scholarly journals crestr An R package to perform probabilistic climate reconstructions using fossil proxies

2021 ◽  
Author(s):  
Manuel Chevalier
Keyword(s):  
R Package ◽  
Climate Reconstruction ◽  
Diagnostic Tools ◽  
Calibration Data ◽  
Reconstruction Process ◽  
Climate Reconstructions ◽  
Reconstruction Software ◽  
Modelling Assumptions ◽  
The Many ◽  
Data Collections

Abstract. Statistical climate reconstruction techniques are practical tools to study past climate variability from fossil proxy data. In particular, the methods based on probability density functions (PDFs) are powerful at producing robust results from various environments and proxies. However, accessing and curating the necessary calibration data, as well as the complexity of interpreting probabilistic results, often limit their use in palaeoclimatological studies. To address these problems, I present a new R package (crestr) to apply the CREST method (Climate REconstruction SofTware) on diverse palaeoecological datasets. crestr includes a globally curated calibration dataset for six common climate proxies (i.e. plants, beetles, chironomids, rodents, foraminifera, and dinoflagellate cysts) that enables its use in most terrestrial and marine regions. The package can also be used with private data collections instead of, or in combination with, the provided dataset. It also includes a suite of graphical diagnostic tools to represent the data at each step of the reconstruction process and provide insights into the effect of the different modelling assumptions and external factors that underlie a reconstruction. With this R package, the CREST method can now be used in a scriptable environment, thus simplifying its use and integration in existing workflows. It is hoped that crestr will contribute to producing the much-needed quantified records from the many regions where climate reconstructions are currently lacking, despite the existence of suitable fossil records.

MEDICAL FILMS

PEDIATRICS ◽  
1962 ◽  
Vol 30 (6) ◽  
pp. 1018-1018
Keyword(s):  
Cystic Fibrosis ◽  
New York ◽  
New York City ◽  
Differential Diagnosis ◽  
Correct Diagnosis ◽  
Diagnostic Tools ◽  
Single Test ◽  
Presenting Symptoms ◽  
The Many ◽  
Therapy And Diagnosis

Cystic Fibrosis—NCFRF. 16 mm., color, sound, showing time 32 minutes. Produced in 1961 by Samuel L. Schulman for the National Cystic Fibrosis Research Foundation, medical supervision by Giulio J. Barbero, M.D. Philadelphia. Procurable on purchase from National Cystic Fibrosis Research Foundation, 521 Fifth Avenue, New York City 17. Procurable on loan from American Medical Association, Motion Picture Library, 535 N. Dearborn Street, Chicago 10. This film has been prepared to aid physicians in making a correct diagnosis and to instruct them in the techniques currently being used to prolong life in cases of cystic fibrosis. Following the introductoy remarks there is a good discussion of the presenting symptoms, the differential diagnosis, the multiple system involvement, hereditary aspects, therapy, and prognosis. The film brings out well the panexocrine involvement, the clinical variability, and the fact that the disease is not an all or none phenomenon but rather a disease of all grades of severity and is a disease in which no single test is applicable to the exclusion of others. The diagrams and patient demonstrations are good. Perhaps too much review of older methods of therapy and diagnosis is given, but this serves as a background for the newer recommended procedures. More emphasis could have been given to the tremendous burden, both financial and emotional, this disease is on parents. This is an excellent instructive film and it emphasizes the many problems of cystic fibrosis as related to the diagnostic tools available and to forms of therapy. The photography and sound are satisfactory. It is recommended for pediatricians, general practitioners, house staff, and medical students.

scholarly journals Monitoring Robust Estimates for Compositional Data

2021 ◽  
Vol 50 (2) ◽  
pp. 16-37
Author(s):  
Valentin Todorov
Keyword(s):  
Compositional Data ◽  
Real Life ◽  
R Package ◽  
Diagnostic Tools ◽  
Data Set ◽  
Mahalanobis Distances ◽  
Robust Estimates ◽  
Real Life Data ◽  
Manufactured Exports ◽  
Parameter Values

In a number of recent articles Riani, Cerioli, Atkinson and others advocate the technique of monitoring robust estimates computed over a range of key parameter values. Through this approach the diagnostic tools of choice can be tuned in such a way that highly robust estimators which are as efficient as possible are obtained. This approach is applicable to various robust multivariate estimates like S- and MM-estimates, MVE and MCD as well as to the Forward Search in whichmonitoring is part of the robust method. Key tool for detection of multivariate outliers and for monitoring of robust estimates is the Mahalanobis distances and statistics related to these distances. However, the results obtained with thistool in case of compositional data might be unrealistic since compositional data contain relative rather than absolute information and need to be transformed to the usual Euclidean geometry before the standard statistical tools can be applied. Various data transformations of compositional data have been introduced in the literature and theoretical results on the equivalence of the additive, the centered, and the isometric logratio transformation in the context of outlier identification exist. To illustrate the problem of monitoring compositional data and to demonstrate the usefulness of monitoring in this case we start with a simple example and then analyze a real life data set presenting the technologicalstructure of manufactured exports. The analysis is conducted with the R package fsdaR, which makes the analytical and graphical tools provided in the MATLAB FSDA library available for R users.

scholarly journals Diagnosing a 12-Item Dataset of Raven Matrices: With Dexter

2020 ◽  
Vol 8 (2) ◽  
pp. 21 ◽  
Author(s):  
Ivailo Partchev
Keyword(s):  
R Package ◽  
Diagnostic Tools ◽  
Not Given ◽  
Test Functions ◽  
Sum Score ◽  
Raven's Standard Progressive Matrices

We analyze a 12-item version of Raven’s Standard Progressive Matrices test, traditionally scored with the sum score. We discuss some important differences between assessment in practice and psychometric modelling. We demonstrate some advanced diagnostic tools in the freely available R package, dexter. We find that the first item in the test functions badly—at a guess, because the subjects were not given exercise items before the live test.

Gene-based association tests using GWAS summary statistics

2019 ◽  
Vol 35 (19) ◽  
pp. 3701-3708 ◽  
Author(s):  
Gulnara R Svishcheva ◽  
Nadezhda M Belonogova ◽  
Irina V Zorkoltseva ◽  
Anatoly V Kirichenko ◽  
Tatiana I Axenovich
Keyword(s):  
Association Analysis ◽  
Association Studies ◽  
R Package ◽  
Supplementary Information ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
New Material ◽  
Artery Disease ◽  
The Many ◽  
Functional Linear Regression

Abstract Motivation A huge number of genome-wide association studies (GWAS) summary statistics freely available in databases provide a new material for gene-based association analysis aimed at identifying rare genetic variants. Only a few of the many popular gene-based methods developed for individual genotype and phenotype data are adapted for the practical use of the GWAS summary statistics as input. Results We analytically prove and numerically illustrate that all popular powerful methods developed for gene-based association analysis of individual phenotype and genotype data can be modified to utilize GWAS summary statistics. We have modified and implemented all of the popular methods, including burden and kernel machine-based tests, multiple and functional linear regression, principal components analysis and others, in the R package sumFREGAT. Using real summary statistics for coronary artery disease, we show that the new package is able to detect genes not found by the existing packages. Availability and implementation The R package sumFREGAT is freely and publicly available at: https://CRAN.R-project.org/package=sumFREGAT. Supplementary information Supplementary data are available at Bioinformatics online.

Image super-resolution based on multi-grained cascade forests

2019 ◽  
Vol 17 (04) ◽  
pp. 1950019
Author(s):  
Yaming Wang ◽  
Zhikang Luo ◽  
Weqing Huang ◽  
Yonghua Han
Keyword(s):  
Super Resolution ◽  
Image Features ◽  
Divide And Conquer ◽  
Learning Ability ◽  
Generalization Capability ◽  
Reconstruction Process ◽  
High Quality Image ◽  
Reconstruction Quality ◽  
Image Super Resolution ◽  
The Many

Although neural networks are most commonly used in the field of image super-resolution (SR), methods based on decision trees are still discussed. These kinds of algorithm need less time to compute than others because of their simple structure but still yield high quality image SR. In this paper, we propose an SR algorithm using the multi-grained cascade forest (SRGCF) method. Our algorithm first uses multi-grained scanning to process the spatial relationships of image features, thus the representational learning ability is improved. During the reconstruction process, the image obtained by cascade forest training is used as the input of the next training, therefore, the image features are continuously emphasized. The training of the cascade forest ends when the evaluation value is optimal. Because the decision tree uses a divide-and-conquer strategy, the SR of an image is improved in an iterative manner simply and quickly. Compared with existing methods, our method not only avoids the tradeoff between reconstruction quality and run time, but also has a good generalization capability. It can be quickly applied to the many cases of image SR.

scholarly journals Sedproxy: a forward model for sediment archived climate proxies

2018 ◽  
Author(s):  
Andrew M. Dolman ◽  
Thomas Laepple
Keyword(s):  
R Package ◽  
Forward Model ◽  
Recorded Signal ◽  
Proxy Records ◽  
Climate Reconstructions ◽  
Reconstruction Methods ◽  
Geochemical Parameters ◽  
Many Sources ◽  
User Friendly ◽  
Climate Proxies

Abstract. Climate reconstructions based on proxy records recovered from marine sediments, such as alkenone records or geochemical parameters measured on foraminifera, play an important role in our understanding of the climate system. They provide information about the state of the ocean ranging back hundreds to millions of years and form the backbone of paleo-oceanography. However, there are many sources of uncertainty associated with the signal recovered from sediment archived proxies. These include seasonal or depth habitat biases in the recorded signal, a frequency dependent reduction in the amplitude of the recorded signal due to bioturbation of the sediment, aliasing of high frequency climate variation onto a nominally annual, decadal or centennial resolution signal, and additional sample processing and measurement error introduced when the proxy signal is recovered. Here we present a forward model for sediment archived proxies that jointly models the above processes, so that the magnitude of their separate and combined effects can be investigated. Applications include the interpretation and analysis of uncertainty in existing proxy records, parameter sensitivity analysis to optimize future studies, and the generation of pseudo-proxy records that can be used to test reconstruction methods. We provide examples, such as the simulation of individual foraminifera records, that demonstrate the usefulness of the forward model for paleoclimate studies. The model is implemented as a user-friendly R package, sedproxy, the use of which we hope will contribute to a better understanding of both the limitations and potential of marine sediment proxies to inform about past climate.

Hypoxia in cancer cell metabolism and pH regulation

2007 ◽  
Vol 43 ◽  
pp. 165-178 ◽  
Author(s):  
M. Christiane Brahimi-Horn ◽  
Jacques Pouysségur
Keyword(s):  
Cancer Cells ◽  
Ph Regulation ◽  
Cell Metabolism ◽  
Hypoxia Inducible Factor ◽  
Diagnostic Tools ◽  
Tumour Mass ◽  
Cellular Functions ◽  
Α Subunit ◽  
The Many ◽  
High Level

At a molecular level, hypoxia induces the stabilization and activation of the α-subunit of an α/β heterodimeric transcription factor, appropriately termed HIF (hypoxia-inducible factor). Hypoxia is encountered, in particular, in tumour tissues, as a result of an insufficient and defective vasculature present in a highly proliferative tumour mass. In this context the active HIF heterodimer binds to and induces a panel of genes that lead to modification in a vast range of cellular functions that allow cancer cells to not only survive but to continue to proliferate and metastasize. Therefore HIF plays a key role in tumorigenesis, tumour development and metastasis, and its expression in solid tumours is associated with a poor patient outcome. Among the many genes induced by HIF are genes responsible for glucose transport and glucose metabolism. The products of these genes allow cells to adapt to cycles of hypoxic stress by maintaining a level of ATP sufficient for survival and proliferation. Whereas normal cells metabolize glucose through a cytoplasmic- and mitochondrial-dependent pathway, cancer cells preferentially use a cytoplasmic, glycolytic pathway that leads to an increased acid load due, in part, to the high level of production of lactic acid. This metabolic predilection of cancer cells is primarily dependent directly on the HIF activity but also indirectly through changes in the activity of tumour suppressors and oncogenes. A better understanding of HIF-dependent metabolism and pH regulation in cancer cells should lead to further development of diagnostic tools and novel therapeutics that will bring benefit to cancer patients.

scholarly journals CREST (Climate REconstruction SofTware): a probability density function (PDF)-based quantitative climate reconstruction method

2014 ◽  
Vol 10 (6) ◽  
pp. 2081-2098 ◽  
Author(s):  
M. Chevalier ◽  
R. Cheddadi ◽  
B. M. Chase
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
Climate Reconstruction ◽  
Climatic Variables ◽  
Pollen Data ◽  
Pollen Type ◽  
Temperature And Precipitation ◽  
Reconstruction Software ◽  
Probability Density Function Pdf

Abstract. Several methods currently exist to quantitatively reconstruct palaeoclimatic variables from fossil botanical data. Of these, probability density function (PDF)-based methods have proven valuable as they can be applied to a wide range of plant assemblages. Most commonly applied to fossil pollen data, their performance, however, can be limited by the taxonomic resolution of the pollen data, as many species may belong to a given pollen type. Consequently, the climate information associated with different species cannot always be precisely identified, resulting in less-accurate reconstructions. This can become particularly problematic in regions of high biodiversity. In this paper, we propose a novel PDF-based method that takes into account the different climatic requirements of each species constituting the broader pollen type. PDFs are fitted in two successive steps, with parametric PDFs fitted first for each species and then a combination of those individual species PDFs into a broader single PDF to represent the pollen type as a unit. A climate value for the pollen assemblage is estimated from the likelihood function obtained after the multiplication of the pollen-type PDFs, with each being weighted according to its pollen percentage. To test its performance, we have applied the method to southern Africa as a regional case study and reconstructed a suite of climatic variables (e.g. winter and summer temperature and precipitation, mean annual aridity, rainfall seasonality). The reconstructions are shown to be accurate for both temperature and precipitation. Predictable exceptions were areas that experience conditions at the extremes of the regional climatic spectra. Importantly, the accuracy of the reconstructed values is independent of the vegetation type where the method is applied or the number of species used. The method used in this study is publicly available in a software package entitled CREST (Climate REconstruction SofTware) and will provide the opportunity to reconstruct quantitative estimates of climatic variables even in areas with high geographical and botanical diversity.

scholarly journals The influence of decision-making in tree ring-based climate reconstructions

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ulf Büntgen ◽  
Kathy Allen ◽  
Kevin J. Anchukaitis ◽  
Dominique Arseneault ◽  
Étienne Boucher ◽  
...  
Keyword(s):  
Tree Ring ◽  
Ring Width ◽  
Volcanic Eruptions ◽  
Double Blind ◽  
Reconstruction Process ◽  
Climate Reconstructions ◽  
The Common ◽  
Common Era ◽  
Mean Variance ◽  
Large Volcanic Eruptions

AbstractTree-ring chronologies underpin the majority of annually-resolved reconstructions of Common Era climate. However, they are derived using different datasets and techniques, the ramifications of which have hitherto been little explored. Here, we report the results of a double-blind experiment that yielded 15 Northern Hemisphere summer temperature reconstructions from a common network of regional tree-ring width datasets. Taken together as an ensemble, the Common Era reconstruction mean correlates with instrumental temperatures from 1794–2016 CE at 0.79 (p < 0.001), reveals summer cooling in the years following large volcanic eruptions, and exhibits strong warming since the 1980s. Differing in their mean, variance, amplitude, sensitivity, and persistence, the ensemble members demonstrate the influence of subjectivity in the reconstruction process. We therefore recommend the routine use of ensemble reconstruction approaches to provide a more consensual picture of past climate variability.

Exploring Fan Behavior: Developing a Scale to Measure Sport eFANgelism

2015 ◽  
Vol 29 (6) ◽  
pp. 642-656 ◽  
Author(s):  
Brendan Dwyer ◽  
Gregory P. Greenhalgh ◽  
Carrie W. LeCrom
Keyword(s):  
Step Method ◽  
Sport Fans ◽  
Sport Team ◽  
Fan Behavior ◽  
Spectator Sport ◽  
The Spectator ◽  
The Many ◽  
Data Collections ◽  
Team Brand ◽  
Brand Evangelism

Brand evangelism, an advanced form of marketing where consumers voluntarily advocate on behalf of the brand, can bring numerous benefits to a firm. Pro-brand behaviors such as word-of-mouth promotion, recruitment of consumers, and disparagement of rivals are just a few of the many actions associated with brand evangelism. With highly impassioned and provocative fans, an opportunity exists to explore brand evangelism within the spectator sport context. The purpose of this study was to develop and validate a scale to measure sport team (brand) evangelism. Guided by Fournier’s (1998) brand extension of relationship theory and following Churchill’s (1979) eight-step method for developing marketing measures, two focus groups of fans were interviewed and an additional 450 sport fans were surveyed through two distinct data collections in an attempt to identify sport team evangelistic behaviors, and test a measure of such behaviors. The assessment of the instrument included two forms of reliability analysis and three modes of validity analysis as the scale was parsimoniously reduced from 88 initial behaviors to four factors and 14 items.

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