A Computational and Statistical Framework for Multidimensional Domain Acoustooptic Material Interrogation

2005 ◽  
Author(s):  
H. T. Banks ◽  
V. A. Bokil
Keyword(s):  
Statistical Framework ◽  
Multidimensional Domain ◽  
Material Interrogation

A Hierarchy of Multinomial Models for Multidimensional Source Monitoring

Methodology ◽  
2005 ◽  
Vol 1 (1) ◽  
pp. 2-17 ◽  
Author(s):  
Thorsten Meiser
Keyword(s):  
Cognitive Processes ◽  
Source Monitoring ◽  
Source Information ◽  
Model Comparisons ◽  
Storage And Retrieval ◽  
Multinomial Processing Tree ◽  
Multinomial Models ◽  
Hierarchical Relationship ◽  
Statistical Framework ◽  
Tree Models

Abstract. Several models have been proposed for the measurement of cognitive processes in source monitoring. They are specified within the statistical framework of multinomial processing tree models and differ in their assumptions on the storage and retrieval of multidimensional source information. In the present article, a hierarchical relationship is demonstrated between multinomial models for crossed source information ( Meiser & Bröder, 2002 ), for partial source memory ( Dodson, Holland, & Shimamura, 1998 ) and for several sources ( Batchelder, Hu, & Riefer, 1994 ). The hierarchical relationship allows model comparisons and facilitates the specification of identifiability conditions. Conditions for global identifiability are discussed, and model comparisons are illustrated by reanalyses and by a new experiment on the storage and retrieval of multidimensional source information.

River Quality Models for Consent Setting in England and Wales

1989 ◽  
Vol 21 (8-9) ◽  
pp. 1015-1024 ◽  
Author(s):  
C. P. Crockett ◽  
R. W. Crabtree ◽  
I. D. Cluckie
Keyword(s):  
River System ◽  
Quality Model ◽  
Catchment Scale ◽  
Quality Models ◽  
England And Wales ◽  
Future Developments ◽  
Statistical Framework ◽  
River Quality ◽  
National Approach

In England and Wales the placing of effluent discharge consents within a statistical framework has led to the development of a new hybrid type of river quality model. Such catchment scale consent models have a stochastic component for the generation of model inputs and a deterministic component to route them through the river system. This paper reviews and compares the existing approaches for consent modelling used by various Water Authorities. A number of possible future developments are suggested including the potential need for a national approach to the review and setting of long term consents.

Redefining ‘Industry’: Young People and Cultural Policy in Australia

1999 ◽  
Vol 90 (1) ◽  
pp. 123-138 ◽  
Author(s):  
Mary Ann Hunter
Keyword(s):  
Young People ◽  
Cultural Policy ◽  
Culture Industry ◽  
Cultural Development ◽  
New Paradigm ◽  
Community Based ◽  
Policy Responses ◽  
Statistical Framework ◽  
Leisure Industry

This article considers the place of youth arts and cultures in the cultural industries approach to cultural policy. It argues that the ‘covert economic overlay’ (Brokensha, 1996: 101) of the Australian National Culture–Leisure Industry Statistical Framework privileges certain processes in a ‘government convenient’ model of industry inputs and outcomes, and that the assumptions of this model are challenged by youth-specific and community-based modes of production. Furthermore, it argues that the philosophies and practices of contemporary youth-specific arts organisations have the potential to redefine ‘culture industry’ and contribute to a ‘coherent new paradigm’ of cultural policy (UNESCO, 1995: 232). This paper makes these arguments by examining the place of youth arts and cultures in the existing environment of cultural industrialisation, by considering recent government policy responses to young people's cultural activity and by addressing long-term policy issues for the support of young people and cultural development.

Revision of Banded Knifefishes of the Gymnotus carapo and G. tigre clades (Gymnotidae Gymnotiformes) from the Southern Neotropics

Zootaxa ◽  
2018 ◽  
Vol 4379 (1) ◽  
pp. 47 ◽  
Author(s):  
JACK M. CRAIG ◽  
LUIZ R. MALABARBA ◽  
WILLIAM G. R. CRAMPTON ◽  
JAMES S. ALBERT
Keyword(s):  
Lateral Line ◽  
Electric Organ ◽  
Valid Species ◽  
Species Boundaries ◽  
Multivariate Statistical ◽  
Widespread Species ◽  
Statistical Framework ◽  
Fin Ray ◽  
Taxonomic Confusion ◽  
Electric Organ Discharges

Banded Knifefishes (Gymnotus, Gymnotidae) comprise the most species-rich, ecologically tolerant (eurytopic), and geographically widespread genus of Neotropical electric fishes (Gymnotiformes), with 40 valid species occupying most habitats and regions throughout the humid Neotropics. Despite substantial alpha-taxonomic work in recent years, parts of the genus remain characterized by taxonomic confusion. Here we describe and delimit species of the G. carapo and G. tigre clades from the southern Neotropics, using body proportions (caliper-based morphometrics), fin-ray, scale and laterosensory-pore counts (meristics), quantitative shape differences (geometric morphometrics), osteology, color patterns and electric organ discharges. We report these data from 174 Gymnotus specimens collected from 100 localities throughout the southern Neotropics, and delimit species boundaries in a multivariate statistical framework. We find six species of the G. carapo clade (G. carapo australis, G. cuia n. sp., G. chimarrao, G. omarorum, G. pantanal, and G. sylvius), and two species of the G. tigre clade (G. inaequilabiatus and G. paraguensis) in the southern Neotropics. The new species G. cuia is readily distinguished from the morphologically similar and broadly sympatric G. c. australis by a shorter head and deeper head and body, and from the morphologically similar and sympatric G. omarorum by fewer lateral-line ventral rami and fewer pored lateral-line scales anterior to the first ventral ramus. We also review the geographic distributions of all eight species of the G. carapo and G. tigre clades in the southern Neotropics, showing that G. cuia is the most widespread species in the region. These results affirm the importance of understanding the structure of variation within and between species, both geographic and ontogenetic, in delimiting species boundaries. 

scholarly journals Different environmental variables predict body and brain size evolution in Homo

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Manuel Will ◽  
Mario Krapp ◽  
Jay T. Stock ◽  
Andrea Manica
Keyword(s):  
Environmental Factors ◽  
Cognitive Abilities ◽  
Net Primary Productivity ◽  
Brain Size ◽  
Environmental Influence ◽  
Size Variation ◽  
Evolutionary Pattern ◽  
Statistical Framework ◽  
Size Evolution ◽  
Major Predictor

AbstractIncreasing body and brain size constitutes a key macro-evolutionary pattern in the hominin lineage, yet the mechanisms behind these changes remain debated. Hypothesized drivers include environmental, demographic, social, dietary, and technological factors. Here we test the influence of environmental factors on the evolution of body and brain size in the genus Homo over the last one million years using a large fossil dataset combined with global paleoclimatic reconstructions and formalized hypotheses tested in a quantitative statistical framework. We identify temperature as a major predictor of body size variation within Homo, in accordance with Bergmann’s rule. In contrast, net primary productivity of environments and long-term variability in precipitation correlate with brain size but explain low amounts of the observed variation. These associations are likely due to an indirect environmental influence on cognitive abilities and extinction probabilities. Most environmental factors that we test do not correspond with body and brain size evolution, pointing towards complex scenarios which underlie the evolution of key biological characteristics in later Homo.

scholarly journals MegaLMM: Mega-scale linear mixed models for genomic predictions with thousands of traits

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Daniel E. Runcie ◽  
Jiayi Qu ◽  
Hao Cheng ◽  
Lorin Crawford
Keyword(s):  
Genomic Prediction ◽  
Large Scale ◽  
Mixed Model ◽  
Human Genetics ◽  
Linear Mixed Effect Model ◽  
Mixed Effect ◽  
Statistical Framework ◽  
Effect Model ◽  
Plant Data ◽  
Genetic Value

AbstractLarge-scale phenotype data can enhance the power of genomic prediction in plant and animal breeding, as well as human genetics. However, the statistical foundation of multi-trait genomic prediction is based on the multivariate linear mixed effect model, a tool notorious for its fragility when applied to more than a handful of traits. We present , a statistical framework and associated software package for mixed model analyses of a virtually unlimited number of traits. Using three examples with real plant data, we show that can leverage thousands of traits at once to significantly improve genetic value prediction accuracy.

scholarly journals EPCO-23. COMPARATIVE TRANSCRIPTOMICS TO IDENTIFY TARGETED THERAPY CANDIDATES IN HIGH GRADE GLIOMA

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii74-ii74
Author(s):  
Kelsey Hundley ◽  
Olena Vaske ◽  
Geoff Lyle ◽  
Katrina Learned ◽  
Holly Beale ◽  
...  
Keyword(s):  
Targeted Therapy ◽  
Therapeutic Targets ◽  
High Grade Glioma ◽  
Comparative Transcriptomics ◽  
Potential Candidate ◽  
High Grade ◽  
Illumina Hiseq ◽  
Li Fraumeni Syndrome ◽  
Statistical Framework ◽  
Genomic Characterization

Abstract Genomic characterization is often used for the identification of therapeutic targets in tumors. Recently, comparative transcriptomics has begun to be utilized for this purpose. In this pilot, we compare the transcriptome of a patient with recurrent high grade glioma (HGG) to our cohort to identify potential therapies. We reviewed transcriptomic profiles from patients who had resection of HGG at our institution over the past year as well as the UCSC cancer compendium. Briefly, tumor RNA was extracted from embedded tumor tissue sections with tumor cellularity higher than 20%. RNA libraries were sequenced to obtain approximately 65 million reads on an Illumina HiSeq 4000 System utilizing patterned flow cell technology. The RNA profile of a 24 male with Li-Fraumeni syndrome and recurrent HGG with leptomeningeal spread underwent comparative transcriptomics to identify targets. A Bayesian statistical framework for gene expression outlier detection was used. These comparisons allowed for the identification of genes and pathways that are significantly overexpressed. Our internal HGG cohort consisted of 44 adult patients and was evenly distributed among the 4 HGG Verhaak subtypes. Our patient of interest had druggable outlier expression in HDAC1, STAT1 and STAT2 in comparison to our internal cohort indicating vorinostat and ruxolitinib as potential therapies, respectively. We then compared our patient of interest to 12,747 patients in the cancer compendium and STAT2 expression was high but not an outlier. In comparison to 738 glioma samples, STAT1 and STAT2 were outliers but not HDAC1 again indicating ruxolitinib as a potential targeted therapy. The patient did not have outlier expression in notch transcriptional targets or immune checkpoint biomarkers when compared to all cohorts. In conclusion, comparative Transcriptomics can identify therapeutic targets in a patient with recurrent HGG even in small cohorts. In our pilot, we identified ruxolitinib as a potential candidate to treat leptomeningeal recurrence.

scholarly journals A Microsatellite Genotyping-Based Genetic Study of Interspecific Hybridization between the Red and Sika Deer in the Western Czech Republic

Animals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1701
Author(s):  
Lenka Štohlová Putnová ◽  
Radek Štohl ◽  
Martin Ernst ◽  
Kateřina Svobodová
Keyword(s):  
Red Deer ◽  
Sika Deer ◽  
Molecular Genetic ◽  
Allelic Diversity ◽  
Molecular Genetic Analysis ◽  
Genetic Introgression ◽  
Statistical Framework ◽  
Western Bohemia ◽  
The Mean ◽  
Species Hybrids

Although inter-species hybrids between the red and sika deer can be phenotypically determined only exceptionally, there is the eventuality of identification via molecular genetic analysis. We used bi-parentally inherited microsatellite markers and a Bayesian statistical framework to re-examine the proportion of hybrids in the Czech red and sika deer populations. In total, 123 samples were collected, and the nuclear dataset consisted of 2668 allelic values. The number of alleles per locus ranged from 10 (BM1818) to 22 (BM888 and T193), yielding the mean of 16 alleles per locus across the deer. The mean allelic diversity of the red deer markedly exceeded that of the Japanese sika deer. Interspecific hybrids were detected, enabling us to confirm the genetic introgression of the sika deer into the red deer populations and vice versa in western Bohemia. The mean hybrid score equaled 10.6%, with 14.3% of the hybrids being among red deer–like individuals and 6.7% among sika-like ones. At two western Bohemian locations, namely, Doupovské hory and Slavkovský les, the total percentages of hybrid animals equaled 18.8 and 8.9, respectively. No red deer alleles were detected in the sika populations of the subregions of Kladská, Žlutice, and Lány. The NeighborNet network clearly separated the seven red and sika deer sampling populations according to the geography. The knowledge gained from the evaluated data is applicable in hunting management to reduce hybridization with the European deer.

scholarly journals InfPolyn, a Nonparametric Bayesian Characterization for Composition-Dependent Interdiffusion Coefficients

Materials ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3635
Author(s):  
Wei-W. Xing ◽  
Ming Cheng ◽  
Kaiming Cheng ◽  
Wei Zhang ◽  
Peng Wang
Keyword(s):  
Interdiffusion Coefficient ◽  
Diffusion Equations ◽  
Numerical Inversion ◽  
Extended Model ◽  
Parametric Form ◽  
Physical Processes ◽  
Large Margin ◽  
Statistical Framework ◽  
Fitting Method ◽  
Interdiffusion Coefficients

Composition-dependent interdiffusion coefficients are key parameters in many physical processes. However, finding such coefficients for a system with few components is challenging due to the underdetermination of the governing diffusion equations, the lack of data in practice, and the unknown parametric form of the interdiffusion coefficients. In this work, we propose InfPolyn, Infinite Polynomial, a novel statistical framework to characterize the component-dependent interdiffusion coefficients. Our model is a generalization of the commonly used polynomial fitting method with extended model capacity and flexibility and it is combined with the numerical inversion-based Boltzmann–Matano method for the interdiffusion coefficient estimations. We assess InfPolyn on ternary and quaternary systems with predefined polynomial, exponential, and sinusoidal interdiffusion coefficients. The experiments show that InfPolyn outperforms the competitors, the SOTA numerical inversion-based Boltzmann–Matano methods, with a large margin in terms of relative error (10x more accurate). Its performance is also consistent and stable, whereas the number of samples required remains small.

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