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81 results for “STS”
Context-Aware Dataset: STS - South Tyrol Suggests IoT Mobile App Data
<p><strong>STS dataset </strong>was collected by a context-aware recommender system mobile app named as<strong> <a href="https://play.google.com/store/apps/details?id=it.unibz.sts.android&hl=en">"South Tyrol Suggests"</a></strong>. The app provides <strong>context-aware recommendations</strong> for attractions, events, public services, restaurants, and much more based on the rating preferences and personality factors of users.</p> <p><strong>Contextual</strong> <strong>variables</strong> includes </p> <ul> <li><strong>distance:</strong> far away, near by</li> <li><strong>time available:</strong> half day, one day, more than one day</li> <li><strong>temperature:</strong> burning, hot, warm, cool, cold, freezing</li> <li><strong>crowdedness:</strong> crowded, not crowded, empty</li> <li><strong>knowledge of surroundings:</strong> new to area, returning visitor, citizen of the area</li> <li><strong>season:</strong> spring, summer, autumn, winter</li> <li><strong>budget:</strong> budget traveler, price for quality, high spender</li> <li><strong>daytime:</strong> morning, noon, afternoon, evening, night</li> <li><strong>weather:</strong> clear sky, sunny, cloudy, rainy, thunderstorm, snowing</li> <li><strong>companion:</strong> alone, with friends/colleagues, with family, with girlfriend/boyfriend, with children</li> <li><strong>mood:</strong> happy, sad, active, lazy weekday: weekday, weekend</li> <li><strong>travel goal:</strong> visiting friends, business, religion, health care, social event, education, scenic/landscape, hedonistic/fun, activity/sport</li> <li><strong>means of transport:</strong> no transportation means, a bicycle, a car, public transport</li> </ul> <p>More details can be found here:</p> <p><em>Braunhofer, Matthias, Mehdi Elahi, and Francesco Ricci. <a href="https://www.researchgate.net/profile/Mehdi_Elahi2/publication/283502363_Techniques_for_cold-starting_context-aware_mobile_recommender_systems_for_tourism/links/56ccaa7608ae059e37507cc0.pdf">"<strong>Techniques for cold-starting context-aware mobile recommender systems for tourism</strong>."</a> Intelligenza Artificiale 8, no. 2 (2014): 129-143.</em></p>
Traveling Waves: The Indonesian Tsunami Warning System - STS Webinar Series #1
<p>Previously published on YouTube: https://www.youtube.com/watch?v=CWK1_Nxi__Y</p> <p>(Indonesian)</p> <p>Seri webinar ini diadakan oleh Pusat Riset Kewilayahan (PRW) BRIN untuk mendiskusikan tema-tema terkait Science, Technology, and Society Studies, salah satu program kajian yang dikembangkan di PRW-BRIN. Webinar ini membahas kelindan antara diskursus, aktor, mesin deteksi, serta praktik sains dan teknologi untuk menghadapi risiko dan ketidakpastian sistem pengetahuan peringatan dini tsunami di Indonesia. Dengan menggunakan pendekatan etnografis, diskusi ini akan berusaha menjawab pertanyaan terkait teknologi sistem peringatan dini tsunami Indonesia sebagai infrastruktur sosial dan jaringan konektivitas pakar Jerman - Indonesia dalam pengembangan sistem teknologi tersebut di Indonesia.</p> <p>(English)</p> <p>This webinar series was held by the BRIN Regional Research Center (PRW) to discuss themes related to Science, Technology, and Society Studies, one of the study programs developed at PRW-BRIN. This webinar discusses the interplay between discourse, actors, detection machines, as well as science and technology practices to deal with the risks and uncertainties of the tsunami early warning knowledge system in Indonesia. Using an ethnographic approach, this discussion will attempt to answer questions related to the technology of the Indonesian tsunami early warning system as a social infrastructure and connectivity network of German-Indonesian experts in developing the technology system in Indonesia.</p>
Рис. 7–15. Lixus pulverulentus, груΔные и брюшные сегменты, хетотаксия. 7, 10, 13 – груΔные сегменты; 8, 11, 14 – брюшной сегмент I; 9, 12, 15 – брюшные сегменты VII–X; 7–9 – виΔ сбоку; 10–12 – виΔ сверху; 13–15 – виΔ снизу. Figs 7–15. Lixus pulverulentus, thoracal and abdominal segments, and chaetotaxy. 7, 10, 13 – thoracal segments; 8, 11, 14 – abdominal segment I; 9, 12, 15 –abdominal segments VII–X; 7–9 – lateral view; 10–12 – dorsal view; 13–15 – ventral view. Setae: dls – dorsolateral, dpls – dorsopleurolateral, ds – dorsal, ls – lateral, lsts – laterosternal, msts – mesosternal, pda – pedal, pds – postdorsal, prns – pronotal, prs – prodorsal, ss – spirarulum, sts – sterna, ts – terminal, vpls – ventropleural. in Description of the preimaginal stages and biology of the weevil Lixus (Dilixellus) pulverulentus (Scopoli, 1763) (Coleoptera: Curculionidae: Lixini)
Рис. 7–15. Lixus pulverulentus, груΔные и брюшные сегменты, хетотаксия. 7, 10, 13 – груΔные сегменты; 8, 11, 14 – брюшной сегмент I; 9, 12, 15 – брюшные сегменты VII–X; 7–9 – виΔ сбоку; 10–12 – виΔ сверху; 13–15 – виΔ снизу. Figs 7–15. Lixus pulverulentus, thoracal and abdominal segments, and chaetotaxy. 7, 10, 13 – thoracal segments; 8, 11, 14 – abdominal segment I; 9, 12, 15 –abdominal segments VII–X; 7–9 – lateral view; 10–12 – dorsal view; 13–15 – ventral view. Setae: dls – dorsolateral, dpls – dorsopleurolateral, ds – dorsal, ls – lateral, lsts – laterosternal, msts – mesosternal, pda – pedal, pds – postdorsal, prns – pronotal, prs – prodorsal, ss – spirarulum, sts – sterna, ts – terminal, vpls – ventropleural.
Validation of STS Conceptual Model Designing Approach. DMI374 and DMI747 Data Sets.
<p>Surveys of DMI374 and DMI747 student groups were conducted for the purpose of validating the STS conceptual model designing method. A 5-point and dichotomous Likert questionnaire was used for the survey. The files contain response datasets used in statistical processing.</p>
Radiation Therapy and Intratumoral Autologous Dendritic Cells in Soft Tissue Sarcomas (STS)
ClinicalTrials.gov study NCT01347034. IPD Sharing: Not stated. Countries: 1. Publications: 1.
STS-Tooth: A multi-modal dental dataset for semi-supervised deep learning image segmentation
<p>In response to the increasing prevalence of dental diseases, dental health, a vital aspect of human well-being, warrants greater attention. Panoramic X-ray images (PXI) and Cone Beam Computed Tomography (CBCT) are key tools for dentists in diagnosing and treating dental conditions. Additionally, deep learning for tooth segmentation can focus on relevant treatment information and localize lesions. However, the scarcity of publicly available PXI and CBCT datasets hampers their use in tooth segmentation tasks. Therefore, this paper presents a multimodal dataset for semi-supervised deep learning in dental PXI and CBCT, named STS-2D-Tooth and STS-3D-Tooth. STS-2D-Tooth includes 4,000 images and 900 masks, categorized by age into children and adults. Moreover, we have collected CBCTs providing more detailed and three-dimensional information, resulting in the STS-3D-Tooth dataset comprising 148,400 unlabeled scans and 8,800 masks. To our knowledge, this is the first multimodal dataset combining dental PXI and CBCT, and it is the largest tooth segmentation dataset, a significant step forward for the advancement of tooth segmentation.</p>
Individualizing Pazopanib Therapy by exploRing the Role of Early Metabolic responsE and Drug Exposure as a preDICTor for Treatment Outcome in Patients With STS
ClinicalTrials.gov study NCT01995981. IPD Sharing: Not stated. Countries: 2. Publications: 1.
PLD and IFO As First-line Treatment for Patients With Advanced or Metastatic STS
ClinicalTrials.gov study NCT03268772. IPD Sharing: NO. Countries: 1. Publications: 1.
Intralesional Injection of STS in Treatment of Calcinosis
ClinicalTrials.gov study NCT06672822. IPD Sharing: YES. Countries: 1. Publications: 2.
Study on Efficacy and Tolerability of Vorinostat in Patients With Advanced, Metastatic Soft Tissue Sarcoma (STS)
ClinicalTrials.gov study NCT00918489. IPD Sharing: Not stated. Countries: 1. Publications: 1.
MCID in 30 STS Test After PR in COPD Patients
ClinicalTrials.gov study NCT03627624. IPD Sharing: UNDECIDED. Countries: 2. Publications: 7.
Retest-reliability and At-home-assessment Feasibility of the 5R-STS
ClinicalTrials.gov study NCT03321357. IPD Sharing: NO. Countries: 1. Publications: 4.
PBI-MST-01 (NCT04541108) Substudy MSD-03: Intratumoral Microdosing of Pembrolizumab Alone and With MK-0482 or MK-4830 in HNSCC or STS
ClinicalTrials.gov study NCT06413095. IPD Sharing: NO. Countries: 1. Publications: 6.
Supplementary material 1 from: Saravanakumar D, Bartholomew ES, Seepersad G, Gore-Francis J, Goldsmith J, Ramnanan N, Chang PG, Bridgemohan P, Sewsaran R, Medrano-Cabral S, Morrison StS (2023) Prioritisation of quarantine pest list for the Caribbean using a multi-criteria decision approach. NeoBiota 88: 1-16. https://doi.org/10.3897/neobiota.88.102673
AHP model developed for priotization of quarantine plant pests in the Caribbeean
A Phase II Study of Apatinib in STS Patients
ClinicalTrials.gov study NCT03064243. IPD Sharing: Not stated. Countries: 0. Publications: 1.
Gemcitabine and Docetaxel in Combination With Pazopanib (Gem/Doce/Pzb) for the Neoadjuvant Treatment of Soft Tissue Sarcoma (STS)
ClinicalTrials.gov study NCT01418001. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Transtympanic STS Against Cisplatin-induced SNHL: the SOUND Trial
ClinicalTrials.gov study NCT07281508. IPD Sharing: YES. Countries: 1. Publications: 0.
Spaceflight effects on the mouse retina: Histological gene expression and epigenetic changes after flight on STS-135
We report the findings of an animal experiment onboard STS-135 investigating the molecular aspects of the impact of spaceflight on retinal biology by performing differential gene expression profiling between mice flown onboard STS-135 and their ground control counterparts.
H-STS NET cell line perturbed with small molecule compounds
GEO Series GSE96760. Homo sapiens. 573 samples. Type: Expression profiling by high throughput sequencing.
A Phase II Study of Anlotinib in STS Patients
ClinicalTrials.gov study NCT01878448. IPD Sharing: Not stated. Countries: 1. Publications: 0.
ScienceDex guides
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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.