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161 results for “proactivity”
Cooperative Proactive resource management for 5G in the unlicensed spectrum open data
<p>The data set consists of the following files:</p> <p><strong>1)COT information:</strong> The channel occupancy time of each channel for the first 5000 measurements. The COT values range from 0 to 1.</p> <p><strong>2)QL decisions uniform traffic:</strong> The decisions of QL for the channel utilization of the available SBS and their impact to the achieved throughput. In this file we consider uniform traffic generation patterns.</p> <p><strong>3)QL decisions NON uniform traffic:</strong> The decisions of QL for the channel utilization of the available SBS and their impact to the achieved throughput. In this file we consider non-uniform traffic generation patterns.</p> <p><strong>4)Performance measurements: </strong>The final results of the experiment in respect to the transmit power control and throughput measurements under different QL configurations.</p>
Proactive COVID-19 testing in a partially vaccinated population.
<p>Complete simulation-generated datasets analyzed in McGee et al. (2021) Proactive COVID-19 testing in a partially vaccinated population. medRxiv 2021.08.15.21262095.</p> <p>Data is uploaded in comma-separated .csv files which have been compressed using gzip. Descriptions of data columns can be found in the column_descriptions.csv file.</p>
Proactive notification to clients of Electric Utility Service in Brazil
<p>A Proactive Notification dataset used to predict the time that will be necessary to fix problems that interrupt the electric supply and identify the clients that potentially will contact the call center in cities of two states of Brazil. This dataset has historical data related to: Occurrence-Client-Complaint and Fail Occurrences.</p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p>
Proactive conservation to prevent habitat losses to agricultural expansion
<p>The projected loss of millions of square kilometres of natural ecosystems to meet future demand for food, animal feed, fibre, and bioenergy crops is likely to massively escalate threats to biodiversity. Reducing these threats requires a detailed knowledge of how and where they are likely to be most severe. We developed a geographically explicit model of future agricultural land clearance based on observed historic changes and combine the outputs with species-specific habitat preferences for 19,859 species of terrestrial vertebrates. We project that 87.7% of these species will lose habitat to agricultural expansion by 2050, with 1,280 species projected to lose ≥25% of their habitat. Proactive policies targeting how, where, and what food is produced could reduce these threats, with a combination of approaches potentially preventing almost all these losses while contributing to healthier human diets. As international biodiversity targets are set to be updated in 2021, these results highlight the importance of proactive efforts to safeguard biodiversity by reducing demand for agricultural land.</p>
Proactive Control Strategies for Overt and Covert Go/NoGo Tasks: an Electrical Neuroimaging Study
<p>ERPs dataset (15 subjects) for session A and session B preparatory phase (from 200 ms before cue onset to 1000 ms after cue onset).</p> <p>GSN Hydrocel Sensor Net 110 channels array is included.</p>
Proactive Conflict Detection for Collaborative Model-driven Software Engineering (Evaluation Data)
<p>Results of the evaluation for the paper "Proactive Conflict Detection for Collaborative Model-driven Software Engineering"</p>
Proactive conservation to prevent habitat losses to agricultural expansion
Open the record for dataset details and reuse information.
Data from: Impacts of proactive health management on cattle and horse diets and dung biodiversity in Danish rewilding areas
Open the record for dataset details and reuse information.
Energy consumption, execution time and fail requests rate of a proactive energy-aware auto-scaling solution for edge-based infrastructures applied to real-world workload.
<p>Spreadsheet of the results obtained with our horizontal auto-scaling proposal presented in "A proactive energy-aware auto-scaling solution for edge-based infrastructures". In that research, we present a proactive horizontal auto-scaling framework for edge infrastructures, which considers both the base (idle) and dynamic (due to application execution) energy consumption of edge nodes and the node scaling mechanism. Simulations were performed with the EdgeCloudSim simulator with a workload provided by Shanghai Telecom and the results show up to a 92.5% decrease in energy consumption, a failed request rate of up to 0%, and reasonable execution times of the auto-scaling process for different problem sizes.</p> <p>Proactive auto-scaling mechanisms in edge-based infrastructures can anticipate user service requests by allocating computing resources while supporting the quality of service needed by a vast range of applications requiring, e.g., a low latency or response time. </p> <p>This work is supported by the European Union's H2020 research and innovation program under grant agreement DAEMON 101017109 and by the projects co-financed by FEDER funds LEIA UMA18-FEDERJA-15, MEDEA RTI2018-099213-B-I00 (MCI/AEI) and RHEA P18-FR-1081.</p>
Proactive management outperforms reactive actions for wildlife disease control
<p>Finding effective pathogen mitigation strategies is one of the biggest challenges humans face today. In the context of wildlife, emerging infectious diseases have repeatedly caused widespread host morbidity and population declines of numerous taxa. In areas yet unaffected by a pathogen, a proactive management approach has the potential to minimize or prevent host mortality. However, we typically lack critical information on the disease dynamics in a novel host system, have limited empirical evidence on efficacy of management interventions, and lack validated predictive models. As such, quantitative support for identifying effective management interventions is largely absent, and the opportunity for proactive management is often missed. Here, we consider the potential invasion of the chytrid fungus, <em>Batrachochytrium salamandrivorans</em>, whose expected emergence in North America poses a severe threat to hundreds of salamander species in this global salamander biodiversity hotspot. We developed and parameterized a dynamic multi-state occupancy model to forecast host and pathogen occurrence, following expected emergence of the pathogen, and evaluated the response of salamander populations to different management scenarios. Our model forecasts that taking no action is expected to be catastrophic to salamander populations. We also show that proactive action is expected to maximize host occupancy outcomes compared to 'wait and see' reactive management, thus providing quantitative support for proactive management opportunities. Additionally, we found that Bsal eradication is unlikely under any evaluated management options. Contrary to our expectations, even early pathogen detection had little effect on Bsal or host occupancy outcomes. Our analysis provides quantitative support that proactive management is the optimal strategy for promoting persistence of disease-threatened salamander populations. Our approach fills a critical gap by defining a framework for evaluating management options prior to pathogen invasion and can thus serve as a template for addressing novel disease threats that jeopardize wildlife and human health.</p>
Data from: Proactive cursorial and ambush predation risk avoidance in four African herbivore species
<p>Most herbivores must balance demands to meet nutritional requirements, maintain stable thermoregulation and avoid predation. Species-specific predator and prey characteristics determine the ability of prey to avoid predation and the ability of predators to maximise hunting success. Using GPS collar data from African wild dogs, lions, impala, tsessebe, wildebeest and zebra in the Okavango Delta, Botswana, we studied proactive predation risk avoidance by herbivores. We considered predator activity level in relation to prey movement, predator and prey habitat selection, and preferential use of areas by prey. We compared herbivore behaviour to lion and wild dog activity patterns and determined the effect of seasonal resource availability and prey body mass on anti-predator behaviour. Herbivore movement patterns were more strongly correlated to lion than wild dog activity. Habitat selection by predators was not activity level-dependent and, while prey and predators differed to some extent in their habitat selection, there were also overlaps, probably caused by predators seeking habitats with high prey abundance. Areas favoured by lions were used by herbivores more when lions were less active, whereas wild dog activity level was not correlated with prey use. Prey body mass was not a strong predictor of the strength of proactive predation avoidance behaviour. Herbivores showed stronger anti-predator behaviours during the rainy season when resources were abundant. Reducing movement when top predators are most active and avoiding areas with a high likelihood of predator use during the same periods appear to be common strategies to minimize predation risk. Such valuable insights into predator-prey dynamics are only possible when using similar data from multiple sympatric species of predator and prey, an approach that should become more prevalent given the ongoing integration of technological methods into ecological studies.</p>
ProACTIVE SCI Physical Activity Intervention
ClinicalTrials.gov study NCT03111030. IPD Sharing: NO. Countries: 1. Publications: 4.
Proactive Community Case Management for Malaria in Zambia
ClinicalTrials.gov study NCT04839900. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
PROactive Evaluation of Function to Avoid CardioToxicity
ClinicalTrials.gov study NCT03862131. IPD Sharing: NO. Countries: 1. Publications: 0.
Proactive Automatized Lifestyle Intervention
ClinicalTrials.gov study NCT05365269. IPD Sharing: YES. Countries: 1. Publications: 3.
A Proactive Walking Trial to Reduce Pain in Black Veterans
ClinicalTrials.gov study NCT01983228. IPD Sharing: NO. Countries: 1. Publications: 4.
Implementation and Effectiveness of Engagement and Collaborative Management to Proactively Advance Sepsis Survivorship
ClinicalTrials.gov study NCT04495946. IPD Sharing: NO. Countries: 1. Publications: 17.
Proactive Outreach for Smokers in VA Mental Health
ClinicalTrials.gov study NCT01737281. IPD Sharing: NO. Countries: 1. Publications: 4.
Evaluation of a Proactive Identification and Digital Mental Health Intervention Approach to Address Unmet Psychosocial Needs of Individuals Living With Cancer
ClinicalTrials.gov study NCT05932810. IPD Sharing: NO. Countries: 1. Publications: 1.
Proactive Protection With Azithromycin and hydroxyChloroquine in Hospitalized Patients With COVID-19
ClinicalTrials.gov study NCT04322396. IPD Sharing: Not stated. Countries: 1. Publications: 2.
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.