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68 results for “social complexity”
Twitter hashtags time series used in the paper "Universality, criticality and complexity of information propagation in social media"
<pre>These files contain the time series and the associated hashtags we obtained by sampling Twitter for our paper "Universality, criticality and complexity of information propagation on social media". The analysis is reported in <a href="https://arxiv.org/abs/2109.00116">https://www.nature.com/articles/s41467-022-28964-8</a> Please acknowledge the use of these data by citing the paper above. ################################# ################################# DATA ORGANIZATION We created a single zip file with all the time series and a single zip file with all the hashtags. There is a one-to-one correspondence between lines in the two files. ################################# ################################# FILES CONTENT As stated, here is a one-to-one correspondence between lines in the time series file and lines in the hashtags file, i.e., the hashtag stored in line X is the hashtag of the time series stored in line X. Time series are stored as follows: Ka t1 t2 t3 \n Kb t1 t2 t3 t4 t5 \n . . . Kn t1 t2 \n where: Ka, Kb,..., Kn is an integer specifying the number of events that compose the time series a, b,..., n respectively. In the example above we would have Ka=3, Kb=5, Kn=2. t1 t2 ... is the time series, i.e., a sequence of chronologically ordered interevent times. The last interevent time, in our implementation, represents the distance between the end of the temporal window and the last event time. It thus does not represent an event. As stated in the Supplemental Material of our paper, the temporal window ranges from 2019, October 1st to 2019, November 30th. </pre>
Donor-acceptor complex formation by social self-sorting of polycyclic aromatic hydrocarbons and perylene bisimides
<p>Additional data to report <a href="https://doi.org/10.1039/D3CC03704E">https://doi.org/10.1039/D3CC03704E</a></p> <p>Self-assembly versus complexation with polycyclic aromatic hydrocarbon (PAH) guest molecules is studied for a series of perylene bisimides (PBIs). Bulky imide substituents at the PBI guide their self-assembly into dimer aggregates with null-type exciton coupling. Host-guest titration experiments with perylene and triphenylene PAHs afford 1:1 and 1:2 complexes whose properties are studied by single crystal X-ray analysis and UV/Vis and fluorescence spectroscopy.</p>
Data from: Social complexity affects cognitive abilities but not brain structure in a Poecilid fish
<p>Some cognitive abilities are suggested to be the result of a complex social life, allowing individuals to achieve higher fitness through advanced strategies. However, most evidence is correlative. Here, we provide an experimental investigation of how group size and composition affect brain and cognitive development in the guppy (<em>Poecilia reticulata</em>). For six months, we reared sexually mature females in one of three social treatments: a small conspecific group of three guppies, a large heterospecific group of three guppies and three splash tetras (<em>Copella arnoldi</em>) – a species that co-occurs with the guppy in the wild, and a large conspecific group of six guppies. We then tested the guppies' performance in self-control (inhibitory control), operant conditioning (associative learning), and cognitive flexibility (reversal learning) tasks. Using X-ray imaging, we measured their brain size and major brain regions. Larger groups of six individuals, both conspecific and heterospecific groups, showed better cognitive flexibility than smaller groups, but no difference in self-control and operant conditioning tests. Interestingly, while social manipulation had no significant effect on brain morphology, relatively larger telencephalons were associated with better cognitive flexibility. This suggests alternative mechanisms beyond brain region size enabled greater cognitive flexibility in individuals from larger groups. Although there is no clear evidence for the impact on brain morphology, our research shows that living in larger social groups can enhance cognitive flexibility. This indicates that the social environment plays a role in the cognitive development of guppies.</p>
Figure 4: Complexity of geographical space with respect of emergent organizations-MODELING SELF-ORGANIZING SYSTEMS WITH SOCIAL INSECTS ALGORITHMS
<p>The applications we focus on in the models that we will propose in the<br> following, concerns specifically the multi-center (or multi-organizational) phenomona<br> inside urban development. As an artificial ecosystem, the city development<br> has to deal with many challenges, specifically for sustainable development,<br> mixing economical, social and environmental aspects. The decentralized<br> methodology proposed in the following allows to deal with multi-criteria problems,<br> leading to propose a decision making assistance, based on simulation<br> analysis.</p>
Figure 1: Complex spatial organizational model-MODELING SELF-ORGANIZING SYSTEMS WITH SOCIAL INSECTS ALGORITHMS
<p>On Figure 1, we describe a two-level model of spatial self-organizations with<br> interactions in both directions between these two levels: the emergence of organizations<br> from entities interactions but also the feed-back process describing<br> how organizations are regulating their own entities.</p>
The diversity of social complexity in termites
<p>Sociality underpins major evolutionary transitions and significantly influences the structure and function of complex ecosystems. Social insects, seen as the pinnacle of sociality, have traits like obligate sterility that are considered 'master traits', used as single phenotypic measures of this complexity. However, evidence is mounting that completely aligning both phenotypic and evolutionary social complexity, and having obligate sterility central to both, is erroneous. We hypothesise that obligate and functional sterility are insufficient in explaining the diversity of phenotypic social complexity in social insects. To test this, we explore the relative importance of these sterility traits in an understudied but diverse taxon: the termites. We compile the largest termite social complexity dataset to date, using specimen and literature data. We find that although functional and obligate sterility explain a significant proportion of variance, neither trait are adequate singular proxies for the phenotypic social complexity of termites. Further, we show both traits have only a weak association with the other social complexity traits within termites. These findings have ramifications for our general comprehension of the frameworks of phenotypic and evolutionary social complexity and their relationship with sterility.</p>
Review of Recent Trends in Measuring the Computing Systems Intelligence-igure 2. Intelligence of different living creature (accessed 01.11.2017). 2.1. A crow solving a complex task (https://www.disclose.tv/spooky-genius-crow-had-to-be-removed-from-scientific-experiment- 314886). 2.2. A group of dolphins with a social behaviour (http://www.sciencemag.org/news/2012/04/teamwork-builds-big-brains); 2.3. An orangutan that use a spear to fish (https://primatology.net/2008/04/29/orangutan-photographed-using-tool-as-spear-to-fish)
<p>Some species of birds have been shown capable of using different tools. Many studies consider the crows as very intelligent. Smirnova, Lazareva, and Zorina (2000) suggested that crows have some kind of numerical ability. Figure 2.1 presents a crow that uses a tool, a small stone in order to catch a worm from a glass of water.The dolphins in many studies are considered intelligent at the individual level. An advanced ability of dolphins is the self-awareness. Marten and Psarakos (1995) presented an interesting study based on self-view television to distinguish between self-examination and social behavior in the Bottlenose dolphin. The most well-known abilities of dolphins are to teach, learn and cooperate. Dolphins have a complex communication and social behaviour. Figure 2.2 presents the image of a common group of dolphins. Some studies prove that primates are one of the most intelligent in the class of animals (Reader, Hager, & Laland, 2011). Orangutans are one of the most intelligent primates. The ability of orangutans to use different types of tools in order to perform tasks is well-known. Figure 2.3 presents an orangutan that uses a spear to catch fish. The orangutans can be considered intelligent at individual level.</p>
Supplementary data for: Transcriptomics of mosaic brain differentiation underlying complex division of labor in a social insect
<p>Concerted developmental programming may constrain changes in component structures of the brain, thus limiting the ability of selection acting on individual brain compartments to form an adaptive mosaic independent of total brain size or body size. Measuring patterns of gene expression underpinning brain scaling in conjunction with anatomical brain atlases can aid in identifying influences of concerted and/or mosaic evolution. Species exhibiting exceptional size and behavioral polyphenisms provide excellent systems to test predictions of brain evolution models by quantifying brain gene expression. We examined patterns of brain gene expression in a remarkably polymorphic and behaviorally complex social insect, the leafcutter ant <em>Atta</em> <em>cephalotes</em>. Approximately ~50% of differential gene expression observed among three morphologically, behaviorally, and neuroanatomically differentiated worker size groups was attributable to body size, but we also found strong evidence of differential brain gene expression unexplained by worker morphological variation. Transcriptomic analysis identified patterns of gene expression not linearly correlated with worker size but rather, in some cases, mirroring neuropil scaling. Additionally, we observed enriched gene ontology terms associated with nucleic acid regulation, metabolism, neurotransmission, and sensory perception, further supporting a relationship between brain gene expression and worker social role. These findings demonstrate that differential brain gene expression among polymorphic workers is linked to behavioral and neuroanatomical differentiation underpinning complex agrarian division of labor in <em>A</em>. <em>cephalotes</em>.</p>
Group augmentation underlies the evolution of complex sociality in the face of environmental instability
<p class="MsoNormalCxSpFirst">Although kin selection is assumed to underlie the evolution of sociality, many vertebrates—including nearly half of all cooperatively breeding birds—form groups that also include unrelated individuals. Theory predicts that despite reducing kin structure, immigration of unrelated individuals into groups can provide direct, group augmentation benefits, particularly when offspring recruitment is insufficient for group persistence. Using population dynamic modelling and analysis of long-term data, we provide clear empirical evidence of group augmentation benefits favoring the evolution and maintenance of complex societies with low kin structure and multiple reproductives. We show that in the superb starling (<em>Lamprotornis superbus</em>)—a plural cooperative breeder that forms large groups with multiple breeding pairs, and related and unrelated non-breeders of both sexes—offspring recruitment alone cannot prevent group extinction, especially in smaller groups. Further, smaller groups, which stand to benefit more from immigration, exhibit lower reproductive skew for immigrants, suggesting that reproductive opportunities as joining incentives lead to plural breeding. Yet, despite a greater likelihood of becoming a breeder in smaller groups, immigrants are more likely to join larger groups where they experience increased survivorship and greater reproductive success as breeders. Moreover, immigrants form additional breeding pairs, increasing future offspring recruitment into the group and guarding against complete reproductive failure in the face of environmental instability and high nest predation. Thus, plural breeding likely evolves because the benefits of group augmentation by immigrants generate a positive feedback loop that maintains societies with low and mixed kinship, large group sizes, and multiple reproductives.</p>
Supplementary data for: Transcriptomics of mosaic brain differentiation underlying complex division of labor in a social insect
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The diversity of social complexity in termites
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Group augmentation underlies the evolution of complex sociality in the face of environmental instability
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Data from: Social complexity affects cognitive abilities but not brain structure in a Poecilid fish
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Data from: Complex selection on a regulator of social cognition: evidence of balancing selection, regulatory interactions and population differentiation in the prairie vole Avpr1a locus
Adaptive variation in social behavior depends upon standing genetic variation, but we know little about how evolutionary forces shape genetic diversity relevant to brain and behavior. In prairie voles (Microtus ochrogaster), variants at the Avpr1a locus predict expression of the vasopressin 1a receptor in the retrosplenial cortex (RSC), a brain region that mediates spatial and contextual memory; cortical V1aR abundance in turn predicts diversity in space-use and sexual fidelity in the field. To examine the potential contributions of adaptive and neutral forces to variation at the Avpr1a locus, we explore sequence diversity at the Avpr1a locus and throughout the genome in two populations of wild prairie voles. First, we refine results demonstrating balancing selection at the locus by comparing the frequency spectrum of variants at the locus to a random sample of the genome. Next, we find that the four SNPs that predict high V1aR expression in the RSC are in stronger linkage disequilibrium than expected by chance despite high recombination among intervening variants, suggesting that epistatic selection maintains their association despite recombination. Analysis of population structure and a haplotype network for two populations revealed that this excessive LD was unlikely to be due to admixture alone. Furthermore, the two populations differed considerably in the region shown to be a regulator of V1aR expression despite the extremely low levels of genome-wide genetic differentiation. Together, our data suggest that complex selection on Avpr1a locus favors specific combinations of regulatory polymorphisms, maintains the resulting alleles at populations-specific frequencies, and may contribute to unique patterns of spatial cognition and sexual fidelity among populations.
Embryo survival in the oviduct not significantly influenced by major histocompatibility complex social signaling in the horse
<p>The major histocompatibility complex (MHC) influences sexual selection in various vertebrates. Recently, MHC-linked social signaling was also shown to influence female fertility in horses (<i>Equus caballus</i>) diagnosed 17 days after fertilization. However, it remained unclear at which stage the pregnancy was terminated. Here we test if MHC-linked cryptic female choice in horses happens during the first days of pregnancy, i.e., until shortly after embryonic entrance into the uterus and before fixation in the endometrium. We exposed estrous mares to one of several unrelated stallions, instrumentally inseminated them with semen of another stallion, and flushed the uterus 8 days later to test for the presence of embryos. In total 68 embryos could be collected from 97 experimental trials. This success rate of 70.1% was significantly different from the mean pregnancy rate of 45.7% observed 17 days after fertilization using the same experimental protocol but without embryo flushing. Embryo recovery rate was not significantly dependent on whether the mares had been socially exposed to an MHC-dissimilar or an MHC-similar stallion. These observations suggest that MHC-linked maternal strategies affect embryo survival mainly (or only) during the time of fixation in the uterus.</p>
Social interactions generate complex selection patterns in virtual worlds
<p>Understanding the influence of social interactions on individual fitness is key to improving our predictions of phenotypic evolution. However, we often overlook the different components of selection regimes arising from interactions among organisms, including social, correlational, and indirect selection. This is due to the challenging sampling efforts required in natural populations to measure phenotypes expressed during interactions and individual fitness. Furthermore, behaviours are crucial in mediating social interactions, yet few studies have explicitly quantified these selection components on behavioural traits. In this study, we capitalize on an online multiplayer videogame as a source of extensive data recording direct social interactions among prey, where prey collaborate to escape a predator in realistic ecological settings. We estimate natural and social selection and their contribution to total selection on behavioural traits mediating competition, cooperation, and predator-prey interactions. Behaviours of other prey in a group impact an individual's survival, and thus are under social selection. Depending on whether selection pressures on behaviours are synergistic or conflicting, social interactions enhance or mitigate the strength of natural selection, although natural selection remains the main driving force. Indirect selection through correlations among traits also contributed to the total selection. Thus, failing to account for the effects of social interactions and indirect selection would lead to a misestimation of the total selection acting on traits. Dissecting the contribution of each component to the total selection differential allowed us to investigate the causal mechanisms relating behaviour to fitness and quantify the importance of the behaviours of conspecifics as agents of selection. Our study emphasizes that social interactions generate complex selective regimes even in a relatively simple ecological environment.</p>
The impact of social complexity on the efficacy of natural selection in termites
<p>This repository contains the dataset and markdown files necessary to reproduce the analysis conducted for the article entitled <em>Social evolution in termites reduces natural selection efficacy</em> (NEW TITLE: <em>The impact of social complexity on the efficacy of natural selection in termites</em>). It includes both raw and processed data, as well as all scripts used in the analysis, organized by the order of execution. Instructions for setting up the environment and running the scripts are provided to facilitate replication of the results.</p> <p>Here, we look at the distribution of dN/dS within Blattodea and Isoptera in order to test for a positive relationship with eusociality.</p> <p>The file <strong>analysis.html</strong> is a R-markdown file describing step by step the analysis of the submitted manuscript. To reproduce the analysis, all files have to be downloaded within the same directory.</p> <p>For any further information or questions, please contact camille.roux@univ-lille.fr or jonathan.romiguier@umontpellier.fr.</p> <p>Please cite this repository if you use these materials in your research.</p>
Multilayer social networks reveal the social complexity of a cooperatively breeding bird
<p>Focal observations of Arabian babblers (<em>Argya squamiceps</em>). The folder contains adjacency matrices of nine social groups observed between 2017 and 2020. Some of the groups were observed multiple times, the complete list of group rounds is also provided. We recorded six different interaction types, hence the folder contains a total of 114 adjacency matrices.</p>
Data from: Global migration is driven by the complex interplay between environmental and social factors
<p><strong>The datasets were produced in the following article. When using the data, please use the following citation:</strong></p> <p>Niva V, Kallio M, Muttarak R, Taka M, Varis O, Kummu M. 2021. Global migration is driven by the complex interplay between environmental and social factors. Environmental Research Letters. <a href="https://doi.org/10.1088/1748-9326/ac2e86">https://doi.org/10.1088/1748-9326/ac2e86</a></p> <p>The data include the following files:</p> <p><strong>AC.tif </strong></p> <p> Composite index computed based on the four AC variables by taking a mean over the respective variables:</p> <p> <strong>economy.tif</strong></p> <p> Downscaled and min-max normalized income data.</p> <p> <strong>education.tif</strong></p> <p> Min-max normalized education data.</p> <p> <strong>governance.tif</strong></p> <p> Min-max normalized governance data.</p> <p> <strong>health.tif</strong></p> <p> Min-max normalized health data.</p> <p>For all of the above data, 0 and 1 represent the lowest and highest <strong>capacity</strong>, respectively.</p> <p><strong>ES.tif</strong></p> <p> Composite index computed based on the four ES variables by taking a mean over the respective variables:</p> <p> <strong>foodProdScarcityScaled.tif</strong></p> <p> Food production scarcity data based on food production data.</p> <p> <strong>droughtRiskScaled.tif</strong></p> <p> Computed and scaled drought risk based on SPEI index.</p> <p> <strong>waterRiskScaled.tif</strong></p> <p> Computed and scaled water risk data based on three water stress indices.</p> <p>For all of the above data 0 and 1 represent the lowest and highest <strong>stress</strong>, respectively. Kindly note that data for natural hazards is available at its source (please see the list below). </p> <p><strong>class_raster.tif</strong></p> <p> Spatial representation of the classification matrix.</p> <p><strong>cntryID.gpkg</strong></p> <p> Country polygons with country IDs.</p> <p><strong>cntry_raster_masked.tif</strong></p> <p> Country raster with country IDs.</p> <p><strong>countriesRegionsZones.csv</strong></p> <p> Country groups and countries.</p> <p>Dataset specifications:</p> <p>spatial extent: -180, 180, -90, 90</p> <p>spatial resolution: 5 arc-min (0.083333333 degrees)</p> <p>projection: long/lat WGS84</p> <p>no data value: NA</p> <p> </p> <p><strong>Original data to produce the above indicators and to replicate the full analysis is available at the following sources:</strong></p> <p>Net-migration data (30 arc-sec resolution): https://doi.org/10.7927/H4319SVC</p> <p>Natural hazards: https://datadryad.org/stash/dataset/doi:10.5061/dryad.h2v2398</p> <p>Governance effectiveness: https://datadryad.org/stash/dataset/doi:10.5061/dryad.h2v2398</p> <p>Human Development Indicators (income, education, health): <a href="https://doi.org/10.1038/sdata.2019.38">https://doi.org/10.1038/sdata.2019.38</a></p> <p>Water risk indicators: <a href="https://doi.org/10.46830/writn.18.00146">https://doi.org/10.46830/writn.18.00146</a></p> <p>Drought (SPEI index): <a href="https://doi.org/10.1175/2009JCLI2909.1">https://doi.org/10.1175/2009JCLI2909.1</a></p> <p>Food production: <a href="https://doi.org/10.1038/nature11420">https://doi.org/10.1038/nature11420</a></p> <p>Population data: <a href="https://doi.org/10.1177%2F0959683609356587">https://doi.org/10.1177/0959683609356587</a></p>
The social network of target of rapamycin complex 1 in plants
<p>The target of rapamycin complex 1 (TORC1) is a highly conserved serine–threonine protein kinase crucial for coordinating growth according to nutrient availability in eukaryotes. It works as a central integrator of multiple nutrient inputs such as sugar, nitrogen, and phosphate and promotes growth and biomass accumulation in response to nutrient sufficiency. Studies, especially in the past decade, have identified the central role of TORC1 in regulating growth through interaction with hormones, photoreceptors, and stress-signaling machinery in plants. In this review, we comprehensively analyse the interactome and phosphoproteome of the Arabidopsis TORC1 signaling network. Our analysis highlights the role of TORC1 as a central hub kinase communicating with the transcriptional and translational apparatus, ribosomes, chaperones, protein kinases, metabolic enzymes, and autophagy and stress response machinery to orchestrate growth in response to nutrient signals. This analysis also suggests that along with the conserved downstream components shared with other eukaryotic lineages, plant TORC1 signaling underwent several evolutionary innovations and co-opted many lineage-specific components. Based on the protein–protein interaction and phosphoproteome data, we also discuss several uncharacterized and unexplored components of the TORC1 signaling network, highlighting potential links for future studies.</p>
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