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5,530 results for “informal”
Utilizing Digital Information for Personalized Cholesterol Management
<p><span>Patients with diseases due to high cholesterol levels in Indonesia can be said to be high because, in 2022, sufferers of the disease reached 28%, with 7.9% of people dying. The problem in this study is the need for more understanding, awareness, and ability of the community to manage and maintain cholesterol through digital information, especially social media. This research uses a questionnaire to understand the community's needs and supporting factors in digitally managing cholesterol through social media. This research gathered data using purposive sampling through a Google Form questionnaire. The data collection was conducted in April 2024 in various cities in Indonesia and successfully collected 221 responses. The method used to analyze the data in this study is the Structural Equation Model (SEM) using Smart Partial Least Square (Smart-PLS) 4.0 as the analysis approach. In this study, there are ten variables with five indicators each, and there are 11 hypotheses. The outcomes of this study show that all of the indicators were valid and reliable, with all hypotheses having a significant effect. Indonesian people must be able to utilize digital information to increase knowledge and understanding about health, especially about Cholesterol Management, so that the number of people affected by disease and who die from cholesterol can be reduced.</span></p>
Supporting Information for "Photothermal Laser Printing of Sub-micrometer Crystalline ZnO Structures"
<p>Supplementary information for the article <strong>"Photothermal Laser Printing of Sub-micrometer Crystalline ZnO Structures"</strong></p> <p>containing a video SEM-EBSD video of the rotating ZnO crystalline angles (mp4 file), raw and processed data of EDX and EBSD files (.bcf), raw and processed SEM and TEM images (.tif .emi .ser), processed images and plots (.svg .png .pdf), and evaluated data results (.txt .csv) .</p> <p> </p> <p>Link to publication: <a href="https://doi.org/10.1002/advs.202410771">https://doi.org/10.1002/advs.202410771</a></p> <p> </p> <p>An explanation of the data files can be found in the <em>Notes.docx </em>document</p>
Supporting Information for Automated and Efficient Sampling of Chemical Reaction Space
<p>These datasets include structures from normal mode sampling, reaction pathway sampling, and transition states for validation (originally from Grambow et al.), all computed using the ωB97X/6-31G(d) method. The corresponding energies and forces are compiled in the Atomic Simulation Environment database format. </p>
Data for "Information sharing within a social network is key to behavioral flexibility – lessons from mice tested under semi-naturalistic conditions"
<p>Data for "Information sharing within a social network is key to behavioral flexibility – lessons from mice tested under semi-naturalistic conditions", currently under review in Science Advances. </p>
Project files provided as supporting information to the manuscript "How Communication Pathways Bridge Local and Global Conformations in an IgG4 Antibody: a Molecular Dynamics Study"
<p>June 23, 2021</p> <p>Thomas Tarenzi, Marta Rigoli and Raffaello Potestio</p> <p>==================================</p> <p>The dataset contains the following folders:</p> <p>- contact_area_binding_site: files with the computed surface area, used for the calculation of the contact area between PD-1 and the antibody Fab (Fig. S41).</p> <p>- hbonds_ab-pd1: number of hydrogen bonds between the antigen and the antibody, for each holo cluster (Fig. S41).</p> <p>- mutual_information: matrices with the computed mutual information, for each pair of residues (Fig. S34, S35, S46). The folder contains also the generalized correlation coefficients (Fig. S43) and the correlation scores (Fig. 4, S44, S45), computed from the mutual informations.</p> <p>- networks: communities - for each cluster, each residue is assigned to a community within the interaction network (Fig. S32, S33). betweenness - the values of edge betweenness for each cluster (S30, S31).</p> <p>- output_clustering: each frame of the apo and holo simulations is assigned a cluster index, on the basis of the structural similarity (Fig. S4).</p> <p>- PAD: per-residue values of PAD parameter, for apo and holo systems (Fig. 3, S39).</p> <p>- PCA: principal component analysis for each conformational cluster (Section S2.1).</p> <p>- representative_structures: representative structures for each conformational cluster (Fig. 2).</p> <p>- r_gyr_antibody: radii of gyration of the antibody, for each cluster (Fig. 2).</p> <p>- r_gyr_hinge: radii of gyration of the sole hinge segment, for each cluster (Fig. S36).</p> <p>- RMSD_antibody: distributions of the root-mean-square deviation of the antibody, for each cluster (Fig. S5). </p> <p>- RMSD_antigen: root-mean-square deviation of the antigen PD-1, for each cluster (Fig. S42).</p> <p>- RMSD_binding_site: distributions of the root-mean-square deviation of the residues belonging to the paratope, for each cluster (Fig. S40, S47).</p> <p>- RMSD_matrix: root-mean-square deviation between structures belonging to different pairs of clusters (Fig. S9).</p> <p>- rmsf_antigen: root-mean-square fluctuation of the antigen PD-1, for each cluster (Fig. S42).</p> <p>- rmsf_hinge: difference between the total root-mean-square fluctuations of the two hinge segments, for each cluster (Fig. S38).</p> <p>- salt_bridge: distribution of distances between residues R979 and D1377 (Fig. 4).</p> <p>- sasa_domains: contact area between Fab and Fc antibody domains, for each cluster (Fig. S8).</p> <p>- sasa_hinge: solvent accessible surface area of each hinge segment, for each cluster (Fig. S37).</p>
Modality-specific dysfunctional neural processing of social-abstract and non-social-concrete information in schizophrenia
<p>Schizophrenia is characterized by marked communication dysfunctions encompassing potential impairments in the processing of social-abstract and non-social-concrete information, especially in everyday situations where multiple modalities are present in the form of speech and gesture. To date, the neurobiological basis of these deficits remains elusive. In a functional magnetic resonance imaging (fMRI) study, 17 patients with schizophrenia or schizoaffective disorder, and 18 matched controls watched videos of an actor speaking, gesturing (unimodal), and both speaking and gesturing (bimodal) about social or non-social events in a naturalistic way. Participants were asked to judge whether each video contains person-related (social) or object-related (non-social) information. When processing social-abstract content, patients showed reduced activation in the medial prefrontal cortex (mPFC) only in the gesture but not in the speech condition. For non-social-concrete content, remarkably, reduced neural activation for patients in the left postcentral gyrus and the right insula was observed only in the speech condition. Moreover, in the bimodal conditions, patients displayed improved task performance and comparable activation to controls in both social and non-social content. To conclude, patients with schizophrenia displayed modality-specific aberrant neural processing of social and non-social information, which is not present for the bimodal conditions. This finding provides novel insights into dysfunctional multimodal communication in schizophrenia, and may have potential therapeutic implications.</p>
Prior information for scMLnet
<p>Prior L-R-TF-genes information for the tutorial of scMLnet, downloaded from <a href="https://github.com/SunXQlab/scMLnet">https://github.com/SunXQlab/scMLnet</a></p>
Supplementary information for phylogenetic benchmarking study
<p>This dataset comprises the following files:</p> <p>- A tarball containing all alignments per run, used to infer phylogenies from (gzipped)</p> <p>- A tarball containing all assemblies (where applicable) per run (gzipped)</p> <p>- Several files with final results of the analyses. These can be read directly into SuperPlotsOfData to obtain the plots in our paper. RF = Robinson Foulds distance, KC = Kendall Colijn metric. L_0, L_0.5 and L_1 indicate lambda values of 0, 0.5 and 1 respectively in the calculation of the Kendall Colijn metric. full_data.csv contains all data. full_data_nomlst.csv contains all data, excluding the runs employing MLST alignment. run_differences_absolute.csv contains absolute differences between identical runs.</p>
HeSANDA Design Phase information session
<p>This information session provides an introduction to the HeSANDA program, an overview of the Design Phase, and information for attendees about how they can be involved.</p> <p>You can watch the video on ARDC's YouTube channel: <a href="https://youtu.be/VROOXwUf9lI">https://youtu.be/VROOXwUf9lI</a></p>
Additional climate information for research paper «Ecological and Geographical Analysis of Distribution of Heracleum persicum, H. mantegazzianum and H. sosnowskyi on The Northern Limit of Its Invaded Range in Europe» submitted to Russian Journal of Biological Invasions
<p><strong>Additional climate information for research paper «Ecological and Geographical Analysis of Distribution of Heracleum persicum, H. mantegazzianum and H. sosnowskyi on The Northern Limit of Its Invaded Range in Europe» submitted to Russian Journal of Biological Invasions </strong></p>
BIOPLAT-EU: Target Area Base Layer providing statistical information on demography, employment and land use for sustainability assessment
<p>This dataset provides information on demographic variables related to population and employment as well as land use/land cover share on the basis of local administrative units (LAU). Within the BIOPLAT-EU project, this information is integrated into the webGIS sustainability assessment tool.<br> Main source of the administrative unit geometries is the spatial data set of local administrative units (LAU) (2016) provided by the European Commission (https://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/administrative-units-statistical-units/lau#lau19). The data set was extended by Level 2 administrative boundaries of Albania (https://data.humdata.org/dataset/albania-administrative-level-0-3-boundaries) and Level 3 administrative boundaries of Ukraine as of 2017 (https://data.humdata.org/m/dataset/ukraine-administrative-boundaries-as-of-q2-2017?force_layout=light)</p> <p>Data on demography (2016) for LAU + Albania was acquired using the Eurostat statistical database (https://ec.europa.eu/eurostat/web/main/data/database). To calculate land use share for LAU and Albania, Corine Land cover (CLC) data from 2018 was used (https://land.copernicus.eu/pan-european/corine-land-cover). CLC classes were summarized into the following classes: urban areas (UrAr), forest (Fo), permanent crops (PeCr), annual crops (AnCr), permanent meadows and pastures (PeMaPa), industrial sites (InSi), water and wetlands (We), others (Ot).</p> <p>For Ukraine data on demography provided by the State Statistics Survey of Ukraine (http://www.ukrstat.gov.ua/) . To calculate land use share per administrative unit, the land use map produced by Myroniuk et al. 2020 (https://doi.org/10.3390/rs12010187) was used. Based to this map shares of the following land use classes are calculated: urban areas (UrAr), forest (Fo), annual and permanent cropland (AnPeCr), grassland (Gra), water and wetlands (We), others (Ot).</p> <p> </p> <p><em><strong>Terms of use:</strong></em> These data are provided "as is". <em>The authors make <strong>no </strong></em><strong><em>warranty</em></strong><em>, representation, or guaranty of any type as to the completeness, accuracy, content or fitness for any particular purpose or use of any </em><strong><em>open data</em></strong><em> set made available here</em><em>, nor shall any </em><strong><em>warranties</em></strong><em> be implied with respec</em><em>t to the data provided.</em></p>
Plant species as the bear cuscus diet based on information from local guides
<p>The table contains information about the plant species as the bear cuscus diet in Bantimurung Bulusaraung National Park (BBNP) and Hasanuddin University Educational Forest (HUEF), South Sulawesi based on information from the local guides, as well as the part(s) of plants eaten.</p>
Supplementary Information for Phylogenetic analyses of ray-finned fishes (Actinopterygii) using collagen type I protein sequences
<p>Ray-finned fishes (Actinopterygii) are the largest and most diverse group of vertebrates, comprising over half of all living vertebrate species. Phylogenetic relationships between ray-finned fishes have historically pivoted on the study of morphology, which has notoriously failed to resolve higher-order relationships, such as within the percomorphs. More recently, comprehensive genomic analyses have provided further resolution of actinopterygian phylogeny, including higher-order relationships. Such analyses are rightfully regarded as the 'gold standard' for phylogenetics. However, DNA retrieval requires modern or well-preserved tissue and is less likely to be preserved in archaeological or fossil specimens. In contrast some proteins, such as collagen, are phylogenetically informative and can survive into deep time. Here, we test the utility of collagen type I amino acid sequences for phylogenetic estimation of ray-finned fishes. We estimate topology using Bayesian approaches and compare the congruence of our estimated trees with published genomic phylogenies. Furthermore, we apply a Bayesian molecular clock approach and compare estimated divergence dates with previously published genomic clock analyses. Our collagen-derived trees exhibit 77% of node positions as congruent with recent genomic-derived trees, with the majority of discrepancies occurring in higher-order node positions, almost exclusively within the Percomorpha. Our molecular clock trees present divergence times that are fairly comparable with genomic-based phylogenetic analyses. We estimate the mean node age of Actinopteri at ~293 million years (Ma), the base of Teleostei at ~211 Ma and the radiation of percomorphs beginning at ~141 Ma (~350 Ma, ~250–283 Ma and ~120–133 Ma in genomic trees, respectively). Finally, we show that the average rate of collagen (I) sequence evolution is 0.9 amino acid substitutions for every million years of divergence, with the α3 (I) sequence evolving the fastest, followed by the α2 (I) chain. This is the quickest rate known for any vertebrate group. We demonstrate that phylogenetic analyses using collagen type I amino acid sequences generate tangible signals for actinopterygians that are highly congruent with recent genomic-level studies. However, there is limited congruence within percomorphs, perhaps due to clade-specific functional constraints acting upon collagen sequences. Our results provide important insights for future phylogenetic analyses incorporating extinct actinopterygian species via collagen (I) sequencing.</p>
A Pragmatic Trial of Interactive Online Statistical Webtools for Teaching Biostatistics to First Year Medical Students: A Constructivism-Informed Approach
<p>Underlying quantitative and anonymised qualitative data for the study, "A Pragmatic Trial of Interactive Online Statistical Tools for Teaching Biostatistics to First Year Medical Students: A Constructivism-Informed Approach"</p>
Supplemental information for: Annual tropical-rainforest productivity through two decades: Complex responses to climatic factors, CO2 and storm damage
<p>The supplemental files in this deposition contribute additional information useful for understanding the analyses in the associated manuscript. Two files contain the annual (CARBONO Project measurement-year) data for productivity and for environmental conditions that were analyzed in the paper. The annual productivity metrics were derived from the CARBONO Project litterfall and tree-growth data that were provided and documented in prior Dryad data depositions. A third file in this deposition provides the daily data underlying the analyzed meteorological factors. The fourth file lists the standardized set of 66 test models that were used to test each of the five productivity metrics for environmental responses. The fifth file is an auxiliary table documenting tree mortality by year. The included README file documents the information in these files.</p>
DATA ON HYGIENIC KNOWLEDGE AND PRACTICES OF MILK VENDING MACHINE HANDLERS IN THE INFORMAL SETTLEMENTS OF NAIROBI KENYA
<p>Data used in the research development on hygienic knowledge and practices of handlers in the informal settlements of Nairobi. </p>
Samples information and datasets list
<p>Samples information and dataset lists, including <em>dataset stru, stru-same, cp_family, cp_genus, cp_species, cp_samples</em>.</p>
Supplementary Information for Consonance-emerging Hebbian Learning neural network model predicts discreteness of musical scales and the Natural Just Intonation scale
<p><strong>The following phenomena and features are apparent in music and auditory perception in general: the discreteness of the tones in musical scales</strong> [1]<strong>, the prevalence of the tonal frequency span of one semitone (100 cents) in musical scales across cultures </strong>[1]<strong>, the list of tonal intervals ordered by consonance [2], and the musical performers’ preference of the Natural Just-Intonation scale [3] (A). However, researchers still have no agreement about the causes and the emergence of said phenomena (A). Here we show that the consonance-pattern emerging neural network model introduced in our previous study [4], predicts and yields all the said phenomena (A) with a precision of 1/100<sup>th</sup> of a semitone (1 cent). This precision is beyond the resolution of human hearing </strong>[5], [6], [7]. <strong>Since the Hebbian learning paradigm and harmonicity are the main features of our model, we propose that they are sufficient conditions for any system to yield the said phenomena (A). Therefore, they have a crucial role in processing pitch, consonance, and music perception in general. As a consequence, we additionally propose that the mentioned phenomena (A) are a balanced result of the joint workings of the Hebbian paradigm (nurture and cultural exposure) and harmonicity (auditory physics and biology).</strong></p>
Data from: Cerebellar complex spikes multiplex complementary behavioral information
<p><span>Purkinje<b> </b>cell (PC) discharge, the only output of cerebellar cortex, involves two types of action potentials, high-frequency simple spikes (SSs) and low-frequency complex spikes (CSs). While there is consensus that SSs convey information needed to optimize movement kinematics, the function of CSs, determined by the PC´s climbing fibre input, remains controversial. While initially thought to be specialized in reporting information on motor error for the subsequent amendment of behavior, CSs seem to contribute to other aspects of motor behavior as well. When faced with the bewildering diversity of findings and views unraveled by highly specific tasks one may wonder if there is just one true function with all the other attributions wrong? Or is the diversity of findings a reflection of distinct pools of PCs, each processing specific streams of information conveyed by climbing fibres? With these questions in mind, we recorded CSs from the monkey oculomotor vermis deploying a repetitive saccade task that entailed sizable motor errors as well as small amplitude saccades, correcting them. We demonstrate that in addition to carrying error-related information, CSs carry information on the metrics of both primary and small corrective saccades in a time-specific manner, with changes in CS firing probability coupled with changes in CS duration. Furthermore, we also found CS activity that seemed to predict the upcoming events. </span>Hence PCs receive a multiplexed climbing fibre input that merges complementary streams of information on the behavior, separable by the recipient PC because they are staggered in time.</p>
Observational Data for: Polarized information ecosystems can reorganize social networks via information cascades
<p><strong>General Information</strong></p> <p>This contains the observational data for the publication:</p> <blockquote> <p>Tokita, Guess, and Tarnita (2021). Polarized information ecosystems can reorganize social networks via information cascades. <em>Proceedings of the National Academies of Science of the United States.</em></p> </blockquote> <p>Please see the above peer-reviewed article that resulted from this data for more details.</p> <p>Please see the <em>o</em><em>bservational/ </em>directory in the Github repository <a href="http://%28https//github.com/christokita/information-cascades)">https://github.com/christokita/information-cascades</a> for the code that analyzes the Twitter data and generates derived data. Data directly pertaining to the four news sources of interest are in the <em>data/</em> directory, while data that is related to the 4,000 monitored news followers are in the <em>data_derived/</em> directory.</p> <p>The main data file is in a zipped file. We also included a read me with a description of each directory and subdirectory of the data.</p> <p><strong>Methods</strong></p> <p>For each of our four news sources of interest (CBS News, USA Today, Vox, and the Washington Examiner), we used the Twitter API to sample 3,000 random Twitter users that followed that news source's account. We then used the <em>tweetscores</em> R package to estimate the ideology of each of the 12,000 sampled users.</p> <p>From the original pool of approximately 12,000 sampled users who follow a news outlet of interest, we monitored the follower networks of 1,000 liberal followers of CBS News, 1,000 conservative followers of USA Today, 1,000 liberal followers of Vox, and 1,000 conservative followers of the Washington Examiner. When selecting the 1,000 random users to monitor for a given news outlet, we first conducted filters based on self-reported geolocation and other Twitter profile attributes to reasonably filter down to US-based users who primarily tweet in English. We then pulled the complete follower network of each of our 4,000 monitored users at the beginning and end of a 6-week period from August to September 2020, allowing us to assess who unfollowed these users over this period of time. Finally, using the initial follower networks of each monitored user, we estimated the ideology of up to 50 random followers to create a baseline for the ideological composition of each user’s follower network. </p> <p>Using the initial and final follower networks of each individual, we calculated the rate of unfollows by opposite-ideology users in their follower network. To determine whether an unfollow event was breaking a cross-ideology social tie, users and their unfollowers were classified simply as either liberal (ideology score < 0) or conservative (ideology score > 0). We excluded from analysis unfollowers for whom we could not estimate ideology, either because the account had been suspended, deleted, or made private, or because they did not follow any of the political, news, or cultural accounts needed to do the estimation. We then compared the proportion of unfollowers that were of the opposite ideology (i.e., conservative unfollowers if the focal user is liberal) against the estimated proportion of opposite-ideology followers in the focal user’s initial follower network. This allowed us to account for the fact that many user’s follower networks were not ideologically balanced and set the baseline expectation that if unfollows were random then the proportion of unfollows by opposite-ideology users should match the proportion of followers that were of the opposite ideology.</p> <p> </p> <p><strong>Abstract (for main paper)</strong></p> <p>The precise mechanisms by which the information ecosystem polarizes society remain elusive. Focusing on political sorting in networks, we develop a computational model that examines how social network structure changes when individuals participate in information cascades, evaluate their behavior, and potentially rewire their connections to others as a result. Individuals follow proattitudinal information sources but are more likely to first hear and react to news shared by their social ties and only later evaluate these reactions by direct reference to the coverage of their preferred source. Reactions to news spread through the network via a complex contagion. Following a cascade, individuals who determine that their participation was driven by a subjectively “unimportant” story adjust their social ties to avoid being misled in the future. In our model, this dynamic leads social networks to politically sort when news outlets differentially report on the same topic, even when individuals do not know others’ political identities. Observational follow network data collected on Twitter support this prediction:We find that individuals in more polarized information ecosystems lose cross-ideology social ties at a rate that is higher than predicted by chance. Importantly, our model reveals that these emergent polarized networks are less efficient at diffusing information: Individuals avoid what they believe to be “unimportant” news at the expense of missing out on subjectively “important” news far more frequently. This suggests that “echo chambers”—to the extent that they exist—may not echo so much as silence.</p>
ScienceDex guides
Understand access before you commit
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.