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5,666 results for “Social”
1p_BLA_sync_permutation_social_valence
<div> <h1>Genetically- and spatially-defined basolateral amygdala neurons control food consumption and social interaction</h1> <a href="https://github.com/limserenahansol/1p_BLA_sync_permutation_social_valence#genetically--and-spatially-defined-basolateral-amygdala-neurons-control-food-consumption-and-social-interaction"></a></div> <p>Highlights:</p> <ol> <li>Classification of molecularly-defined glutamatergic neuron types in mouse BLA with distinct spatial expression patterns.</li> <li>BLALypd1 neurons are positive-valence neurons innately responding to food and promoting normal feeding.</li> <li>BLAEtv1 neurons innately respond to aversive and social stimuli.</li> <li>BLAEtv1 neurons promote fear learning and social interactions.</li> </ol> <p> </p> <div> <h2>"Step by step" for codes for BLA neuron calcium imaging analysis</h2> <a href="https://github.com/limserenahansol/1p_BLA_sync_permutation_social_valence#step-by-step-for-codes-for-bla-neuron-calcium-imaging-analysis"></a></div> <ol> <li>Either using our demo files or your calcium imaging and behavior CSV files need to be used: Demo lists: 1. Figure4_food, 2. Figure5_social, 3. Figure5_fear_conditioning, 4. suppl.fig10_longitudinal_footshock_social.</li> </ol> <div> <p>Note</p> <p>Demo files are already preprocessed H5 files, so you can skip 2-3steps.</p> </div> <ol> <li>you need to download "core_codes" <strong>(logger.py, preprocessing.py, util.py)</strong> to synchronize the extracted behavior statistics with calcium traces (The TTL emission-reception delay is negligible (less than 30ms), therefore the behavioral statistics time series can be synchronized with calcium traces by the emission/receival time on both devices) and it would generate combined one H5 file (behavior+calcium data)</li> <li>Run <strong>Synchrnoize_h5generation.py</strong> code to apply core-codes (preprocessing) to your data:</li> </ol> <div> <pre><code>import core.preprocessing as prep </code></pre> <div> </div> </div> <ol> <li>You can run each code (5 codes) described in the paper to generate the results: <strong>1. Fear Conditioning, 2.social, 3. food, 4. permutation, 5, suppl.10 social_footshock.py</strong> code number 4 is the percentage comparison with shuffling of data in Figure4-5 as bar graph you can reproduce using the code: Figure4_5_permutation_bargraph.</li> </ol> <div> <h3>required</h3> <a href="https://github.com/limserenahansol/1p_BLA_sync_permutation_social_valence#required"></a></div> <div> <p>Note</p> <p>-System requirements Python (3.10.8): we used a Python IDE for professional developers by JetBrains, Pycharm. Packages: suite2p : <a href="https://github.com/MouseLand/suite2p">https://github.com/MouseLand/suite2p</a></p> </div> <div> <pre><code>pip install git+https://github.com/MouseLand/suite2p.git </code></pre> <div> </div> </div> <blockquote> <p>matplotlib</p> </blockquote> <div> <pre><code>pip install matplotlib pip install PyQt5 </code></pre> <div> </div> </div> <blockquote> <p>numpy</p> </blockquote> <div> <p>Warning</p> <p>our code included : matplotlib Qt5Agg An Error is happening because Google Colab and Jupyter run on virtual environments which do not support GUI outputs as you cannot open new windows through a browser. Running it locally on a code editor(Spyder, or even IDLE) ensures that it can open a new window for the GUI to initialize.</p> </div> <div> <p>Tip</p> <ul> <li>"our analysis pipeline is based on basic python packages:"</li> </ul> </div> <div> <pre><code>> import numpy as np >import h5py as h5 >import pandas as pd </code></pre> <div> </div> </div> <p>Installation guide above</p> <ul> <li>Demo -Demo_data.zip</li> </ul> <div> <h3>Acknowledgement</h3> <a href="https://github.com/limserenahansol/1p_BLA_sync_permutation_social_valence#acknowledgement"></a></div> <p>Yue Zhang</p> <p> </p> <p>https://github.com/limserenahansol/1p_BLA_sync_permutation_social_valence</p> <blockquote> <p><a href="https://github.com/limserenahansol/1p_BLA_sync_permutation_social_valence">Github link for this </a></p> </blockquote>
Climate Change Adaptation, Social Resilience, and Perceived Values Data from Turkana, Machakos and Narok County, Kenya
<p>This dataset provides socioeconomic and value perception interview data collected from 1,020 individuals living across three counties in Kenya: Turkana, Machakos and Narok. Socioeconomic data were collected on housing, healthcare, water sources, electricity access, experience of extreme weather events, community services and access to information. Value perception data were collected using the user-perceived value (UPV) method - a perception-based surveying approach which requires interviewees to select their most valued household items in different circumstances and explain their choice through 'why'-probing. This is done under different circumstances - here, either in daily life, or in the face of a climate shock. The data are made available with sub-county level geospatial attribution. Together, the socioeconomic and interview data can be used to better understand the views of different communities and demographic groups concerning climate change and extreme weather events across Kenya. They also provide insight as to the intrinsic, social, emotional, epistemic, functional, and indigenous values associated with everyday household items. The data can be used by policymakers to inform development planning and to identify gaps in available infrastructure. Additionally, researchers and development practitioners can use these data to design interventions which reflect the needs and values of communities in Kenya.</p>
Data from: Multiple effects of weather on common waxbill group foraging and social behavior
<p>The weather poses challenges for wildlife. Environmental challenges can be responded to at the group level by social animals, but the influence of weather on group behavior is poorly understood. We investigated how the weather affects behavior in a gregarious species by monitoring common waxbills <em>(Estrilda astrild</em>) in a large mesocosm during five years. We found seasonal patterns on collective foraging, aggressiveness, and the structure of the social network, usually showing two cycles per year: one peaking in Spring and a smaller one in late Summer. Controlling for seasonality, we found behavioral changes related to increased energy demands on colder and/or cloudier days, such as more frequent and larger foraging groups that resulted in less structured social networks. Rain and wind disturb movement, and we found that on rainy days foraging group journeys became briefer and more synchronous, resulting in stronger associations between individuals and less structured networks, and that on windy days foraging groups were less frequent, larger, and with more within-group aggression. The results show that the weather has more varied effects than anticipated on ecologically-relevant group behavior. We discuss how such weather-related effects can improve predictions of how social animals will react to environmental changes.</p>
Data from: Translocation experiment of taiga bean geese Anser fabalis provides evidence for oblique social learning of moult migration
<p>While there is ample evidence supporting genetic control of migratory behaviour in short-lived passerines, long-lived social species have been assumed to rely solely on cultural inheritance of migratory routes. Evidence from experimental studies supporting this idea is scarce. We tested whether the moult migration in taiga bean geese <em>Anser fabalis </em>has an inherited component or whether the birds need oblique social learning (where knowledge on migration is transferred from any experienced individual to any naïve individual conspecific) to carry out this journey. In many waterfowl species, non-breeders and failed breeders migrate to remote places for wing moult while successful breeders stay at the breeding grounds and moult with their chicks. We translocated one-year-old taiga bean geese before their first moult migration to sites outside of the breeding range to examine whether they display innate moult migration behaviour without experienced conspecifics or not. The birds were equipped with GPS-transmitters and released in randomly assigned groups of two. Wild control one-year-old birds were released immediately after capture with other non-breeding geese, while a procedural control group consisting of older birds was held in captivity until released at the same time with the translocated one-year-old birds but in the place where they were captured. Most translocated birds found conspecifics and either joined locally moulting breeders or followed experienced birds to moulting sites in Russia. Two of the translocated birds did not find other bean geese and settled to moult together in SW Finland. The wild control birds moult-migrated as expected, while only one of the procedural control birds moult-migrated to Russia and the remaining three stayed with locally moulting breeders in Finland. Our results support the idea that moult migration in geese is culturally inherited, highlighting the importance of the non-relative, experienced adult individuals have in maintaining population-specific behaviours.</p>
Aisa 1st annual conference "Nostra res agitur: open science as a social question" [section 2]
<p>Video degli interventi del pomeriggio del 22 ottobre 2015, secondo l'ordine seguente: saluti delle autorità (0:0:00-0:03:06); saluti del Presidente (0:03:07-0:12:52); J-C. Guédon (0:12.53-1:14:22); G. Destro Bisol (1:14:23-1:45:10); dibattito (1:45:11-1:56:04). La registrazione è stata curata dal Team Elearning ed Eventi del Centro Serra dell'università di Pisa.</p>
Data for: Multiple behavioral mechanisms shape development in a highly social cichlid fish
<p>Early-life social experiences shape adult phenotype, yet the underlying behavioral mechanisms remain poorly understood. We manipulated early-life social experience in the highly social African cichlid fish Astatotilapia burtoni to investigate the effects on behavior and stress axis function in juveniles. Juveniles experienced different numbers of social partners in stable pairs (1 partner), stable groups (6 fish; 5 partners), and socialized pairs (a novel fish was exchanged every 5 days; 5 partners). Treatments also differed in group size (groups vs. pairs) and stability (stable vs. socialized). We then measured individual behavior and water-borne cortisol to identify effects of early-life experience. We found treatment differences in behavior across all assays: open field exploration, social cue investigation, dominant behavior, and subordinate behavior. Treatment did not affect cortisol. Principal components (PC) analysis revealed robust co-variation of behavior across contexts, including with cortisol, to form behavioral syndromes sensitive to early-life social experience. PC1 (25.1 %) differed by social partner number: juveniles with more partners (groups and socialized pairs) were more exploratory during the social cue investigation, spent less time in the territory, and were more interactive as dominants. PC5 (8.5 %) differed by stability: socialized pairs were more dominant, spent less time in and around the territory, were more socially investigative, and had lower cortisol than stable groups or pairs. Observations of the home tanks provided insights into the social experiences that may underlie these effects. These results contribute to our understanding of how early-life social experiences are accrued and exert strong, lasting effects on phenotype.</p>
Data of paper entitled "The Impact of Financial Influencers, Social Influencers, and FOMO Economy on the Decision-Making of Investment on Millennial Generation and Gen Z of Indonesia"
<p>The repository contains:</p> <ol> <li>Result of inner model of PLS</li> <li>Result of outer model of PLS</li> <li>Questionnaire result</li> </ol>
Activational and organizational effects of testosterone on the number of mating partners and reproductive success in males of a social rodent
<p>The timing of exposure to the steroid hormone, testosterone, produces activational and organizational effects in vertebrates. These activational and organizational effects are hypothesized to relate with the number of female mating partners and reproductive success in males. We tested this hypothesis by examining 151 wild degu (<em>Octodon degus</em>) males across a 10-year study. We quantified the association between adult serum testosterone levels (i.e., an indirect index of adult activational effects) and anogenital distance (AGD) length (i.e., a direct index of fetal organizational effects), and their interaction on the number of female mating partners and reproductive success. We found no evidence of an association between adult male serum testosterone levels and the number of female mating partners, or between adult male serum testosterone levels and reproductive success. However, male AGD was positively associated with reproductive success, but not so with the number of female mating partners. Additionally, the positive association between male AGD and male reproductive success was mediated by the number of mates. Our findings do not support major roles of activational or organizational effects of testosterone on the number of female mating partners and its consequences on male reproductive success. Instead, our results suggest that compared with individual male attributes, the female social environment plays a more important role in driving male reproductive success.</p>
Social selection analysis reveals limited effect of neighbors' traits in Tree swallows
<p>Social interactions are ubiquitous in nature and can shape fitness of individuals through social selection. This type of selection arises when phenotypes of neighbors influence the fitness of a focal individual. Quantifying social selection is crucial to better characterise the overall selective landscape. For example, if intraspecific competition is strong, traits that are beneficial for an individual could be detrimental for competitors. In this study, we quantified social selection acting on four key ecological traits (body mass, wing length, laying date and clutch size) in wild Tree swallow (<em>Tachycineta bicolor)</em> females. We used reproductive success measured at three stages throughout the breeding season as fitness proxies to assess selection acting at those decisive moments. We also quantified the effects of environment on selection using measures of conspecifics' density, type of agricultural landscape and presence of interspecific competitors. Overall, we found no strong evidence of social selection on these traits in our study system, although there were marginally non-significant selection gradients suggesting positive effect of larger neighbors. Environmental variables affected reproductive success but did not affect social selection gradients. Our study calls for more social selection estimates to be reported across environments to better understand its importance in wild populations.</p>
"Unlocking the Urban Code. Digital Social Innovation and City Spaces"
<p>DSI in the City is a project funded by MUR-PRIN 2022 led by Chiara Certomà (PI, University Sapienza Rome) and Venere Sanna (University of Siena). The video explore one of the main challenges for contemporary society, i.e. understand and govern the digital revolution and its sociopolitical consequences.The video identifies and deconstructs the principal issues determined by the digitalisation of urban reproduction processes, notably via the diffusion of DSI practices.</p> <p> </p> <p>The project has been funded by the PRIN2022 MUR program, Funded by the European Commission - Next Generation EU, code 2022KTEZPX to the University Sapienza Rome</p>
Fig. 1 in A formiga parasita social Formicoxenus nitidulus (Nylander, 1846) en Galicia, NO Iberia (Hymenoptera: Formicidae).
Fig. 1.- Obreira (abaixo) e intercasta (enriba) de F. nitidulus de Montemeá (Guitiriz, Lugo).
Human Microbiome Action - Social Media Templates
<p>This comprehensive resource pack includes ready-to-use messages in PNG format and versatile templates for Twitter/X, LinkedIn, and Instagram available as PowerPoint files. Designed to streamline your communication efforts, these templates enable you to effectively share the latest advancements and insights in human microbiome research with your audience.</p>
Medical Concept Normalization in Social Media Posts with Recurrent Neural Networks
<p>Text mining of scientific libraries and social media has already proven itself as a reliable tool for<br> drug repurposing and hypothesis generation. The task of mapping a disease mention to a concept<br> in a controlled vocabulary, typically to the standard thesaurus in the Unified Medical Language<br> System (UMLS), is known as medical concept normalization. This task is challenging due to the<br> differences in medical terminology between health care professionals and social media texts coming<br> from the lay public. To bridge this gap, we use sequence learning with recurrent neural networks<br> and semantic representation of one- or multi-word expressions: we develop end-to-end architectures<br> directly tailored to the task, including bidirectional Long Short-Term Memory and Gated Recurrent<br> Units with an attention mechanism and additional semantic similarity features based on UMLS.<br> Our evaluation over a standard benchmark shows that recurrent neural networks improve results<br> over an effective baseline for classification based on convolutional neural networks. A qualitative<br> examination of mentions discovered in a dataset of user reviews collected from popular online health<br> information platforms as well as quantitative evaluation both show improvements in the semantic<br> representation of health-related expressions in social media.</p>
Emotions of Social Eating for People with Selective Eating Habits (ESE1)
<p><strong><em>Emotions of Social Eating for </em></strong><strong><em>People with Selective Eating Habits (ESE1) data set</em></strong></p> <p> </p>
Is there a social life in Open Data? Open datasets exploring practices in Educational Technology Research
<p>In the landscape of Open Science, Open Data [OD] plays a crucial role as data are one of the most basic components of research despite their diverse formats across scientific disciplines. Opening up data is a recent concern for policy makers and researchers as the basis for good open science practices. The common factor underlying these new practices – the relevance of promoting open data circulation and reuse – is mostly a social form of knowledge sharing and construction. However, while data sharing is being strongly promoted by policy making and is becoming a frequent practice in some disciplinary fields, open data sharing is much less developed in social sciences and in educational research.</p> <p>The Open Data hereby introduced is composed of two integrated datasets which collect data relating practices of Open Data publication and sharing in the field of Educational Thecnologies. This data was collected to suport the aim of investigating open data sharing in a selection of open data repositories as well as in the academic social network site ResearchGate.</p> <p>The research questions addressing this study are:</p> <ol> <li>Do researchers in the field of Educational Technology publish Open Datasets [ODs]?</li> <li>To which extent are ODs compliant with the FAIR data principles?</li> <li>What is the social life relating to the ODs in terms of the metrics provided by the OD portals? As a subsidiary question: 3.a- To what extent do open data portals allow researchers to cultivate social practices around OD?</li> </ol> <p> </p> <p>In order to investigate OD presence in ResearchGate, the following research aim guided the second part of the study: Analysis of the presence of the same selected OD in ResearchGate and of the type of social activity OD exhibited by OD according to ResearchGate mètrics.</p> <p>The Open Data here presented is composed by two datasets.</p> <ol> <li>23 datasets extracted out from 82 randomly selected datasets, from an inital total of 633. The data set presents a Codebook explaining the several categories of analysis or variables and the values assigned to the same. Since the analysis was performed in two phases (first selection and screening, second selection and classification) the codebook is divided in two tables. Moreover, the data set contains 6 Worksheets, ordered taking the workflow as reference: Codebook, Dataset_Extraction, Analysis_Workflow, Selected_Analysis. This dataset has been produced and curated by J.E.Raffaghelli</li> <li>The analysis of correspondance for the 23 datasets in ResearchGate. The data set presents a Codebook, and is divided into two worksheets: Codebook, ODT&RG. The last worksheet introduces the comparison between the social mètrics within RG of the found datasets and the relating papers. This dataset has been produced and curated by S. Manca and J.E. Raffaghelli.</li> </ol>
Data for : Social equity shapes zone-selection: Balancing aquatic biodiversity conservation and ecosystem services delivery in the transboundary Danube River Basin
<p>Freshwater biodiversity is declining, despite national and international efforts to manage and protect <a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/freshwater-ecosystem">freshwater ecosystems</a>. Ecosystem-based management (EBM) has been proposed as an approach that could more efficiently and adaptively <a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/ecological-balance">balance ecological</a> and societal needs. However, this raises the question of how social and ecological objectives can be included in an <a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/integrated-management">integrated management</a> plan. Here, we present a generic model-coupling framework tailored to address this question for freshwater ecosystems, using three components: biodiversity, ecosystem services (ESS), and a spatial prioritisation that aims to balance the spatial representation of biodiversity and <a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/evolutionarily-stable-strategy">ESS</a> supply and demand. We illustrate this model-coupling approach within the Danube River Basin using the spatially explicit, potential distribution of (i) 85 fish species as a surrogate for biodiversity as modelled using hierarchical Bayesian models, and (ii) four estimated ESS layers produced by the <a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/artificial-intelligence">Artificial Intelligence</a> for Ecosystem Services (ARIES) platform (with ESS supply defined as <a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/carbon-sequestration">carbon storage</a> and flood regulation, and demand specified as recreation and water use). These are then used for (iii) a joint spatial prioritisation of biodiversity and ESS employing Marxan with Zones, laying out the spatial representation of multiple management zones. Given the transboundary setting of the Danube River Basin, we also run comparative analyses including the country-level <a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/purchasing-power-parity">purchasing power parity</a> (PPP)-adjusted gross domestic product (GDP) and each country's percent cover of the total basin area as potential cost factors, illustrating a scheme for balancing the share of establishing specific zones among countries. We demonstrate how emphasizing various biodiversity or ESS targets in an EBM model-coupling framework can be used to cost-effectively test various spatially explicit management options across a multi-national case study. We further discuss possible limitations, future developments, and requirements for effectively managing a balance between biodiversity and ESS supply and demand in freshwater ecosystems.</p>
The futures of 193 Popular Financial Reporting of Awards Program 2017 and social economic elements
<p>Dataset The futures of 193 Popular Financial Reporting of Awards Program 2017 and social economic elements</p>
The social life of algae
<p>animated movie produced in the course of the ALFF project</p>
Russian social contact data relative to reactive school closure policies
<p>The dataset consists of individual contact diaries collected in Tomsk, Russia, in 2016. The dataset contains contact information for both for regular school/work days and for days when classes/schools are closed as a consequence of a reactive school closure strategy.<br> <br> This record consists of the dataset associated with M. Litvinova, Q.-H. Liu, E. S. Kulikov, M. Ajelli, Reactive school closure weakens the network of social interactions and reduces the spread of influenza. PNAS, 116(27):13174-13181, 2019.</p>
ENGLISH Participation in a new group and the identification processes: The quest for a positive social identity
<p>Dataset for manuscript Participation in a new group and the identification processes: The quest for a positive social identity</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.