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Dataset results
6 results for “existing structures”
Detection of Structural Components in Point Clouds of Existing RC Bridges
<p><em>The cost and effort </em><em>of</em><em> modelling existing bridges from point clouds currently outweighs the perceived benefits of the resulting model. There is a pressing need to automate this process. Previous research has achieved the automatic generation of surface primitives combined with rule-based classification to create labelled cuboids and cylinders from point clouds. While these methods work well in synthetic datasets or idealized cases, they encounter huge challenges when dealing with real-world bridge point clouds, which are often unevenly distributed and suffer from occlusions. In addition, real bridge geometries are complicated. In this paper, we propose a novel top-down method to tackle these challenges for detecting slab, pier, pier cap, and girder components in reinforced concrete bridges. This method uses a slicing algorithm to separate the deck assembly from pier assemblies. It then detects and segments pier caps using their surface normal, and girders using oriented bounding boxes and density histograms. Finally, our method merges over-segments into individually labelled point clusters. The results of 10 real-world bridge point cloud experiments indicate that our method achieves an average detection precision of 98.8%. This is the first method of its kind to achieve robust detection performance for the four component types in reinforced concrete bridges and to directly produce labelled point clusters. Our work provides a solid foundation for future work in generating rich Industry Foundation Classes models from the labelled point clusters.</em></p>
Describing and mapping of the main existing structures and systematic initiatives and academic activities for surveillance in the EU for zoonoses (transboundary, emerging and re-emerging) in domestic animals and wildlife
<p>These annexes refer to a report which describes and maps the main existing structures and systematic initiatives and academic activities for surveillance in the EU for transboundary, emerging and re-emerging zoonoses in domestic animals, wildlife, and the environment, developed by the different sectors, namely human, domestic animal, wildlife and environmental, under One Health approach. This is essential to provide scientific and technical advice and improve future schemes of surveillance. A questionnaire was compiled by MSs and the information collected was complemented by literature reviews about (i) the main existing structures and systematic initiatives or activities, and (ii) academic activities for surveillance in the EU for zoonoses in domestic animals and wildlife. The annexes to the report are as follows:</p> <p>Annex 1. Questionnaire survey on official zoonotic disease surveillance activities in the EU and neighbouring countries.</p> <p>- Sheet 1: PART 1 – Surveillance. This part explores the general organization of the surveillance plan</p> <p>- Sheet 2: PART 2 – Pathogens. This part aims to identify target pathogen and species and methods for surveillance</p> <p>Annex 2. Characteristic of surveillance plans.</p> <p>- Sheet “Pathogens”, where not primary but also a wide range of hosts are summarized.</p> <p>- Sheet “active/passive surveillance” by country</p> <p>- Sheet “origin of funding” (the proportion and number) of surveillance plans</p> <p>Annex 3. More detailed distribution of active and passive surveillance planaccording to countries and pathogen is presented in this Annex.</p> <p>Annex 4. Standardized data model (to extract key information to characterize the surveillance systems in the literature review on systematic surveillance. The data model was divided into two parts:</p> <p>- Sheet 1: PART 1 – Surveillance system (explores the general organization)</p> <p>- Sheet 2: PART 2 – Pathogens (identifies the target pathogen, species, and methods)</p> <p>Annex 5. Standardized data model used during the literature review to extract key information to characterize the surveillance performed by the academia</p>
Literature review on the main existing structures and systematic/academic initiatives for surveillance in the EU for zoonoses in the environment and the methods for surveillance of pathogens in the environment
<p>The report to which this datasets refer to is based on two literature reviews</p> <ol> <li>on the main existing structures and systematic/academic initiatives for surveillance in the EU for zoonoses in the environment, and</li> <li>on the methods for pathogen surveillance in the environment.</li> </ol> <p>Concerning (i), the purpose of this literature review was to collect published information regarding surveillance in Europe that focuses on health hazards where environmental sampling is involved. It includes a review of study design and methodological approaches, including types of environmental samples, and methods to detect animal pathogens in the environment. Documents describing systematic, structured, or academic surveillance systems targeting zoonotic pathogens in the environment in Member States and neighbouring countries were searched. A list of target zoonotic pathogens has already been produced by EFSA and was included in the search strings in literature browsers. The publication search was done in the following databases: Biomedical databases (Embase) and Science databases (ISI web of Science, Pubmed). In addition to references retrieved directly from scientific browsers the literature cited to identify missing references was examined. A standardised data model was used to extract key information to characterise the surveillance systems (Annex 1), which is presented as an excel document, including the list of references and the vocabulary.</p> <p>Concerning (ii), the purpose of this literature review was to assess the published information on the methods applied to survey zoonotic pathogens or diseases using environmental protocols, i.e., non-invasive environmental samples. To achieve this goal, scientific databases such as Scopus, Pubmed and Web of Science (WOS) were used. The search method was limited to documents published between 2017 to 2022. Thereafter, inclusion/exclusion criteria were applied. A standardised data model was similarly used to extract key information from each document: target pathogen; type of samples collected (faecal, object surface…) and if it is an invasive or non-invasive collection method; sample collection methods; pre-analytical treatments; pathogen identification methods, and existence of quality controls. Data were collected at the assay level. The full text of all selected papers was read, and relevant information was extracted, summarised, and schematically outlined in tables in the form of one or multiple single-entry assays per reference. The standardized data model is presented in Annex 2, and it was divided into 6 parts: PART 1 – Target pathogen; PART 2 – Type of samples collected (faecal, object surface…) and whether it is an invasive or non-invasive collection method; PART 3 – Sample collection methods; PART 4 – Pre-analytical treatments; PART 5 – Pathogen identification methods; PART 6 – Quality controls. This annex is presented as an excel document, including the list of references.</p>
Pre-existing Structures and Stress Variations Jointly Control the Induced Seismicity in Enhanced Geothermal System of Gonghe Basin, China
<p>This is the dataset available for the article titled "Pre-existing Structures and Stress Variations Jointly Control the Induced Seismicity in Enhanced Geothermal System of Gonghe Basin, China", including phase information, earthquake catalog, waveforms of earthquakes and resolved focal mechanisms, 1D velocity model.</p>
Original data for "Multiple co-existing structures of an RNA four-way junction resolved by FRET, SAXS, and integrative modeling"
<p>Experimental single-molecule FRET data (Intensity ratio histograms) and starting structures used for rigid body docking for an RNA four-way junction related to the hairpin ribozyme.</p> <p> </p>
A Study of an Existing Database to Assess the Treatment Persistence to Basal Insulin in Type 2 Diabetes Mellitus Patients in a Structured Patient Education Program in India
ClinicalTrials.gov study NCT05628090. IPD Sharing: YES. Countries: 1. Publications: 0.
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
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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.