for mammals and 64±27% for birds. The AOH maps were validated independently, following a novel two-step methodology: a modeling approach to identify outliers and a species-level approach based on point localities. We used AOH maps to produce global maps of the species richness of mammals, birds, globally threatened mammals, and globally threatened birds. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 766417

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    DRYAD
    Dataset . 2022 . 2021
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      DRYAD
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    Authors: Tacconelli, Evelina;

    Data were collected during the implementation of a randomised clinical trial (Clinical trial number NCT05205759). Study data were collected and managed using REDCap electronic data capture tool hosted at the Verona University Hospital. A web-based eCRF (electronic Case Report Form) was developed and patient randomisation was centrally managed and monitored by the coordinating centre. Data monitoring was also carried out with STATA and the variables for the analysis were manipulated and created using the same software. In line with ethics board approval and informed consent signed by study participants, some variables, namely age, gender, height, weight, smoking habit, were removed from the original dataset used for the analysis. Pseudonymization was also used in order to guarantee patients' anonymity. In addition, the dataset record order was randomised so the resulting dataset is a file very similar in terms of length, fields and content to the original version, except for row order which is now completely random, and the record ID variable deleted. The dataset is based on the results of a trial called MANTICO (Clinical trial number NCT05205759). The study is a non-inferiority randomised controlled trial comparing the clinical efficacy of bamlanivimab/etesevimab, casirivimab/imdevimab, and sotrovimab in outpatients aged 50 or older with early COVID-19. The primary outcome was COVID-19 progression (hospitalisation, need of supplemental oxygen therapy, or death through day 14). STATA v.17 with an ad hoc codebook

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    Authors: Waelbroeck, Claire; Tjiputra, Jerry; Guo, Chuncheng; Nisancioglu, Kerim H.; +9 Authors

    We combine consistently dated benthic carbon isotopic records distributed over the entire Atlantic Ocean with numerical simulations performed by a glacial configuration of the Norwegian Earth System Model with active ocean biogeochemistry, in order to interpret the observed Cibicides δ13C changes at the stadial-interstadial transition corresponding to the end of Heinrich Stadial 4 (HS4) in terms of ocean circulation and remineralization changes. We show that the marked increase in Cibicides δ13C observed at the end of HS4 between ~2000 and 4200 m in the Atlantic can be explained by changes in nutrient concentrations as simulated by the model in response to the halting of freshwater input in the high latitude glacial North Atlantic. Our model results show that this Cibicides δ13C signal is associated with changes in the ratio of southern-sourced (SSW) versus northern-sourced (NSW) water masses at the core sites, whereby SSW is replaced by NSW as a consequence of the resumption of deep water formation in the northern North Atlantic and Nordic Seas after the freshwater input is halted. Our results further suggest that the contribution of ocean circulation changes to this signal increases from ~40 % at 2000 m to ~80 % at 4000 m. Below ~4200 m, the model shows little ocean circulation change but an increase in remineralization across the transition marking the end of HS4. The simulated lower remineralization during stadials than interstadials is particularly pronounced in deep subantarctic sites, in agreement with the decrease in the export production of carbon to the deep Southern Ocean during stadials found in previous studies.

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    Authors: Martins, Lucas P.; Stouffer, Daniel B.; Blendinger, Pedro G.; Böhning-Gaese, Katrin; +26 Authors

    Funding: University of Canterbury Doctoral Scholarship; The Marsden Fund, Award: UOC1705; Earthwatch Institute and Conservation International for financial support; Carlos Chagas Filho Foundation for Supporting Research in the Rio de Janeiro State – FAPERJ , Award: E-26/200.610/2022 Universidade Estadual de Santa Cruz, Award: Propp-UESC No. 00220.1100.1644/10-2018; Fundação de Amparo à Pesquisa do Estado da Bahia, Award: 0525/2016; Horizon 2020, Award: 787638; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Award: 173342 ARC SRIEAS, Award: SR200100005; National Scientific and Technical Research Council, Award: PIP 592; Instituto Venezolano de Investigaciones Científicas, Award: Project 898; Fundação de Amparo à Pesquisa do Estado de São Paulo, Award: 2014/01986-0; Fundação de Amparo à Pesquisa do Estado de São Paulo, Award: 2015/15172-7; Fundação de Amparo à Pesquisa do Estado de São Paulo, Award: 2016/18355-8; Fundação de Amparo à Pesquisa do Estado de São Paulo, Award: 2004/00810-3; Fundação de Amparo à Pesquisa do Estado de São Paulo, Award: 2008/10154-7; Brazilian Research Council, Award: 540481/01-7; Brazilian Research Council, Award: 304742/2019-8; Brazilian Research Council, Award: 300970/2015-3; Rufford Small Grants for Nature Conservation, Award: 22426–1; Rufford Small Grants for Nature Conservation, Award: 9163-1; Rufford Small Grants for Nature Conservation, Award: 11042-1; Deutsche Forschungsgemeinschaft, Award: PAK 825/1; Deutsche Forschungsgemeinschaft, Award: FOR 2730 Deutsche Forschungsgemeinschaft, Award: FOR 1246; Deutsche Forschungsgemeinschaft, Award: HE2041/20-1; Fundação para a Ciência e a Tecnologia, Award: CEECIND/00135/2017; Fundação para a Ciência e a Tecnologia, Award: UID/BIA/04004/2020; Fundação para a Ciência e a Tecnologia, Award: CEECIND/02064/2017 Species interactions can propagate disturbances across space via direct and indirect effects, potentially connecting species at a global scale. However, ecological and biogeographic boundaries may mitigate this spread by demarcating the limits of ecological networks. We tested whether large-scale ecological boundaries (ecoregions and biomes) and human disturbance gradients increase dissimilarity among plant-frugivore networks, while accounting for background spatial and elevational gradients and differences in network sampling. We assessed network dissimilarity patterns over a broad spatial scale, using 196 quantitative avian frugivory networks (encompassing 1,496 plant and 1,004 bird species) distributed across 67 ecoregions, 11 biomes, and 6 continents. We show that dissimilarities in species and interaction composition, but not network structure, are greater across ecoregion and biome boundaries and along different levels of human disturbance. Our findings indicate that biogeographic boundaries delineate the world’s biodiversity of interactions and likely contribute to mitigating the propagation of disturbances at large spatial scales. Zip-file including the Data and Code necessary for reproducing the analyses from 'Global and regional ecological boundaries explain abrupt spatial discontinuities in avian frugivory interactions'. General Information regarding the data is included as a pdf file in the download. Peer reviewed

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    DRYAD; ZENODO
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      DRYAD; ZENODO
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    Authors: Galgani, Luisa; Tzempelikou, Eleni; Kalantzi, Ioanna; Tsiola, Anastasia; +8 Authors

    Microplastics are substrates for microbial activity and can influence biomass production. This has potentially important implications in the sea-surface microlayer, the marine boundary layer that controls gas exchange with the atmosphere and where biologically produced organic compounds can accumulate. In the present study, we used six large scale mesocosms to simulate future ocean scenarios of high plastic concentration. Each mesocosm was filled with 3 m3 of seawater from the oligotrophic Sea of Crete, in the Eastern Mediterranean Sea. A known amount of standard polystyrene microbeads of 30 μm diameter was added to three replicate mesocosms, while maintaining the remaining three as plastic-free controls. Over the course of a 12-day experiment, we explored microbial organic matter dynamics in the sea-surface microlayer in the presence and absence of microplastic contamination of the underlying water. Our study shows that microplastics increased both biomass production and enrichment of carbohydrate-like and proteinaceous marine gel compounds in the sea-surface microlayer. Importantly, this resulted in a 3 % reduction in the concentration of dissolved CO2 in the underlying water. This reduction was associated to both direct and indirect impacts of microplastic pollution on the uptake of CO2 within the marine carbon cycle, by modifying the biogenic composition of the sea's boundary layer with the atmosphere. for information: luisa.galgani@icloud.com; luisa.galgani@unisi.it; lgalgani@geomar.de

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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: ZENODO; Sygma
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    ZENODO
    Dataset . 2022
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      ZENODO
      Dataset . 2022
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      ZENODO
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    Authors: Galgani, Luisa; Tzempelikou, Eleni; Kalantzi, Ioanna; Tsiola, Anastasia; +8 Authors

    Microplastics are substrates for microbial activity and can influence biomass production. This has potentially important implications at the sea-surface microlayer, the marine boundary layer that controls gas exchange with the atmosphere and where biologically produced organic compounds can accumulate. In the present study, we used large scale mesocosms (filled with 3 m3 of seawater) to simulate future ocean scenarios. We explored microbial organic matter dynamics in the sea-surface microlayer in the presence and absence of microplastic contamination of the underlying water. Our study shows that microplastics increased both biomass production and enrichment of particulate carbohydrates and proteins in the sea-surface microlayer. Importantly, this resulted in a 3% reduction in the concentration of dissolved CO2 in the underlying water. This reduction suggests direct and indirect impacts of microplastic pollution on the marine uptake of CO2, by modifying the biogenic composition of the sea’s boundary layer with the atmosphere.

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    https://doi.org/10.5281/zenodo...
    Other ORP type . 2022
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      https://doi.org/10.5281/zenodo...
      Other ORP type . 2022
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      Data sources: Sygma
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    Authors: Amjad, Khurram; Lambert, Peter; Middleton, Ceri; Greene, Richard; +1 Authors

    The advent of packaged infra-red (IR) bolometer detectors has led to thermography-based techniques becoming popular for non-destructive evaluation of aerospace structures. These packaged bolometers are relatively compact and cost about 10% the price of high-resolution IR photovoltaic effect detectors. In this work, a condition monitoring system for in situ crack detection has been presented which utilises an original equipment manufacturer (OEM) microbolometer detector. The proposed system cost approximately 1% the price of a state-of-the-art photovoltaic effect detector system and has the potential to transform the use of IR imaging for condition monitoring in the aerospace industry and elsewhere. The proposed system performs crack detection based on the principles of thermoelastic stress analysis (TSA), which is a well-established non-destructive thermography technique. Proof-of-concept lab tests were performed on open-hole aluminium specimens to compare the performance of the proposed system against an IR photovoltaic effect detector system and demonstrate its potential application for in situ crack detection in industrial environments. It was demonstrated that crack detection is possible from loading waveform signals with frequencies as low as 0.3 Hz. This represents a significant advance in the viability of TSA-based crack detection in large-scale structural tests where loading frequencies are usually lower than 1 Hz.

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    DRYAD; ZENODO
    Dataset . 2022
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      DRYAD; ZENODO
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    Authors: Kim J.N. Scherrer;

    Dataset on the number of marine fishers 1950-2015 accompanying the manuscript "Diminishing returns on labor in the global marine food system" by K. J. N. Scherrer, Y. Rousseau, L. C. L. Teh, U. R. Sumaila and E. D. Galbraith. Includes 1) script for data analysis, 2) processed fisheries labor data set, 3) separate data file with average socioeconomic indicators by country needed for analysis, 4) data documentation. 

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    ZENODO
    Dataset . 2022
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    ZENODO
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      ZENODO
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      ZENODO
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Wass, Sam;

    Experimental participant details The project was approved by the Research Ethics Committee at the University of East London (Approval number: EXP 1617 04). Informed consent, and intent to publish, were obtained in the usual manner. Participants were recruited from the London, Essex, Hertfordshire and Cambridge regions of the UK. In total, 91 infant-caregiver dyads were recruited to participate in the study, of whom usable autonomic data were recorded from 82. Of these, usable paired autonomic data (from both caregiver and child) were obtained from 74 participants. Further details, including exclusion criteria, and detailed demographic details on the sample, are given in Appendix 1 section 1.1. The sample size was selected following power calculations presented in the original funding application ES/N017560/1. Of note, we excluded families in which the primary day-time care was performed by the male caregiver because the numbers were insufficient to provide an adequately gender-matched sample. All participating caregivers were, therefore, female. Participants received £30 in gift vouchers as a token of gratitude for participation, split over two visits. Experimental method details Participating caregivers were invited to select a day during which they would be spending the entire day with their child but which was otherwise, as far as possible, typical for them and their child. The researcher visited the participants’ homes in the morning (c. 7:30–10am) to fit the equipment, and returned later (c. 4–7pm) to pick it up. The mean (std) recording time per day was 7.3 (1.4) hours. The equipment consisted of two wearable layers, for both infant and caregiver. For the infant, a specially designed baby-grow was worn next to the skin, which contained a built-in Electrocardiogram (ECG) recording device (recording at 250Hz), accelerometer (30Hz), Global Positioning System (GPS) (1Hz), and microphone (11.6kHz). A T-shirt, worn on top of the device, contained a pocket to hold the microphone and a miniature video camera (a commercially available Narrative Clip 2 camera). For the caregiver, a specially designed chest strap was also worn next to the skin, containing the same equipment. A cardigan, worn as a top layer, contained the microphone and video camera. The clothes were comfortable when worn and, other than a request to keep the equipment dry, participants were encouraged to behave exactly as they would do on a normal day. At the start and end of each recording session, before the devices were inserted into the clothes worn by the participants, the researchers synchronised the two devices by holding them on top of one another and moving them sharply from side to side, once per second for 10 consecutive seconds. Post hoc trained coders identified the timings of these movements in the accelerometer data from each device independently. This information was used to synchronise the two recording devices. Quantification and statistical analysis Autonomic data parsing and calculation of the autonomic composite measure. Further details on the parsing of the heart rate, heart rate variability, and actigraphy are given here: https://tinyurl.com/yckzfxf8. Here we present our motivation for collapsing these three measures into a single composite measure of autonomic arousal. Home/Awake coding. Our preliminary analyses suggested that infants tended to be strapped-in to either a buggy or car seat for much of the time that they were outdoors, which strongly influenced their autonomic data. For this reason, all of the analyses presented in the paper only include data segments in which the dyad was at home and the infant was awake. A description of how these segments were identified is given in Appendix 1 (section 1.7). Following these exclusions, the mean (std) total amount of data available per dyad was 3.7 (1.7) hours, corresponding to 221.5 (102.4) 60-second epochs per dyad. Vocal coding. The microphone recorded a 5-second snapshot of the auditory environment every 60 seconds. Post hoc, trained coders identified samples in which the infant or caregiver was vocalising, and the following codings were applied. For each coding scheme, consistency of rating between coders was achieved through discussions and joint coding sessions based on an ersatz dataset, before the actual dataset was coded. All coders were blind to study design and hypothesised study outcome. Importantly, analyses conducted on a separate, continuous dataset (see Appendix 1, section S10) suggest that the temporal structure of our vocalisations was maintained despite this ‘sparse sampling’ approach. Furthermore, our analyses examine how arousal changes relative to observed vocalisations, and any arousal changes that we do observe time-locked to vocalisations would be weakened (not strengthened) by the fact that the vocalisation data were sparsely sampled (because power would have been reduced by missing vocalizations through the sparse sampling method, rather than increased). Infant data. i) vocalisation type. A morphological coding scheme was applied with the following categories: cry, laugh, squeal, growl, quasi-resonant vowel, fully-resonant vowel, marginal syllable, canonical syllable. Overall, 29% of vocalisations were cries; 1% laughs; 1% squeal; 3% growl; 18% quasi-resonant vowel; 18% fully-resonant vowel; 6% marginal syllable; 23% canonical syllable. For analyses presented in the main text these were collapsed into cries and speech-like vocalisations, which included the following non-cry categories: quasi-resonant vowel; fully-resonant vowel; marginal syllable; canonical syllable. Laughs, squeals and growls were excluded due to rarity. ii) vocal affect was coded on a three-point scale for vocal affect (negative (fussy and difficult), neutral or positive (happy and engaged). In order to assess inter-rater reliability, 11% of the sample was double coded; Cohen’s kappa was 0.70, which is considered substantial agreement. iii) vocal intensity was coded on a three-point scale from low emotional intensity, neutral, or high emotional intensity. Adult data. i) vocalisation type. A trained coder listened to vocalisations one by one and categorised them into the following categories: Imperative, Question, Praise, Singing, Imitation of Baby Vocalisation, Laughter, Reassurance, Sighing, Storytelling. These were then further collapsed into four supraordinate categories: Positive (Singing, Laughter); Stimulating (Question); Intrusive/negative affect (Imperative, Sighing); Sensitive (Praise, Imitation of Baby Vocalisation, Reassurance, Storytelling). Overall, 14% of vocalisations were Positive; 30% were Stimulating; 41% were Intrusive; 15% were Praise. In addition, ii) vocal affect and iii) vocal intensity were coded in the same way as for the infant data. In order to assess inter-rater reliability, 24% of the sample was double coded; Cohen’s kappa was 0.60, which is considered acceptable. Physical positions while vocalising. We also ascertained the physical position of our participants while vocalising (Appendix 1 section 1.8). Permutation-based temporal clustering analyses. To estimate the significance of time-series relationships, a permutation-based temporal clustering approach was used. This procedure, which is adapted from neuroimaging, allows us to estimate the probability of temporally contiguous relationships being observed in our results, a fact that standard approaches to correcting for multiple comparisons fail to account for. See further details in Appendix 1 section 1.9. ROC analyses. In order to assess the selection of visual features we employed a signal detection framework based on the Receiver Operator Characteristic (ROC) . This analyses the degree to which arousal levels predict the timings of vocalisations relative to the timings of randomly sampled comparison samples, epoch by epoch. See Results section and 67 for more details. Arousal stability. Arousal stability was measured by calculating the auto-correlation in infant and caregiver arousal, considered separately. The auto-correlation was calculated using the Matlab function nanautocorr.m, written by Fabio Oriani. Only the first lag term was reported as previous analyses have shown that autocorrelation data show a strong first order autoregressive tendency. Arousal coupling. Arousal coupling was measured by calculating the zero-lag cross-correlation between infant and caregiver arousal. The cross-correlation was calculated by first applying a linear detrend to each measure independently and then calculating the Spearman’s correlation between the infant and caregiver arousal data within that window. Moving window analyses. To estimate how stability and coupling changed relative to vocalisations, we used a moving window analysis (see Figure 8). Arousal data were downsampled to 1-minute epochs (0.016 Hz) (which was the sampling frequency of our microphone data). The size of the moving window was set arbitrarily at 10 epochs, with a shift of 5 epochs between windows. We excerpted the stability and coupling values around each individual vocalisation, and averaged these across all vocalisations. Control analysis. Participant by participant, for each vocalisation that was observed, a random ‘non-vocalisation’ moment was selected as a moment during the day when the dyad was at home and the infant was awake but no vocalisation occurred. The same moving window analysis described above was then repeated to examine change relative to this ‘non-vocalisation event’. The same procedure was repeated 1000 times and the results averaged. Real and observed data were compared using the permutation-based temporal clustering analyses described above. Appendices available here: https://doi.org/10.31234/osf.io/gmfk7 It has been argued that a necessary condition for the emergence of speech in humans is the ability to vocalize irrespectively of underlying affective states, but when and how this happens during development remains unclear. To examine this, we used wearable microphones and autonomic sensors to collect multimodal naturalistic datasets from 12-month-olds and their caregivers. We observed that, across the day, clusters of vocalisations occur during elevated infant and caregiver arousal. This relationship is stronger in infants than caregivers: caregivers' vocalizations show greater decoupling with their own states of arousal, and their vocal production is more influenced by the infant’s arousal than their own. Different types of vocalisation elicit different patterns of change across the dyad. Cries occur following reduced infant arousal stability and lead to increased child-caregiver arousal coupling, and decreased infant arousal. Speech-like vocalisations also occur at elevated arousal, but lead to longer-lasting increases in arousal, and elicit more parental verbal responses. Our results suggest that: 12-month-old infants’ vocalisations are strongly contingent on their arousal state (for both cries and speech-like vocalisations), whereas adults’ vocalisations are more flexibly tied to their own arousal; that cries and speech-like vocalisations alter the intra-dyadic dynamics of arousal in different ways, which may be an important factor driving speech development; and that this selection mechanism which drives vocal development is anchored in our stress physiology. These data files and associated processing scripts are designed to be run in Matlab R2022a. Only the Statistics and Machine Learning Toolbox is required. Details on open-source alternatives to Matlab are given here: https://opensource.com/alternatives/matlab.

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    Authors: Stefanidis Fotios; Stefanou Evangelos; Boulougouris Evangelos; Karagiannidis Lazaros; +4 Authors

    Despite the current high level of safety and the efforts to make passenger ships resilient to most fire and flooding scenarios, there are still gaps and challenges in the marine emergency response and ship evacuation processes. Those challenges arise from the fact that both processes are complex, multi-variable problems that rely on parameters involving not only people and technology but also procedural and managerial issues. SafePASS Project, funded under EU’s Horizon 2020 Research and Innovation Programme, is set to radically redefine the evacuation processes by introducing new equipment, expanding the capabilities of legacy systems on-board, proposing new Life-Saving Appliances and ship layouts, and challenging the current international regulations, hence reducing the uncertainty, and increasing the efficiency in all the stages of ship evacuation and abandonment process.

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    Authors: Lumbierres, Maria; Dahal, Prabhat Raj; Soria, Carmen D.; Di Marco, Moreno; +3 Authors

    Area of Habitat (AOH) is 'the habitat available to a species, that is, habitat within its range'. It complements a geographic range map for a species by showing potential occupancy and reducing commission errors. AOH maps are produced by subtracting areas considered unsuitable for the species from their range map, using information on each species' associations with habitat and elevation. We present AOH maps for 5,481 terrestrial mammal and 10,651 terrestrial bird species (including 1,816 migratory bird species for which we present separate maps for the resident, breeding, and non-breeding areas). Our maps have a resolution of 100 m. On average, AOH covered 66±28% of the range maps for mammals and 64±27% for birds. The AOH maps were validated independently, following a novel two-step methodology: a modeling approach to identify outliers and a species-level approach based on point localities. We used AOH maps to produce global maps of the species richness of mammals, birds, globally threatened mammals, and globally threatened birds. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 766417

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    Authors: Tacconelli, Evelina;

    Data were collected during the implementation of a randomised clinical trial (Clinical trial number NCT05205759). Study data were collected and managed using REDCap electronic data capture tool hosted at the Verona University Hospital. A web-based eCRF (electronic Case Report Form) was developed and patient randomisation was centrally managed and monitored by the coordinating centre. Data monitoring was also carried out with STATA and the variables for the analysis were manipulated and created using the same software. In line with ethics board approval and informed consent signed by study participants, some variables, namely age, gender, height, weight, smoking habit, were removed from the original dataset used for the analysis. Pseudonymization was also used in order to guarantee patients' anonymity. In addition, the dataset record order was randomised so the resulting dataset is a file very similar in terms of length, fields and content to the original version, except for row order which is now completely random, and the record ID variable deleted. The dataset is based on the results of a trial called MANTICO (Clinical trial number NCT05205759). The study is a non-inferiority randomised controlled trial comparing the clinical efficacy of bamlanivimab/etesevimab, casirivimab/imdevimab, and sotrovimab in outpatients aged 50 or older with early COVID-19. The primary outcome was COVID-19 progression (hospitalisation, need of supplemental oxygen therapy, or death through day 14). STATA v.17 with an ad hoc codebook

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    Authors: Waelbroeck, Claire; Tjiputra, Jerry; Guo, Chuncheng; Nisancioglu, Kerim H.; +9 Authors

    We combine consistently dated benthic carbon isotopic records distributed over the entire Atlantic Ocean with numerical simulations performed by a glacial configuration of the Norwegian Earth System Model with active ocean biogeochemistry, in order to interpret the observed Cibicides δ13C changes at the stadial-interstadial transition corresponding to the end of Heinrich Stadial 4 (HS4) in terms of ocean circulation and remineralization changes. We show that the marked increase in Cibicides δ13C observed at the end of HS4 between ~2000 and 4200 m in the Atlantic can be explained by changes in nutrient concentrations as simulated by the model in response to the halting of freshwater input in the high latitude glacial North Atlantic. Our model results show that this Cibicides δ13C signal is associated with changes in the ratio of southern-sourced (SSW) versus northern-sourced (NSW) water masses at the core sites, whereby SSW is replaced by NSW as a consequence of the resumption of deep water formation in the northern North Atlantic and Nordic Seas after the freshwater input is halted. Our results further suggest that the contribution of ocean circulation changes to this signal increases from ~40 % at 2000 m to ~80 % at 4000 m. Below ~4200 m, the model shows little ocean circulation change but an increase in remineralization across the transition marking the end of HS4. The simulated lower remineralization during stadials than interstadials is particularly pronounced in deep subantarctic sites, in agreement with the decrease in the export production of carbon to the deep Southern Ocean during stadials found in previous studies.

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