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625 results for “Rules”
Datasets for "Learning Anisotropic Interaction Rules from Individual Trajectories in a Heterogeneous Cellular Population"
<p>Datasets used as examples in "<strong>Learning Anisotropic Interaction Rules from Individual Trajectories in a Heterogeneous Cellular Population</strong>", DA Messenger, GE Wheeler, X Liu DM Bortz, arXiv:2204.14141, 2022. </p> <p>Code: <a href="https://github.com/MathBioCU/WSINDy_CellCluster">https://github.com/MathBioCU/WSINDy_CellCluster</a></p> <p>Download code and run <strong>visualize_trajectories.m , </strong>changing file in line 5 accordingly.</p> <p> </p> <p> </p>
Fluorescent Membrane Probes Obey the Israelachvili Rules: Original Data
<p>Original data</p>
Trait-based approach confirms the importance of propagule limitation and assembly rules in old-field restoration
<p>Trait values for plant species present in our research.</p>
Replication Package for "Improving Programming Education Through SonarQube: A Multiple Empirical Study of How Students Understand Rule Violations, Perceive the Criticality of the Rule, and the Fixing Difficulty"
Open the record for dataset details and reuse information.
Data from: A theoretical approach to the size-complexity rule
The so-called size-complexity rule claims the existence of a positive correlation between organism size and number of cell types. In this spirit, here we address the relationship between organism size and number of potential tasks that can be performed. The modeling relies on the assumption that the states of the cells within the aggregates are such that the maximum fitness is realized, but also relies on the existence of tradeoffs among the distinct functions. For group sizes larger than the number of potential tasks, fitness maximization is attained when all cells in group specialize in a given task. Under this scenario, the number of potential tasks equals the number of cell types. We have found that the morphology and the topology of aggregates, as well as the developmental mode, strongly influence the dynamics of body formation. Particularly, it has been observed that more compact structures, such as sphere-like structures, are more likely to follow the claim of the size-complexity rule, whereas more fragile structures such as linear chains, which are more vulnerable to drastic changes due to division mechanisms, can, in a broad scenario, violate the size-complexity rule.
Data from: Testing for Depéret's rule (body size increase) in mammals using combined extinct and extant data
Whether or not evolutionary lineages in general show a tendency to increase in body size has often been discussed. This tendency has been dubbed "Cope's rule" but because Cope never hypothesized it, we suggest renaming it after Depéret, who formulated it clearly in 1907. Depéret's rule has traditionally been studied using fossil data, but more recently a number of studies have used present-day species. While several paleontological studies of Cenozoic placental mammals have found support for increasing body size, most studies of extant placentals have failed to detect such a trend. Here, we present a method to combine information from present-day species with fossil data in a Bayesian phylogenetic framework. We apply the method to body mass estimates of a large number of extant and extinct mammal species, and find strong support for Depéret's rule. The tendency for size increase appears to be driven not by evolution toward larger size in established species, but by processes related to the emergence of new species. Our analysis shows that complementary data from extant and extinct species can greatly improve inference of macroevolutionary processes.
Data from: Cope's rule and the adaptive landscape of dinosaur body size evolution
The largest known dinosaurs weighed at least 20 million times as much as the smallest, indicating exceptional phenotypic divergence. Previous studies have focused on extreme giant sizes, tests of Cope's rule, and miniaturization on the line leading to birds. We use non-uniform macroevolutionary models based on Ornstein–Uhlenbeck and trend processes to unify these observations, asking: what patterns of evolutionary rates, directionality and constraint explain the diversification of dinosaur body mass? We find that dinosaur evolution is constrained by attraction to discrete body size optima that undergo rare, but abrupt, evolutionary shifts. This model explains both the rarity of multi-lineage directional trends, and the occurrence of abrupt directional excursions during the origins of groups such as tiny pygostylian birds and giant sauropods. Most expansion of trait space results from rare, constraint-breaking innovations in just a small number of lineages. These lineages shifted rapidly into novel regions of trait space, occasionally to small sizes, but most often to large or giant sizes. As with Cenozoic mammals, intermediate body sizes were typically attained only transiently by lineages on a trajectory from small to large size. This demonstrates that bimodality in the macroevolutionary adaptive landscape for land vertebrates has existed for more than 200 million years.
FIG. 5 in Proposed Rules for the incorporation of nomina of higher-ranked zoological taxa in the International Code of Zoological Nomenclature. 2. The proposed Rules and their rationale
FIG. 5. — Diagrammatic illustration (as cladograms) of the status of 11 class-series nomina according to a given ergotaxonomy and following the Rules here proposed for class-series nomenclature. G1 to G8 are taxa of rank genus, A1 to A4 taxa of rank order, B1 and B2 taxa of rank superorder, C1 and C2 taxa of rank subclass, and D1 a taxon of rank class. A-K, status of 11 classomina C1788 to C1985 �
FIG. 4 in Proposed Rules for the incorporation of nomina of higher-ranked zoological taxa in the International Code of Zoological Nomenclature. 2. The proposed Rules and their rationale
FIG. 4. — Diagrammatic illustration (as cladograms) of the status of 11 family-series nomina according to a given ergotaxonomy and following the Rules of the Code (Anonymous 1999). G1 to G8 are taxa of rank genus, A1 to A4 taxa of rank tribe, B1 and B2 taxa of rank subfamily, C1 and C2 taxa of rank family, and D1 a taxon of rank superfamily. A-K, status of 11 familiomina F1788 to F1985 �
Data for: Number of cards to infer rule for placing cards into piles
<p>Nearly sixty years ago, in a publication with a growing rate of citation ever since, JR Platt presented "strong inference" (SI) as an accumulative method of inductive inference to produce much more rapid progress than others. The article offered persuasive testimony for the use of multiple working hypotheses combined with disconfirmation. It is often cited as an exemplar of scientific practice. However, the article provides no evidence of greater efficacy. Over a 34 year period a total 780 matched trials were completed in 56 labs in a university course in statistical science. The reduction from random (18.9 cards) to selected cards was 7.2 cards, compared to a further reduction of 0.3 cards from selected to SI. In 46% of the 780 trials, the number of cards to infer a rule was greater for strong inference than for a less rigid experimental method. Based on the evidence, strong inference added little additional strength beyond that of less rigidly structured experiments.</p>
Rule-Based Closed Loop System for Type 1 Diabetes Control
ClinicalTrials.gov study NCT01614496. IPD Sharing: Not stated. Countries: 1. Publications: 1.
A Framework For Linking Sequential Pattern Rules in DLD: Perception in Toddlers
ClinicalTrials.gov study NCT04531514. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
High-Sensitivity Cardiac Troponin On Presentation to Rule Out Myocardial Infarction
ClinicalTrials.gov study NCT03005158. IPD Sharing: UNDECIDED. Countries: 0. Publications: 5.
Developmental of Clinical Prediction Rule for Females Responding to Proximal Control Exercises
ClinicalTrials.gov study NCT04481022. IPD Sharing: Not stated. Countries: 0. Publications: 3.
Mersey Acute Coronary Syndrome Rule-Out Using High Sensitive Troponin
ClinicalTrials.gov study NCT02581540. IPD Sharing: NO. Countries: 0. Publications: 1.
The Effects of Rule Modifications in 3v3 and 4v4 Small-Sided Games on Cardiovascular and Technical Performance in Elite Football Players
ClinicalTrials.gov study NCT07157150. IPD Sharing: YES. Countries: 1. Publications: 0.
ISNT Rule in Normal Population
ClinicalTrials.gov study NCT05575154. IPD Sharing: Not stated. Countries: 0. Publications: 18.
Feasibility and Pilot Study of a Rule-based Chatbot Application for Adolescents With Anxiety Symptoms
ClinicalTrials.gov study NCT05758935. IPD Sharing: YES. Countries: 1. Publications: 0.
Left Atrial Imaging Prior to Cardioversion: Leveraging Computed Tomography to Rule Out Thrombus
ClinicalTrials.gov study NCT04223505. IPD Sharing: NO. Countries: 1. Publications: 0.
Feasibility and Impact of a Decision Rule for Imaging of Emergency Department Patients With Suspected Kidney Stone
ClinicalTrials.gov study NCT01869647. IPD Sharing: NO. Countries: 1. Publications: 0.
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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)
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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.