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ShareScore release 0.7.1
Dataset results
60 results for “load profile”
Daily load and flexibility profiles (2030) according to the Slow Progression scenario of the electricity transmission system from Portugal – ATTEST project
<p>This dataset was prepared under the framework of the ATTEST project, financed by the European Commission with grant number 864298. The dataset contains information about the full transmission test network of Portugal as in 2030, considering a Slow Progression scenario which represents a lower demand increase and less renewables in the generation. The grid topology has been anonymized and contains 312 nodes, 592 branches and 8 interconnections with Spain. It is operated at 400 kV, 220 kV and 150 kV. There are 299 generators, and a label classifies each of them according to the generation technology type (e.g., Fossil Gas, Wind Onshore, etc.). A network model (MatPower format) including the grid information and considering realistic assumptions for unknown data was built from scratch taking into account the available public data released by the Portuguese TSO as in 2020 and then updated to 2030 conditions. The auxiliary spreadsheet contains the following hourly data: load data, generator status obtained from unit commitment, regulated voltage magnitude setpoint of each generator, transformer tap ratio and aggregated flexibility per consumption node.</p>
Gene expression profiles of OT-1 T cells co-cultured with MHC-I Negative Tumors and Antigen Loaded Macrophages
GEO Series GSE220960. Mus musculus. 9 samples. Type: Expression profiling by array.
Cell-type-specific profiling of loaded miRNAs from Caenorhabditis elegans reveals spatial and temporal flexibility in Argonaute loading [RNA-seq]
GEO Series GSE156717. Caenorhabditis elegans. 6 samples. Type: Expression profiling by high throughput sequencing.
Transcriptional profiling of Slc7a7-deficient bone marrow derived macrophages subjected to in vitro LDL loading
GEO Series GSE254398. Mus musculus. 18 samples. Type: Expression profiling by high throughput sequencing.
Modeling ribosome dwell times and relationship with tRNA loading and codon usage in mammals (Ribosome Profiling)
GEO Series GSE126383. Mus musculus. 11 samples. Type: Other.
Transcriptome profiling of Atlantic salmon (Salmo salar) parr with higher and lower pathogen loads following Piscirickettsia salmonis infection
GEO Series GSE178327. Salmo salar. 15 samples. Type: Expression profiling by array.
TRACE-seq: A transgenic system for unbiased loading of mRNA into extracellular vesicles allowing non-invasive transcriptome profiling of living cells
GEO Series GSE186954. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.
Scalability Assessment of Microservice Architecture Deployment Configurations: A Domain-based Approach Leveraging Operational Profiles and Load Tests - Reproducibility Package
<p>Reproducibility package for the following publication:</p> <p>Alberto Avritzer, Vincenzo Ferme, Andrea Janes, Barbara Russo, André van Hoorn, Henning Schulz, Daniel Menasché, Vilc Rufino: <em>Scalability Assessment of Microservice Architecture Deployment Configurations: A Domain-based Approach Leveraging Operational Profiles and Load Tests</em>, Journal of Systems and Software, 2020, https://doi.org/10.1016/j.jss.2020.110564.</p>
The Effect of Loading Dose of Magnesium Sulfate on Uterine, Umbilical, and Fetal Middle Cerebral Arteries Doppler, Biophysical Profile, CTG, Maternal Vital Signs in Women With Severe Preeclampsia
ClinicalTrials.gov study NCT03891498. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Metabolites Profiling Reveals Nutrient Processing Patterns Upon Dietary Loading
ClinicalTrials.gov study NCT05784506. IPD Sharing: Not stated. Countries: 1. Publications: 0.
The expression profile of serum lncRNAs in pregnant women with high hepatitis B viral load during antiviral and non-antiviral treatment
GEO Series GSE238157. Homo sapiens. 12 samples. Type: Non-coding RNA profiling by array.
Modeling ribosome dwell times and relationship with tRNA loading and codon usage in mammals (tRNA Profiling)
GEO Series GSE126382. Mus musculus. 24 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Cell-type-specific profiling of loaded miRNAs from Caenorhabditis elegans reveals spatial and temporal flexibility in Argonaute loading [miRNA-seq]
GEO Series GSE156716. Caenorhabditis elegans. 14 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Transcriptional profile of the CNS of pups from Zika virus-infected SJL mothers treated with nanoliposomes loaded with AHR antagonist CH223191
GEO Series GSE147094. Mus musculus. 7 samples. Type: Expression profiling by high throughput sequencing.
Cell-type-specific profiling of loaded miRNAs from Caenorhabditis elegans reveals spatial and temporal flexibility in Argonaute loading
GEO Series GSE156721. Caenorhabditis elegans. 20 samples. Type: Expression profiling by high throughput sequencing; Non-coding RNA profiling by high throughput sequencing.
Designing Data-Driven Battery Prognostic Approaches for Variable Loading Profiles: Some Lessons Learned
Among various approaches for implementing prognostic algorithms data-driven algorithms are popular in the industry due to their intuitive nature and relatively fast developmental cycle. However, no matter how easy it may seem, there are several pitfalls that one must watch out for while developing a data-driven prognostic algorithm. One such pitfall is the uncertainty inherent in the system. At each processing step uncertainties get compounded and can grow beyond control in predictions if not carefully managed during the various steps of the algorithms. This paper presents analysis from our preliminary development of data- driven algorithm for predicting end of discharge of Li-ion batteries using constant load experiment data and challenges faced when applying these algorithms to randomized variable loading profile as is the case in realistic applications. Lessons learned during the development phase are presented.
Gene Expression Profiles in Engineered Cardiac Tissues Respond to Mechanical Loading and Inhibition of Tyrosine Kinase
GEO Series GSE48342. Rattus norvegicus. 22 samples. Type: Expression profiling by array.
Transcription profiling of tomato leaves treated with harpin, chitosan nanoparticles and harpin loaded chitosan nanoparticles against untreated controls
GEO Series GSE100594. Solanum lycopersicum. 20 samples. Type: Expression profiling by array.
Transcriptomic profiling of HepaRG cells with or without fat-loading
GEO Series GSE185169. Homo sapiens. 8 samples. Type: Expression profiling by high throughput sequencing.
Linalool, an aromatic terpenoid, rewires transcriptome profile of lipid-loaded HepG2 cells
GEO Series GSE45961. Homo sapiens. 8 samples. Type: Expression profiling by array.
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.