PHYLOGENETIC STUDIES OF ANEMONE STYLOSA

1965 ◽  
Vol 43 (3) ◽  
pp. 361-372 ◽  
Author(s):  
G. Boraiah
Keyword(s):  
Chromosome Rearrangement ◽  
Large Chromosome ◽  
Large Set ◽  
Meiotic Analysis ◽  
Phylogenetic Studies ◽  
Small Set

A collection of the allotetraploid Anemone stylosa Nelson from Heliotrope Mts., Gunnison, Utah, was successfully crossed with A. multifida Poir. (tetraploid) and the diploids A. riparia Fern., A. virginiana L., A. silvestris L., and A. pavonina Lam. The karyotype of A. stylosa resembles that of A. multifida except for modifications of chromosome VII in the “large set” and chromosome IV in the “small set”. Meiotic analysis in A. stylosa × A. multifida hybrids indicates that these modifications are due to a chromosome interchange and that this is the only detectable chromosome rearrangement between the two species.Analysis of the crosses with the diploids corroborates these conclusions and suggests that the donor of the “large-chromosome” set of A. stylosa had the A. riparia karyotype rather than the A. virginiana one. A. stylosa may have originated as a variant of A. multifida in which an interchange became established homozygously.

Modelling spatial reasoning systems with shape algebras and formal logic

1997 ◽  
Vol 11 (4) ◽  
pp. 273-285 ◽  
Author(s):  
Scott C. Chase
Keyword(s):  
Spatial Reasoning ◽  
Predicate Logic ◽  
Spatial Relations ◽  
Large Set ◽  
First Order ◽  
Reasoning Systems ◽  
Geometric Objects ◽  
Small Set ◽  
Definition Of ◽  
High Level

AbstractThe combination of the paradigms of shape algebras and predicate logic representations, used in a new method for describing designs, is presented. First-order predicate logic provides a natural, intuitive way of representing shapes and spatial relations in the development of complete computer systems for reasoning about designs. Shape algebraic formalisms have advantages over more traditional representations of geometric objects. Here we illustrate the definition of a large set of high-level design relations from a small set of simple structures and spatial relations, with examples from the domains of geographic information systems and architecture.

The relationship between genetic and cytogenetic maps of pea. I. Standard and translocation karyotypes

Genome ◽  
1997 ◽  
Vol 40 (5) ◽  
pp. 744-754 ◽  
Author(s):  
K. J. Hall ◽  
J. S. Parker ◽  
T. H. N. Ellis
Keyword(s):  
Linkage Map ◽  
Synaptonemal Complex ◽  
Chromosome Rearrangement ◽  
Translocation Line ◽  
Mitotic Chromosomes ◽  
Cytogenetic Map ◽  
Cytogenetical Study ◽  
Meiotic Analysis ◽  
Translocation Karyotypes ◽  
The Relationship

A detailed cytogenetical study of inbred lines of pea and their F1 hybrids has been undertaken to study the relationship between the cytogenetic map and the molecular linkage map. The mitotic karyotypes of a standard pea line, JI15, a translocation line, JI61, and line JI281, a line used in the production of a mapping population, are given. A chromosome rearrangement detected by cytogenetic analysis of mitotic chromosomes has been further defined by synaptonemal complex (SC) analysis and the study of metaphase I chromosome behaviour. This meiotic analysis has allowed a comparison of SC physical lengths, observed chiasma frequencies, and recombination frequencies, as estimated from the genetic map, as a means of comparing physical and genetic distances.Key words: Pisum, linkage map, cytogenetics, chromosome rearrangement, synaptonemal complex.

Computer-Aided Design Synthesis Using Syntactic Solid Modeling

1994 ◽  
Author(s):  
Vassilios E. Theodoracatos ◽  
Xiaogang Guan
Keyword(s):  
Computer Aided Design ◽  
Solid Modeling ◽  
Large Set ◽  
Complex Structures ◽  
Design Synthesis ◽  
Computer Aided ◽  
Grammar Rules ◽  
Small Set ◽  
Definition Of ◽  
Aided Design

Abstract This paper presents a new Computer-Aided Design (CAD) synthesis model which uses Plex Grammar as structural relationship descriptors and NURBS surface representation for constructing standard and non-standard solid entities. Here, the designer uses a syntactic design methodology for early topological and geometrical definition of the structure of concept alternatives resulting from the design process. This syntactic scheme provides the capability of describing a large set of complex structures by using a small set of simple entities. The recursive nature of the grammar and the hierarchical representation of the structure makes the description of complex structures simple and under the direct control of the designer. An object structure constructive tree is generated and subsequently translated into Plex Grammar production rules in order to form an Interconnection Matrix (ICM) expressing. The resulting Plex structure defined in the ICM expresses the topological information among entities which form the specific types of objects. By modifying the Plex grammar rules, various objects with different geometry and topology can easily be reconstructed. Compared to conventional solid modeling techniques, this approach provides more systematic object generation, easy manipulation and modification, control over congruity and the ability to represent sculptured shapes. Several examples of syntactic solid modeling applied in design synthesis will be presented for further usage in downstream applications.

scholarly journals Response Shaping to Improve Food Acceptance for Children with ASD: Effects of Small and Large Food Sets

2019 ◽  
Author(s):  
Jennifer R. Ledford
Keyword(s):  
Poor Response ◽  
Food Selectivity ◽  
Large Set ◽  
Cumulative Number ◽  
Food Acceptance ◽  
Children With Asd ◽  
Small Constant ◽  
Shaping Procedure ◽  
Small Set ◽  
Limited Food

Background: Food selectivity, characterized by food refusal, limited food repertoire, or preference for certain types of foods, is common among children with ASD. Method: In this study, researchers examined the effects of a response shaping procedure using a large rotating food set and a small constant food set on food acceptance for two boys with ASD. The small set consisted of three foods that were presented during every session; the large set consisted of 15 foods, of which three were presented during each session, in randomly ordered sets. Researchers measured the percentage of correct behaviors and the cumulative number of foods with which participants interacted. Two concurrently operating multiple baseline across behaviors designs were used to assess whether the shaping procedure resulted in increased correct responding compared to baseline conditions, and whether the intervention was differentially effective with large versus small food sets. Results: The procedures were similar in efficiency for one participant, although he ate many more foods in the large set condition. For the other participant, shaping was successful at increasing some acceptance behaviors (e.g., putting food in his mouth) but only the small set resulted in eating a new food. Conclusions: Practitioners should consider use of less restrictive or intrusive interventions to promote food acceptance and the use of larger sets of foods, modified to include fewer foods in the case of poor response to intervention.

scholarly journals Overspecification of small cardinalities in reference production

2021 ◽  
Vol 1 ◽  
pp. 298
Author(s):  
Natalia Zevakhina ◽  
Elena Pasalskaya
Keyword(s):  
Experimental Evidence ◽  
Large Set ◽  
Bare Plural ◽  
Small Cardinality ◽  
Small Set ◽  
Human Capacity

This paper presents experimental evidence for overspecification of small cardinalities in refer-ence production. The idea is that when presented with a small set of unique objects (2, 3 or 4), the speaker includes a small cardinality while describing given objects, although it is overin-formative for the hearer (e.g., 'three stars'). On the contrary, when presented with a large set of unique objects, the speaker does not include cardinality in their description – so she produces a bare plural (e.g. 'stars'). The effect of overspecifying small cardinalities resembles the effect of overspecifying color in reference production which has been extensively studied in recent years (cf. Rubio-Fernandez 2016, Tarenskeen et al. 2015). When slides are flashed on the screen one by one, highlighted objects are still overspecified. We argue that one of the main reasons lies in subitizing effect, which is a human capacity to instantaneously grasp small cardinalities.

scholarly journals Towards semantic interoperability: finding and repairing hidden contradictions in biomedical ontologies

2020 ◽  
Vol 20 (S10) ◽  
Author(s):  
Luke T. Slater ◽  
Georgios V. Gkoutos ◽  
Robert Hoehndorf
Keyword(s):  
Automated Reasoning ◽  
Semantic Interoperability ◽  
Large Set ◽  
Biomedical Domain ◽  
Biomedical Ontologies ◽  
Small Set ◽  
Multiple Domains ◽  
Novel Algorithm

Abstract Background Ontologies are widely used throughout the biomedical domain. These ontologies formally represent the classes and relations assumed to exist within a domain. As scientific domains are deeply interlinked, so too are their representations. While individual ontologies can be tested for consistency and coherency using automated reasoning methods, systematically combining ontologies of multiple domains together may reveal previously hidden contradictions. Methods We developed a method that tests for hidden unsatisfiabilities in an ontology that arise when combined with other ontologies. For this purpose, we combined sets of ontologies and use automated reasoning to determine whether unsatisfiable classes are present. In addition, we designed and implemented a novel algorithm that can determine justifications for contradictions across extremely large and complicated ontologies, and use these justifications to semi-automatically repair ontologies by identifying a small set of axioms that, when removed, result in a consistent and coherent set of ontologies. Results We tested the mutual consistency of the OBO Foundry and the OBO ontologies and find that the combined OBO Foundry gives rise to at least 636 unsatisfiable classes, while the OBO ontologies give rise to more than 300,000 unsatisfiable classes. We also applied our semi-automatic repair algorithm to each combination of OBO ontologies that resulted in unsatisfiable classes, finding that only 117 axioms could be removed to account for all cases of unsatisfiability across all OBO ontologies. Conclusions We identified a large set of hidden unsatisfiability across a broad range of biomedical ontologies, and we find that this large set of unsatisfiable classes is the result of a relatively small amount of axiomatic disagreements. Our results show that hidden unsatisfiability is a serious problem in ontology interoperability; however, our results also provide a way towards more consistent ontologies by addressing the issues we identified.

OPTIMIZATION OF A NONLINEAR ELECTRICAL–THERMAL MODEL OF THE SKIN

2013 ◽  
Vol 25 (03) ◽  
pp. 1350039 ◽  
Author(s):  
S. Rasoul Molaei ◽  
Reza Jafari ◽  
Sajad Jafari ◽  
Hamid Reza Abdolmohammadi
Keyword(s):  
Genetic Algorithm ◽  
Thermal Model ◽  
Outward Current ◽  
Special Kind ◽  
Experimental Results ◽  
Large Set ◽  
Small Set ◽  
State Regime ◽  
Physical Phenomena ◽  
Capacitance Current

This paper presents modified equations for a nonlinear electrical–thermal model of the skin, and optimizes the parameters of the model by a genetic algorithm. In publications, an electrical–thermal model for the skin has been presented. Although, the model is sophisticated and includes the most of physical phenomena occurring in the skin; however, mathematical equations used in this model for the capacitance and dissipated power are incompletely stated so that they sometimes cause instability in solving the equations. In this paper, the equations given previously for the capacitance current and the dissipated power are first modified. We have considered different inward and outward current in the model, since there are different ions which make this two currents in the skin. Then, a special kind of genetic algorithm is applied to estimate the parameters of the model. The used algorithm is a powerful optimization tool against high-dimensional problems and can overcome the curse of dimensionality. In each iteration, it divides variable sets into two groups: a small set still variable and a large set frozen on their best values. Finally, modeling results are compared with experimental results. The comparison shows there is a good agreement between the modeling and experimental results especially in the steady state regime.

scholarly journals A Deeper Look at Sheet Music Composer Classification Using Self-Supervised Pretraining

2021 ◽  
Vol 11 (4) ◽  
pp. 1387
Author(s):  
Daniel Yang ◽  
Kevin Ji ◽  
TJ Tsai
Keyword(s):  
Language Processing ◽  
Data Augmentation ◽  
Language Model ◽  
Classification Performance ◽  
Large Set ◽  
Sheet Music ◽  
Modern Language ◽  
Music Score ◽  
Augmentation Strategies ◽  
Small Set

This article studies a composer style classification task based on raw sheet music images. While previous works on composer recognition have relied exclusively on supervised learning, we explore the use of self-supervised pretraining methods that have been recently developed for natural language processing. We first convert sheet music images to sequences of musical words, train a language model on a large set of unlabeled musical “sentences”, initialize a classifier with the pretrained language model weights, and then finetune the classifier on a small set of labeled data. We conduct extensive experiments on International Music Score Library Project (IMSLP) piano data using a range of modern language model architectures. We show that pretraining substantially improves classification performance and that Transformer-based architectures perform best. We also introduce two data augmentation strategies and present evidence that the model learns generalizable and semantically meaningful information.

scholarly journals Study of principal component analyses for pod traits in soybean

2021 ◽  
Vol 17 (2) ◽  
pp. 341-349
Author(s):  
Shivani Uikey ◽  
Stuti Sharma ◽  
M.K. Shrivastava ◽  
Pawan K. Amrate
Keyword(s):  
Principal Component ◽  
Large Set ◽  
Eigen Value ◽  
Total Variability ◽  
Small Set ◽  
Biological Yield ◽  
Advanced Line ◽  
Ideotype Breeding ◽  
Yield Factor ◽  
Positive Effect

Yield being a complex entity influenced by several components and environments. PCA is a well-known method of dimension reduction that can be used to reduce a large set of variables to a small set that still contains most of the information in the large set (Massay, 1965 and Jolliffie, 1986). In present study, PCA preformed for pod and yield traits revealed that out of fourteen, only five principal components (PCs) exhibited more than 1.0 eigen value and showed about 70.44% total variability among the traits. PC1 showed 23.83% variability with eigen value 3.33 indicating the maximum variation in comparison to other four PCs. The PC1 was more related to traits viz., days to 50% flowering, total number of pods per plant, number of seeds per plant, biological yield per plant and seed yield per plant. Thus, PC1 allowed for simultaneous selection of yield related traits and it can be regarded as yield factor. PC2 exhibited positive effect for days to maturity, number of primary branches per plant and number of nodes per plant, The PC3 was more related to number of two seeded pods per plant, 100 seed weight and harvest index traits, whereas PC4 was more loaded with three seeded pods per plant. PC5 was more related to plant height and number of one seeded pods per plant. A high value of PC score of a particular advanced line in a particular PC denotes high value for those variables. Genotypes namely KS 103, JS 20-15, PS 1423, Cat 1957, Cat 1958, JS 20-06 and JS 20-66 can be considered an ideotype breeding material for selection and for further utilization in precise breeding programme.

The Differences between Suicide Ideators and Suicide Attempters: Simple, Complicated, or Complex?

2019 ◽  
Author(s):  
Xieyining Huang ◽  
Jessica D. Ribeiro ◽  
Joseph C. Franklin
Keyword(s):  
High Accuracy ◽  
Large Set ◽  
Total N ◽  
Number Of Factors ◽  
Psychological Evidence ◽  
Small Set ◽  
Logistic Regressions ◽  
The Difference ◽  
Necessary And Sufficient ◽  
Simple Difference

Background: Given that many people think about suicide and relatively few attempt suicide, researchers have proposed that accurate differentiation between ideators and attempters can aid suicide prevention efforts. Ideators and attempters might differ in three possible ways. First, they might differ in a simple way such that one or a small set of factors are both necessary and sufficient to distinguish between the two groups. Second, ideators and attempters might differ in a complicated way such that a specific combination of a large set of factors is necessary and sufficient for the distinction. Third, complex differences might exist: many possible combinations of a large set of factors are sufficient to distinguish the two groups, but no combination is necessary. This study empirically examined the difference between suicide ideators and attempters. To support a simple difference, individual factors need to produce high classification accuracy. To support complicated differences, one optimized algorithm including a large number of factors needs to produce high accuracy, but removal of factors from the algorithm should substantially reduce the accuracy. To support complex differences, multiple algorithms including a large number of factors need to produce similarly high accuracy, and meanwhile not all algorithms should lead to high accuracy.Methods: Across five samples (total N = 3,869), univariate logistic regressions were conducted to test for simple differences. To test for complicated and complex differences, Machine learning (ML) methods were used to identify the optimized algorithm with all available variables. Subsequently, the same methods were repeated after removing the top five most important or discriminative variables, and a randomly selected 10% subset of variables. Multiple logistic regressions were conducted with all variables.Results: Results were highly consistent across samples. Univariate logistic regressions on average yielded chance-level accuracy. ML algorithms with all variables or with a subset of variables removed showed good accuracy, whereas multiple logistic regressions produced poor to fair accuracy.Conclusions: The study found that differences between suicide ideators and attempters are complex rather than simple or complicated. The findings are consistent with broader psychological evidence and bear important implications for research and clinical practice.

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