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2,532 results for “at present”
The Difference in Presentation Level of Variant Receptors in Female Breast Tissue in Macromastia and Micromastia
ClinicalTrials.gov study NCT00173251. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Enoxaparin Versus Unfractionated Heparin in Subjects Who Present to the Emergency Department With Acute Coronary Syndrome (RESCUE)
ClinicalTrials.gov study NCT00077818. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Clinical Presentations, Microbiology, Antibiotic Resistance Patterns and Management Outcomes of Culture-proven Infection Among Adolescent and Adult in A Tertiary Hospital in Saudi Arabia
ClinicalTrials.gov study NCT04395586. IPD Sharing: NO. Countries: 0. Publications: 0.
Characterize Novel Pathogen- and Host- Related Factors in Hospitalized Patients and Patients on the Emergency Department Presenting With Lower Respiratory Tract Infections and/or Sepsis
ClinicalTrials.gov study NCT02093247. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Retrospective Study of Patients with Acute Presentation for Asthma to an Emergency Department in UK (RAPAE)
ClinicalTrials.gov study NCT06360185. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
Aryl Hydrocarbon Receptor Ligands Present In The Environment Impact Human Trophoblast Cell Development [EVT]
GEO Series GSE246508. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
Antigen Presentation-Independent Reciprocal Immune Modulation by HLA-DRB1 Allelic Epitopes that Associate with Autoimmune Disease Risk or Protection
GEO Series GSE159821. Homo sapiens; Mus musculus. 48 samples. Type: Expression profiling by high throughput sequencing.
NPM1 inhibits tumoral antigen presentation to promote immune evasion and tumor progression
GEO Series GSE272634. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
Interleukin-1? Induces Human Endothelial Surface Expression and Trans-presentation of Interleukin-15 by Relieving let-7c-3p Suppression of Protein Translation
GEO Series GSE266374. Homo sapiens. 30 samples. Type: Expression profiling by high throughput sequencing; Non-coding RNA profiling by high throughput sequencing.
IL-12 induces myeloid cells in situ to cross-present antigen
GEO Series GSE29164. Mus musculus. 24 samples. Type: Expression profiling by array.
Antigen Presenting Dendritic Cells
GEO Series GSE702. Mus musculus. 7 samples. Type: Expression profiling by array.
Features of TAP independently presented MHC ligands revealed by quantitative mass spectrometry.
GEO Series GSE9437. Homo sapiens. 2 samples. Type: Expression profiling by array.
Specific requirement of the p84/p110γ complex of PI3Kγ for antibody-activated, inducible cross-presentation in murine type 2 DCs
GEO Series GSE273544. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
CCL3-Mediated Inflammatory Reprogramming of the Hepatocellular Carcinoma Microenvironment Enhances Macrophage Antigen Presentation and Adaptive Immune Response (RNA-Seq)
GEO Series GSE277065. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
Transcription factor Etv6 controls functional differentiation of cross-presenting classical dendritic cells
GEO Series GSE106408. Mus musculus. 28 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Workshop Presentations: RSW Analysts
These slides were presented at the AePW, April 21-22, 2012. They detail the analytical results generated by each of the participating analysis teams for the Rectangular Supercritical Wing (RSW).
ASE SIM Workshop WEBCAST Link & Presentation Slides
<a href="http://nia-mediasite.nianet.org/NIAmediasite100/Catalog/pages/catalog.aspx?catalogId=3c58920b-1b8d-4163-becd-6354c7352fd9">Link to Aeroservoelasticity Simulation Workshop WEBCAST </a>
Bonissone CIDU Presentation: Design of Local Fuzzy Models
After reviewing key background concepts in fuzzy systems and evolutionary computing, we will focus on the use of local fuzzy models, which are related to both kernel regressions and locally weighted learning. Instead of using a manual approach to develop such models, we use evolutionary algorithms to search in the design space of these models. With these models we will determine the remaining life of a unit in a fleet of vehicles. Instead of developing individual models (based on the track history of each unit) or developing a global model (based on the collective track history of the fleet), we propose local fuzzy models based on clusters of peers, similar units with comparable utilization and performance. For each cluster of peers we create a local fuzzy model. We combine the fuzzy peer-based approach for performance modeling with an evolutionary framework for model maintenance. Our process generates a collection of competing models, evaluates their performance in light of the currently available data, refines the best models using evolutionary search, and selects the best one after a finite number of iterations. This process is repeated periodically to automatically produce updated and improved versions of the model. To illustrate this methodology we chose an asset selection problem: given a fleet of industrial vehicles (diesel electric locomotives), we want to select the best subset (of fixed or variable size) for mission-critical utilization. To this end, we predict the remaining life for each unit in the fleet. We then sort the fleet using this prediction and select the highest ranked units. The model chosen to perform this prediction/selection task is a fuzzy instance based model. A series of experiments using data from locomotive operations were conducted and the results from an initial validation exercise are presented. The approach of constructing local predictive models using fuzzy similarity with neighboring points along appropriate dimensions is not specific to any asset type, but it applies to many other Prognostics and Health Management (PHM) problems.
Workshop Presentations: Overviews
These slides were presented at the AePW, April 21-22, 2012. Additional presentations can be found on each of the associated analysis webpages. Separate pages contain the RSW, BSCW and HIRENASD analysts' presentations. Updated May 15, 2012 JH
Planning to Explore: Using a Coordinated Multisource Infrastructure to Overcome Present and Future Space Flight Planning Challenges
Few human endeavors present as much of a planning and scheduling challenge as space flight, particularly manned space flight. Just on the operational side of it, efforts of thousands of people across hundreds of organizations need to be coordinated. Numerous tasks of varying complexity and nature, from scientific to construction, need to be accomplished within limited mission time frames. Resources need to be carefully managed and contingencies worked out, often on a very short notice. From the beginning of the NASA space program, planning has been done by large teams of domain experts working months, sometimes years, to put together a single mission. This approach, while proven very reliable up to now, is becoming increasingly harder to sustain. Elevated levels of NASA space activities, from deployment of the new Crew Exploration Vehicle (CEV) and completion of the International Space Station (ISS), to the planned lunar missions and permanent lunar bases, will put an even greater strain on this largely manual process. While several attempts to automate it have been made in the past, none have fully succeeded. In this paper we describe the current NASA planning methods, outline their advantages and disadvantages, discuss the planning challenges of upcoming missions and propose a distributed planning/scheduling framework (CMMD) aimed at unifying and optimizing the planning effort. CMMD will not attempt to make the process completely automated, but rather serve in a decision support capacity for human managers and planners. It will help manage information gathering, creation of partial and consolidated schedules, inter-team negotiations, contingencies investigation, and rapid re-planning when the situation demands it. The first area of CMMD application will be planning for Extravehicular Activities (EVA) and associated logistics. Other potential applications, not only in the space flight domain, and future research efforts will be discussed as well.
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.