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284 results for “reasoner”
Data from: Real-world study of efficacy, risk management and reasons for discontinuation of natalizumab for treatment of multiple sclerosis in Russia
Open the record for dataset details and reuse information.
Figure 3 in Goliath frogs build nests for spawning - the reason for their gigantism?
Figure 3. Different Conraua goliath nest types. On the left side nest types 1 (a), 2 (b) and 3 (c) are sketched in top view and in cross section, respectively; on the right side examples for each nest type are illustrated; compare text for further details.
Figure 4 in Goliath frogs build nests for spawning - the reason for their gigantism?
Figure 4. Conraua goliath is heavily hunted in the region, either using fishhooks set above breeding habitats (a, c) or with traps (b).
Figure 1 in Goliath frogs build nests for spawning - the reason for their gigantism?
Figure 1. Adult Conraua goliath from Cameroon (a) and different sections of one of its habitats, the Mpoula River, Littoral District, western Cameroon (b, c).
Facilitating Exceptional Execution Auditing via Probabilistic Reasoning
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Risk Factors and Reasons for Cancellation Within 24 Hours of Scheduled Elective Surgery in an Academic Medical Centre
ClinicalTrials.gov study NCT03812133. IPD Sharing: Not stated. Countries: 0. Publications: 0.
As Low As Reasonable Achievable Fluoroscopy for SVT Ablation
ClinicalTrials.gov study NCT02743325. IPD Sharing: NO. Countries: 0. Publications: 0.
Outcomes of Unfit Patients With CLL Included in the GIMEMA LLC1114 Trial Who Discontinued Ibrutinib Due to Reasons Other Than Disease Progression
ClinicalTrials.gov study NCT06084923. IPD Sharing: NO. Countries: 0. Publications: 0.
RIAT Registry: Reason for Not Intensifying Antihypertensive Treatment
ClinicalTrials.gov study NCT00258921. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Strategic Memory and Reasoning Training for Cognitive Problems
ClinicalTrials.gov study NCT04554537. IPD Sharing: NO. Countries: 0. Publications: 0.
Retrospective Observational Trial on Reasons for Withdraw of Adjuvant Tamoxifen in Breast Cancer Patients
ClinicalTrials.gov study NCT00727883. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Study of Readmission to Intensive Care Unit After Cardiac Surgery in Heart Hospital of Assiut University : Risk Factors .Reasons and Early Out Come
ClinicalTrials.gov study NCT07083297. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Designing Resource-Bounded Reasoners using Bayesian Networks
In this work we are concerned with the conceptual design of large-scale diagnostic and health management systems that use Bayesian networks. While they are potentially powerful, improperly designed Bayesian networks can result in too high memory requirements or too long inference times, to they point where they may not be acceptable for real-time diagnosis and health management in resource-bounded systems such as NASA's aerospace vehicles. We investigate the clique tree clustering approach to Bayesian network inference, where increasing the size and connectivity of a Bayesian network typically also increases clique tree size. This paper combines techniques for analytically characterizing clique tree growth with bounds on clique tree size imposed by resource constraints, thereby aiding the design and optimization of large-scale Bayesian networks in resource-bounded systems. We provide both theoretical and experimental results, and illustrate our approach using a NASA case study. **Reference:** O. J. Mengshoel, “Designing Resource-Bounded Reasoners using Bayesian Networks: System Health Monitoring and Diagnosis”, In Proc. of the 18th International Workshop on Principles of Diagnosis (DX-07), Nashville, TN, May 2007. **BibTex Reference:** @inproceedings{mengshoel07designing, author = "Mengshoel, O. J.", title = "Designing Resource-Bounded Reasoners using {Bayesian} Networks: System Health Monitoring and Diagnosis", booktitle = {Proceedings of the 18th International Workshop on Principles of Diagnosis (DX-07)}, year = {2007}, pages = {330--337}, address = {Nashville, TN}, }
Vehicle-Level Reasoning Systems: Integrating System-Wide data to Estimate Instantaneous Health State
One of the primary goals of Integrated Vehicle Health Management (IVHM) is to detect, diagnose, predict, and mitigate adverse events during the flight of an aircraft, regardless of the subsystem(s) from which the adverse event arises. To properly address this problem, it is critical to develop technologies that can integrate large, heterogeneous (meaning that they contain both continuous and discrete signals), asynchronous data streams from multiple subsystems in order to detect a potential adverse event, diagnose its cause, predict the effect of that event on the remaining useful life of the vehicle, and then take appropriate steps to mitigate the event if warranted. These data streams may have highly non-Gaussian distributions and can also contain discrete signals such as caution and warning messages which exhibit non-stationary and obey arbitrary noise models. At the aircraft level, a Vehicle-Level Reasoning System (VLRS) can be developed to provide aircraft with at least two significant capabilities: improvement of aircraft safety due to enhanced monitoring and reasoning about the aircraft’s health state, and also potential cost savings through Condition Based Maintenance (CBM). Along with the achieving the benefits of CBM, an important challenge facing aviation safety today is safeguarding against system- and component-level failures and malfunctions. Citation: A. N. Srivastava, D. Mylaraswamy, R. Mah, and E. Cooper, “Vehicle Level Reasoning Systems: Concept and Future Directions,” Society of Automotive Engineers Integrated Vehicle Health Management Book, Ian Jennions, Ed., 2011.
A Reasoning Architecture for Expert Troubleshooting of Complex Processes
This paper introduces a novel reasoning methodology, in combination with appropriate models and measurements (data) to perform accurately and expeditiously expert troubleshooting for complex military and industrial processes. This automated troubleshooting tool is designed to support the maintainer/ repairman by identifying and locating faulty system components. The enabling technologies build upon a Model Based Reasoning paradigm and a Dynamic Case Based Reasoning method acting as the intelligent database. A case study employs a helicopter Intermediate Gearbox as the application domain to illustrate the efficacy of the approach.
A Model-based Avionic Prognostic Reasoner (MAPR)
The Model-based Avionic Prognostic Reasoner (MAPR) presented in this paper is an innovative solution for non-intrusively monitoring the state of health (SoH) and predicting the remaining useful life (RUL) of electronic and electromechanical assets by accessing and processing data obtained from a standard avionics data bus. To support Integrated Vehicle Health Monitoring (IVHM) initiatives, the solution being described here has been designed to be as non-intrusive as possible. An innovative, model-driven anomaly diagnostic and fault characterization system for electromechanical actuator (EMA) systems was developed to mitigate potentially catastrophic faults. EMA systems are used in a wide variety of aircraft applications to control critical components such as control surfaces, landing gear and thrust vector control. Failure in any one of these systems can compromise passenger safety, as well as mission success. A MIL-STD-1553 bus interface and monitor were designed to extract environmental (e.g., altitude, air speed, air density) and operational (i.e., response of system to a commanded change) data of a representative EMA system and to determine whether an anomaly is detected, and the corresponding severity. The MIL-STD-1553 bus was chosen as the test bed to develop this approach, due to its large installed base and availability of compatible development tools. Advanced and unique reasoning methodologies are applied to the extracted data sets to provide anomaly detection and fault classification on various fault modes and eventually yield SoH and RUL. In this paper we describe a data monitoring unit that will, in real time, identify, isolate, and characterize faults and establish their severity so that major performance problems can be alleviated. When built, this system will consist of a laptop with a Peripheral Component Interconnect (PCI) card slot that can accept multiple interfaces to the MAPR software package. The MAPR package will be designed to be adaptable for a large number of different platforms, for portability and for maximum input data type flexibility. This paper describes a ground-based prototype of the technology to show the efficacy of the method.
To compare the transcriptome expression of cumulus granulosa cells between PCOS patients with insulin resistance and women undergoing assisted reproduction for fallopian tube reasons
GEO Series GSE216609. Homo sapiens. 7 samples. Type: Expression profiling by high throughput sequencing.
Towards Explainable Classification of Non-Functional Requirements Using Fine-Tune-Chain-of-Thought Reasoning - Repo 2
<p>Supplementary material for <em>Towards Explainable Classification of Non-Functional Requirements Using Fine-Tune-Chain-of-Thought Reasoning </em></p> <div> <div> </div> <div>This version contains the llama2-7B model generated output for NFR identification on the PURE dataset. As discussed, the llama2-7B model mostly generated extraneous text. </div> <div> </div> <div>Llama2-7B generated output can be found in the column > <em>Model_output</em></div> <div>Input to Llama2-7B column > <em>llama_input_pure_test</em></div> <div> </div> <div><strong>Here is the link to repo 1 for accessing the fine-tuned models, code, and datasets > <a href="../records/10574330">https://zenodo.org/records/10574330</a></strong></div> </div>
Opt-out rates and reasons for non-participation in a single-arm feasibility trial (ENGAGE) of a guided internet-administered CBT-based intervention for parents of children treated for cancer
<p>Data to support a cross-sectional nested survey embdeed with the ENGAGE study, a single-arm feasibility study (ENGAGE) of a guided, internet-administered, CBT-based intervention for parents of children treated for cancer. </p> <p>Primary objectives examined opt-out and consent rates, mode and time point of opt-out, and sociodemographic characteristics of those who opted out versus chose to participate in the ENGAGE study. Secondary objectives examined reasons for non-participation.</p>
Reasonable Accommodation Factor Survey
The purpose of this study was (a) to explore the latent factors in the Reasonable Accommodation Factor Survey (RAFS) instrument and (b) to compare scores on the latent factors of the RAFS by participant's role. Eight latent factors were identified through an exploratory factor analysis with orthogonal rotation. The reliability tests indicated satisfactory reliability scores on each of the eight latent factors of the RAFS. Comparison of scores by roles of stakeholders (employee, employer, and service provider) indicated statistically significant differences in scores on three latent factors: Employee Competence in Reasonable Accommodation, Workplace Impact, and Employee Work Record. Implications for practice and research are discussed.
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.