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2,820 results for “Physical Activity”
Physical soil characteristics, microbial community composition, extracellular enzymatic activity, biologically based phosphorus (BBP) pools, and available phosphorus from two soil depths, four microhabitats, and four landforms at the Jornada Experimental Range, 2021.
This dataset contains physical soil characteristics, PLFA based microbial community composition, extracellular enzymatic activity, nitrate and ammonium activity, and phosphorus availability in various phosphorus pools (Biologically Based Phosphorus, potassium sulfate, Olsen-P). Soils were collected from two depths (0-2cm, 2-30 cm), four microhabitats (grass, shrub, biocrust, interspace), and four landforms (alluvial flat, alluvial fan remnant, erosional scarplet, fan piedmont – see coordinates) within the Jornada Experimental Range in July 2021 to answer questions about how these variables change across these spatial scales in drylands. This project was a collaboration between researchers at New Mexico State University and The University of Texas at El Paso as part of the Drylands Critical Zone Thematic Cluster within the Critical Zone Network. This dataset is complete.
A longitudinal study of the associations of children's body mass index and physical activity with blood pressure – dataset
<p>B-Proact1v is a longitudinal study examining changes in children’s physical activity and sedentary behaviours as they progress through primary school. In 2012-2013, 1299 Year 1 children (median age: 6 years) were recruited from 57 schools in greater Bristol, UK (total number of eligible children: 2600; recruitment rate: 50.0%). Following this, data were collected from 1223 Year 4 children (median age: 9 years) from 47 of the original schools between March 2015 and July 2016 (total number of eligible children: 2047; recruitment rate: 59.7%). This included 685 children from the original sample.</p> <p> </p> <p>This dataset represents a subset of the B-Proact1v data to examine the longitudinal associations of children’s body mass index and physical activity with blood pressure. Included in this repository is the dataset and a data dictionary. The dataset includes the variables that underlie the findings in a manuscript entitled ‘A longitudinal study of the associations of children’s body mass index and physical activity with blood pressure’ that has been submitted to PLOS ONE. This dataset has been made available so that future researchers can replicate the study findings using the data. If you wish to use the data for any purpose other than replicating the study findings, please contact the Principal Investigator Professor Russ Jago (russ.jago@bristol.ac.uk) to discuss this.</p>
Gerational issues in linking family farming production, traditional food in diet, physical activity and obesity in Pacific Islands countries and territories: the case of the Melanesian population on Lifou Island
<p>In the Melanesian culture, traditional activities are organized around family farming, although the lifestyle transition taking place over the last several decades has led to imbalances in diet and physical activity, with both leading to obesity. The aim of this interdisciplinary study was to understand the links between family farming (produced, exchanged, sold, and consumed food), diet (focused on produced, hunted, and caught food), physical activity (sedentary, light, and moderate-to-vigorous physical activity) and obesity in Melanesian Lifou Island families (parents and children). Forty families, including 142 adults and children, completed individual food frequency questionnaires, wore tri-axial accelerometers for seven continuous days, and had weight and height measured with a bio-impedance device. Qualitative and quantitative interviews were conducted at the household level concerning family farming practices and sociodemographic variables. Multinomial regression analyses and logistic regression models were used to analyze the data. Results showed that family farming production brings a modest contribution to diet and active lifestyles for the family farmers of Lifou Island. The drivers for obesity in these tribal communities were linked to diet in the adults, whereas parental socioeconomic status and moderate-to-vigorous physical activity were the main factors associated to overweight and obesity in children. These differences in lifestyle behaviors within families suggest a transition in cultural practices at the intergenerational level. Future directions should consider seasonality and a more in-depth analysis of diet including macro- and micro- nutrients to acquire more accurate information on the intergenerational transition in cultural practices and its consequences on health outcomes in the Pacific region.</p>
Bonanza Creek moisture gradient physical data at BZBS: hourly temperature, moisture and photosynthetically active radiation.
This dataset contains the hourly output from temperature, moisture and PAR sensors at five unique vegetative sites at the Bonanza Creek moisture gradient. This data can be sorted and viewed by site, year, hour and depth of probe below surface. Data from each site within this transect will be update yearly. Start dates for the probes at each site vary depending on when they were installed.
Bonanza Creek moisture gradient physical data at BZWB: hourly temperature, moisture and photosynthetically active radiation.
This dataset contains the hourly output from temperature, moisture and PAR sensors at five unique vegetative sites at the Bonanza Creek moisture gradient. This data can be sorted and viewed by site, year, hour and depth of probe below surface. Data from each site within this transect will be update yearly. Start dates for the probes at each site vary depending on when they were installed.
Bonanza Creek moisture gradient physical data at BZTG: hourly temperature, moisture and photosynthetically active radiation.
This dataset contains the hourly output from temperature, moisture and PAR sensors at five unique vegetative sites at the Bonanza Creek moisture gradient. This data can be sorted and viewed by site, year, hour and depth of probe below surface. Data from each site within this transect will be update yearly. Start dates for the probes at each site vary depending on when they were installed.
Bonanza Creek moisture gradient physical data at BZEC: hourly temperature, moisture and photosynthetically active radiation.
This dataset contains the hourly output from temperature, moisture and PAR sensors at five unique vegetative sites at the Bonanza Creek moisture gradient. This data can be sorted and viewed by site, year, hour and depth of probe below surface. Data from each site within this transect will be update yearly. Start dates for the probes at each site vary depending on when they were installed.
Bonanza Creek moisture gradient physical data at BZDE: hourly temperature, moisture and photosynthetically active radiation.
This dataset contains the hourly output from temperature, moisture and PAR sensors at five unique vegetative sites at the Bonanza Creek moisture gradient. This data can be sorted and viewed by site, year, hour and depth of probe below surface. Data from each site within this transect will be update yearly. Start dates for the probes at each site vary depending on when they were installed.
Physical activities data
<p>This upload contains anonymized open data for physical activities.</p>
Apathy, motivation, and physical activity behavior: Material, data and R code
<p>This new release includes updates to the code and additional material following the peer review process conducted by Communications in Kinesiology.</p>
Overview of PASTA Questionnaires: Physical Activity through Sustainable Transport Approaches (PASTA): protocol for a multi-centre, longitudinal study
<p>Overview of questionnaires used in the PASTA project (Physical Activity through Sustainable Transport Approaches (PASTA))</p> <p>English version</p>
A comparison of the World Health Organisation's HEAT model results using a non-linear physical activity dose response function with results from the existing tool
<p>Datasets relating to the Wellcome Open Research publication of the same name.</p>
COVID-19, physical activity, and health
<p>Dataset related to the project on COVID-19, physical activity, and health</p> <p>This dataset includes:</p> <p><strong>1) A codebook (including the name of the main variables)</strong></p> <p>--> "code_book_covid.xlsx"</p> <p><strong>2) The anonymous data set</strong></p>
Dataset for the comparison of accelerometry-based and self-reported physical activity and their association with cardiovascular risk markers in children from South Africa
<p>Dataset used to evaluate and compare self-reported with accelerometry-based physical activity measurements as well as their associations with cardiovascular risk markers among South African school-aged children from disadvantaged communities.</p> <p>It encompasses anonymized, unique, identification numbers, demographic and body-mass-index, blood pressure, lipid panel and blood glucose measures.</p>
Data for "The Role of Mood and Stress in Physical Activity Engagement: Insights from Ecological Momentary Assessment
<p>Data collected in the SmartPA study in a joint effort from the Department of Psychology at the University of Salzburg (Jens Blechert) and the Ludwig Boltzmann Institute for Digital Health and Prevention Salzburg.</p>
Avoiding sedentary behaviors requires more cortical resources than avoiding physical activity
<p><strong>Dataset related to the paper entitled "Avoiding sedentary behaviors requires more cortical resources than avoiding physical activity". </strong></p> <p>This dataset includes:</p> <p>1) A workbook</p> <p>2) Raw data ("raw_data_eprime_zen.csv") of the behavioral outcomes of the manikin task</p> <p>3) Self-reported data ("data_self_report_R_subset_zen.csv").</p> <p>4) Electroencephalography data ("ERP_by_subject_by_condition_data.zip").</p> <p>5) R script for the data management of the behavioral outcomes (i.e., from the raw data to data ready to be analyzed)</p> <p>6) Images used in the manikin task</p> <p>7) Eprime script for the manikin task</p>
Physical stabilization of water-soluble PVA nanofibrous materials functionalized with biologically active substances
<p>Tissue engineering aims to develop materials that enhance biological activity and promote tissue healing and regeneration. One promising approach is to functionalize nanofibrous materials with antimicrobial substances, such as lipophosphonoxin (LPPO), and use water-soluble polymers like polyvinyl alcohol (PVA) to incorporate bioactive molecules into fibers. However, water-soluble materials often face the issue of "burst release," releasing over 90% of the active substances within the initial 24 hours. This research focuses on preparing functionalized nanofibrous materials based on PVA containing the experimental antimicrobial compound LPPO and subsequent physical stabilization of the materials using the "Heat treatment" method. The applied stabilization successfully reduced the incorporated substance's release rate by up to 50%. The resulting materials have the potential to provide functional cross-linked PVA nanofiber scaffolds for regenerative medicine applications in large and chronic skin injuries.</p>
Deep Representation Learning of Physical Activity and Sleep Patterns During Pregnancy Identifies post-hoc Inferences Associated with Prematurity
<p><strong>Running title</strong>: series2signal gestational age "clock" for pregnancy monitoring</p> <p><strong>Summary</strong>: </p> <p>Preterm birth (PTB) is the leading cause of infant mortality globally. While research has focused on the development of predictive models for PTB, cost-effective interventions have remained understudied. Physical activity and sleep present unique opportunities for interventions in low- and middle-income populations. However, objective measurement of physical activity and sleep remains challenging and self-reported metrics suffer from low-resolution and accuracy that decays over time. In this study, we use physical activity data collected using a wearable device comprising over 181, 944 hours of data across N = 1, 083 patients. Using a new state-of-the art deep learning time-series classification architecture, we first develop a ”clock” of healthy dynamics in physical activity patterns during pregnancy by using gestational age (GA) as a surrogate for progression of pregnancy. We also developed a novel interpretability algorithm that integrates unsupervised clustering, model error analysis, feature attribution, and automated actigraphy analysis, allowing for model interpretation with respect to sleep, activity, and static clinical variables. Our model performs significantly better than 7 other machine learning and AI methods for modeling the progression of pregnancy based on measures of physical activity and sleep.</p> <p>Importantly, we found that deviations from this normal ”clock” of physical activity and sleep changes during pregnancy are strongly associated with pregnancy outcomes. When our model underestimates GA, there are 0.52 fewer preterm births than expected (P = 1.01e − 67) and when our model overestimates GA, there are 1.44 times (P = 2.82e − 39) more preterm births than expected. Model error is negatively correlated with interdaily stability (P = 0.043), indicating that our model assigns a more advanced GA when an individual’s daily rhythms are less precise. Supporting this, our model attributes higher importance to sleep periods in predicting higher-than-actual GA, relative to lower-than-actual GA (P = 1.01e − 21). Combining prediction with interpretability allows us to robustly signal when activity behaviors increase or decrease the likelihood of preterm birth and advocates for the future development of clinical decision support through passive monitoring and suggestions around exercise habits and sleep patterns, which are easily implemented in low- and middle-income countries (LMICs). Beyond this particular application, the presented pipeline can be used to analyze high-fidelity time-series data in other translational studies utilizing wearable devices.</p> <p> </p> <p><strong>Data description (brief)</strong>: the raw wearables data is available as .mtn files with the GA encoded in the filename after the underscore. The processed data with sleep annotations can be loaded using the pickle module for serialized objects in python. See https://github.com/nealgravindra/wearables for examples.</p>
Dataset for the intervention effects and long-term changes in physical activity and cardiometabolic outcomes among children at risk of noncommunicable diseases in South Africa
<p>Dataset used to evaluate the short-term effects of the physical and health <em>KaziKidz</em> intervention on cardiometabolic risk factors and the long-term changes thereof among school-aged children at risk of NCDs from disadvantaged communities in South Africa.</p> <p>It encompasses anonymized, unique, identification numbers, anthropometric and clinical measures, such as blood pressure, blood sugar and blood lipids, and Actigraphy-measured physical activity levels. Assigned categories to each cardiovascular risk factor and the overall classification as at risk or not is available too.</p>
Comparison of children's physical activity profiles before and after COVID-19 lockdowns - dataset
<p>This dataset represents a subset of the Active-6 data used to produce the children's activity profiles reported in the manuscript 'Comparison of children's physical activity profiles before and after COVID-19 lockdowns: a latent profile analysis'. Included in this repository is the dataset and a data dictionary.</p> <p>This dataset has been made available so that future researchers can replicate the study findings using the data. If you wish to use the data for any purpose other than replicating the study findings, please contact the Principal Investigator Professor Russ Jago (russ.jago@bristol.ac.uk) to discuss this.</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
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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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.