Character selection and the quantification of morphological disparity

AbstractA priori choices in the detail and breadth of a study are important in addressing scientific hypotheses. In particular, choices in the number and type of characters can greatly influence the results in studies of morphological diversity. A new character suite was constructed to examine trends in the disparity of early Paleozoic crinoids. Character-based rarefaction analysis indicated that a small subset of these characters (~20% of the complete data set) could be used to capture most of the properties of the entire data set in analyses of crinoids as a whole, noncamerate crinoids, and to a lesser extent camerate crinoids. This pattern may be the result of the covariance between characters and the characterization of rare morphologies that are not represented in the primary axes in morphospace. Shifting emphasis on different body regions (oral system, calyx, periproct system, and pelma) also influenced estimates of relative disparity between subclasses of crinoids. Given these results, morphological studies should include a pilot analysis to better examine the amount and type of data needed to address specific scientific hypotheses.

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Estimating the Support of a High-Dimensional Distribution

Neural Computation ◽

10.1162/089976601750264965 ◽

2001 ◽

Vol 13 (7) ◽

pp. 1443-1471 ◽

Cited By ~ 2293

Author(s):

Bernhard Schölkopf ◽

John C. Platt ◽

John Shawe-Taylor ◽

Alex J. Smola ◽

Robert C. Williamson

Keyword(s):

A Priori ◽

Natural Extension ◽

Feature Space ◽

Weight Vector ◽

Test Point ◽

Training Data ◽

Sequential Optimization ◽

Support Vector ◽

Small Subset ◽

Data Set

Suppose you are given some data set drawn from an underlying probability distribution P and you want to estimate a “simple” subset S of input space such that the probability that a test point drawn from P lies outside of S equals some a priori specified value between 0 and 1. We propose a method to approach this problem by trying to estimate a function f that is positive on S and negative on the complement. The functional form of f is given by a kernel expansion in terms of a potentially small subset of the training data; it is regularized by controlling the length of the weight vector in an associated feature space. The expansion coefficients are found by solving a quadratic programming problem, which we do by carrying out sequential optimization over pairs of input patterns. We also provide a theoretical analysis of the statistical performance of our algorithm. The algorithm is a natural extension of the support vector algorithm to the case of unlabeled data.

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High-resolution geophysical characterization of shallow-water wetlands

Geophysics ◽

10.1190/1.2210307 ◽

2006 ◽

Vol 71 (4) ◽

pp. B101-B109 ◽

Cited By ~ 14

Author(s):

Nasser Mansoor ◽

Lee Slater ◽

Francisco Artigas ◽

Esben Auken

Keyword(s):

Surface Water ◽

Shallow Water ◽

A Priori ◽

Aerial Photographs ◽

Inversion Algorithm ◽

Data Set ◽

Surface Water Chemistry ◽

Sources Of Pollution ◽

Magnetic Gradiometry

We describe a procedure for rapid characterization of shallow-water, contaminated wetlands. Terrain-conductivity (TC), vertical-magnetic-gradiometry, and surface-water-chemistry data were obtained from a shallow-draft paddleboat operable in as little as [Formula: see text] of water. Measurements were taken every [Formula: see text], with data-acquisition rates exceeding [Formula: see text] of line ([Formula: see text] data points) per 8-hr field day. We applied this procedure to an urban wetland that is affected by point and nonpoint sources of pollution. We used a one-dimensional, laterally constrained inversion algorithm to invert the apparent-conductivity data set obtained from the TC survey and to create a pseudo-2D image of sediment conductivity. The continuously recorded surface-water depth and conductivity values were input as a priori information in the inversion. We used soil chemistry determined for 28 sediment samples collected from the site, as well as lithologic logs from across the wetland, to constrain interpretation of the geophysical data. The inverted sediment conductivity describes a pattern of contamination probably attributable to leachates from adjacent landfills and/or to saltwater ingress from a partial tidal connection that is not obvious in the surface-water data. Magnetic-gradiometry values and the in-phase component of an EM31 response both reflect primarily the distribution of junk metal associated with a legacy of illegal dumping. Historic aerial photographs suggest that this distribution reflects land-use history and defines the maximum previous extent of an adjacent landfill and a pattern of dumping correlated with historic roadways.

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Diversity of Cowpea [Vigna unguiculata (L.) Walp] Landraces in Mozambique: New Opportunities for Crop Improvement and Future Breeding Programs

Agronomy ◽

10.3390/agronomy11050991 ◽

2021 ◽

Vol 11 (5) ◽

pp. 991

Author(s):

Ana Maria Figueira Gomes ◽

David Draper ◽

Nascimento Nhantumbo ◽

Rafael Massinga ◽

José C. Ramalho ◽

...

Keyword(s):

Vigna Unguiculata ◽

Production Systems ◽

Crop Improvement ◽

Morphological Diversity ◽

Ecological Zones ◽

Nutrition Security ◽

Food And Nutrition ◽

High Level ◽

Nutrition Sensitive

Cowpea (Vigna unguiculata) is a neglected crop native to Africa, with an outstanding potential to contribute to the major challenges in food and nutrition security, as well as in agricultural sustainability. Two major issues regarding cowpea research have been highlighted in recent years—the establishment of core collections and the characterization of landraces—as crucial to the implementation of environmentally resilient and nutrition-sensitive production systems. In this work, we have collected, mapped, and characterized the morphological attributes of 61 cowpea genotypes, from 10 landraces spanning across six agro-ecological zones and three provinces in Mozambique. Our results reveal that local landraces retain a high level of morphological diversity without a specific geographical pattern, suggesting the existence of gene flow. Nevertheless, accessions from one landrace, i.e., Maringué, seem to be the most promising in terms of yield and nutrition-related parameters, and could therefore be integrated into the ongoing conservation and breeding efforts in the region towards the production of elite varieties of cowpea.

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A Traveler’s Guide to the Multiverse: Promises, Pitfalls, and a Framework for the Evaluation of Analytic Decisions

Advances in Methods and Practices in Psychological Science ◽

10.1177/2515245920954925 ◽

2021 ◽

Vol 4 (1) ◽

pp. 251524592095492

Author(s):

Marco Del Giudice ◽

Steven W. Gangestad

Keyword(s):

Degrees Of Freedom ◽

A Priori ◽

Simulated Data ◽

Style Analysis ◽

Data Set ◽

Scant Attention ◽

Equivalence Type ◽

The Impact ◽

Biased Estimates

Decisions made by researchers while analyzing data (e.g., how to measure variables, how to handle outliers) are sometimes arbitrary, without an objective justification for choosing one alternative over another. Multiverse-style methods (e.g., specification curve, vibration of effects) estimate an effect across an entire set of possible specifications to expose the impact of hidden degrees of freedom and/or obtain robust, less biased estimates of the effect of interest. However, if specifications are not truly arbitrary, multiverse-style analyses can produce misleading results, potentially hiding meaningful effects within a mass of poorly justified alternatives. So far, a key question has received scant attention: How does one decide whether alternatives are arbitrary? We offer a framework and conceptual tools for doing so. We discuss three kinds of a priori nonequivalence among alternatives—measurement nonequivalence, effect nonequivalence, and power/precision nonequivalence. The criteria we review lead to three decision scenarios: Type E decisions (principled equivalence), Type N decisions (principled nonequivalence), and Type U decisions (uncertainty). In uncertain scenarios, multiverse-style analysis should be conducted in a deliberately exploratory fashion. The framework is discussed with reference to published examples and illustrated with the help of a simulated data set. Our framework will help researchers reap the benefits of multiverse-style methods while avoiding their pitfalls.

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Pan-cancer analysis of transcripts encoding novel open-reading frames (nORFs) and their potential biological functions

npj Genomic Medicine ◽

10.1038/s41525-020-00167-4 ◽

2021 ◽

Vol 6 (1) ◽

Cited By ~ 2

Author(s):

Chaitanya Erady ◽

Adam Boxall ◽

Shraddha Puntambekar ◽

N. Suhas Jagannathan ◽

Ruchi Chauhan ◽

...

Keyword(s):

Transcript Level ◽

Open Reading Frames ◽

The Cancer Genome Atlas ◽

Small Subset ◽

Cancer Tissue ◽

Post Translational Modifications ◽

Cancer Genome Atlas ◽

Systematic Identification ◽

Reading Frames

AbstractUncharacterized and unannotated open-reading frames, which we refer to as novel open reading frames (nORFs), may sometimes encode peptides that remain unexplored for novel therapeutic opportunities. To our knowledge, no systematic identification and characterization of transcripts encoding nORFs or their translation products in cancer, or in any other physiological process has been performed. We use our curated nORFs database (nORFs.org), together with RNA-Seq data from The Cancer Genome Atlas (TCGA) and Genotype-Expression (GTEx) consortiums, to identify transcripts containing nORFs that are expressed frequently in cancer or matched normal tissue across 22 cancer types. We show nORFs are subject to extensive dysregulation at the transcript level in cancer tissue and that a small subset of nORFs are associated with overall patient survival, suggesting that nORFs may have prognostic value. We also show that nORF products can form protein-like structures with post-translational modifications. Finally, we perform in silico screening for inhibitors against nORF-encoded proteins that are disrupted in stomach and esophageal cancer, showing that they can potentially be targeted by inhibitors. We hope this work will guide and motivate future studies that perform in-depth characterization of nORF functions in cancer and other diseases.

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MAX-DOAS observations of aerosols, formaldehyde and nitrogen dioxide in the Beijing area: comparison of two profile retrieval approaches

Atmospheric Measurement Techniques ◽

10.5194/amt-8-941-2015 ◽

2015 ◽

Vol 8 (2) ◽

pp. 941-963 ◽

Cited By ~ 47

Author(s):

T. Vlemmix ◽

F. Hendrick ◽

G. Pinardi ◽

I. De Smedt ◽

C. Fayt ◽

...

Keyword(s):

Standard Deviation ◽

A Priori ◽

Systematic Bias ◽

Aerosol Extinction ◽

Data Set ◽

Near Surface ◽

Beijing Area ◽

Least Squares Fit ◽

Relative Differences ◽

Good Agreement

Abstract. A 4-year data set of MAX-DOAS observations in the Beijing area (2008–2012) is analysed with a focus on NO2, HCHO and aerosols. Two very different retrieval methods are applied. Method A describes the tropospheric profile with 13 layers and makes use of the optimal estimation method. Method B uses 2–4 parameters to describe the tropospheric profile and an inversion based on a least-squares fit. For each constituent (NO2, HCHO and aerosols) the retrieval outcomes are compared in terms of tropospheric column densities, surface concentrations and "characteristic profile heights" (i.e. the height below which 75% of the vertically integrated tropospheric column density resides). We find best agreement between the two methods for tropospheric NO2 column densities, with a standard deviation of relative differences below 10%, a correlation of 0.99 and a linear regression with a slope of 1.03. For tropospheric HCHO column densities we find a similar slope, but also a systematic bias of almost 10% which is likely related to differences in profile height. Aerosol optical depths (AODs) retrieved with method B are 20% high compared to method A. They are more in agreement with AERONET measurements, which are on average only 5% lower, however with considerable relative differences (standard deviation ~ 25%). With respect to near-surface volume mixing ratios and aerosol extinction we find considerably larger relative differences: 10 ± 30, −23 ± 28 and −8 ± 33% for aerosols, HCHO and NO2 respectively. The frequency distributions of these near-surface concentrations show however a quite good agreement, and this indicates that near-surface concentrations derived from MAX-DOAS are certainly useful in a climatological sense. A major difference between the two methods is the dynamic range of retrieved characteristic profile heights which is larger for method B than for method A. This effect is most pronounced for HCHO, where retrieved profile shapes with method A are very close to the a priori, and moderate for NO2 and aerosol extinction which on average show quite good agreement for characteristic profile heights below 1.5 km. One of the main advantages of method A is the stability, even under suboptimal conditions (e.g. in the presence of clouds). Method B is generally more unstable and this explains probably a substantial part of the quite large relative differences between the two methods. However, despite a relatively low precision for individual profile retrievals it appears as if seasonally averaged profile heights retrieved with method B are less biased towards a priori assumptions than those retrieved with method A. This gives confidence in the result obtained with method B, namely that aerosol extinction profiles tend on average to be higher than NO2 profiles in spring and summer, whereas they seem on average to be of the same height in winter, a result which is especially relevant in relation to the validation of satellite retrievals.

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Magnetotelluric static shift: Estimation and removal using the cokriging method

Geophysics ◽

10.1190/1.2400625 ◽

2007 ◽

Vol 72 (1) ◽

pp. F25-F34 ◽

Cited By ~ 11

Author(s):

Benoit Tournerie ◽

Michel Chouteau ◽

Denis Marcotte

Keyword(s):

Apparent Resistivity ◽

A Priori ◽

Shift Factor ◽

Static Shift ◽

Geostatistical Model ◽

Data Set ◽

Resistivity Sounding ◽

The Difference ◽

Cross Variogram

We present and test a new method to correct for the static shift affecting magnetotelluric (MT) apparent resistivity sounding curves. We use geostatistical analysis of apparent resistivity and phase data for selected periods. For each period, we first estimate and model the experimental variograms and cross variogram between phase and apparent resistivity. We then use the geostatistical model to estimate, by cokriging, the corrected apparent resistivities using the measured phases and apparent resistivities. The static shift factor is obtained as the difference between the logarithm of the corrected and measured apparent resistivities. We retain as final static shift estimates the ones for the period displaying the best correlation with the estimates at all periods. We present a 3D synthetic case study showing that the static shift is retrieved quite precisely when the static shift factors are uniformly distributed around zero. If the static shift distribution has a nonzero mean, we obtained best results when an apparent resistivity data subset can be identified a priori as unaffected by static shift and cokriging is done using only this subset. The method has been successfully tested on the synthetic COPROD-2S2 2D MT data set and on a 3D-survey data set from Las Cañadas Caldera (Tenerife, Canary Islands) severely affected by static shift.

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A novel tropopause-related climatology of ozone profiles

Atmospheric Chemistry and Physics ◽

10.5194/acp-14-283-2014 ◽

2014 ◽

Vol 14 (1) ◽

pp. 283-299 ◽

Cited By ~ 12

Author(s):

V. F. Sofieva ◽

J. Tamminen ◽

E. Kyrölä ◽

T. Mielonen ◽

P. Veefkind ◽

...

Keyword(s):

Climate Model ◽

A Priori ◽

Stratospheric Aerosol ◽

Ozone Monitoring Instrument ◽

Earth Observing System ◽

Ozone Profile ◽

High Vertical Resolution ◽

Climate Model Simulations ◽

Longitudinal Variability

Abstract. A new ozone climatology, based on ozonesonde and satellite measurements, spanning the altitude region between the earth's surface and ~60 km is presented (TpO3 climatology). This climatology is novel in that the ozone profiles are categorized according to calendar month, latitude and local tropopause heights. Compared to the standard latitude–month categorization, this presentation improves the representativeness of the ozone climatology in the upper troposphere and the lower stratosphere (UTLS). The probability distribution of tropopause heights in each latitude–month bin provides additional climatological information and allows transforming/comparing the TpO3 climatology to a standard climatology of zonal mean ozone profiles. The TpO3 climatology is based on high-vertical-resolution measurements of ozone from the satellite-based Stratospheric Aerosol and Gas Experiment II (in 1984 to 2005) and from balloon-borne ozonesondes from 1980 to 2006. The main benefits of the TpO3 climatology are reduced standard deviations on climatological ozone profiles in the UTLS, partial characterization of longitudinal variability, and characterization of ozone profiles in the presence of double tropopauses. The first successful application of the TpO3 climatology as a priori in ozone profile retrievals from Ozone Monitoring Instrument on board the Earth Observing System (EOS) Aura satellite shows an improvement of ozone precision in UTLS of up to 10% compared with the use of conventional climatologies. In addition to being advantageous for use as a priori in satellite retrieval algorithms, the TpO3 climatology might be also useful for validating the representation of ozone in climate model simulations.

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Data set on the characterization of the phytoestrogenic extract and isolated compounds of the roots of Inula racemosa Hook F (Asteraceae)

Data in Brief ◽

10.1016/j.dib.2018.02.004 ◽

2018 ◽

Vol 17 ◽

pp. 770-773

Author(s):

Mangathayaru Kalachaveedu ◽

Divya Raghavan ◽

Srivani Telapolu ◽

Sarah Kuruvilla ◽

Balakrishna Kedike

Keyword(s):

Data Set ◽

Inula Racemosa

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Combining remote sensing and hydrological information for improving hydrological characterization of dehesas in Mediterranean mountain areas: a study case in Cardeña-Montoro Natural Park (Spain)

10.5194/egusphere-egu21-10898 ◽

2021 ◽

Author(s):

Rafael Pimentel ◽

Pedro Torralbo ◽

Javier Aparicio ◽

María José Pérez-Palazón ◽

Ana Andreu ◽

...

Keyword(s):

Remote Sensing ◽

Heat Waves ◽

A Priori ◽

Regional Government ◽

Livestock Farming ◽

Spatiotemporal Resolution ◽

Mountain Areas ◽

Natural Park ◽

Mediterranean Shrubs

Mediterranean mountain areas are especially vulnerable to changes. Climatic trends observed in the last decades point out to an increasing number of extreme events (i.e., number of heat waves and droughts) and consequently, a direct alteration of the hydrological states of their associated ecosystems. The savanna type ecosystem called dehesa is one of them. This system is the result of a long-term co-evolution of indigenous ecosystems and human settlement in a sustainable balance, with high relevance from both the environmental (biodiversity) and socioeconomic (livestock farming, including Iberian pork food industry) point of view. Dehesa systems have a complex vegetation cover structure, where isolated trees, mainly holm oak, cork oak and oak, Mediterranean shrubs, and pastures coexist. Different problems have arisen in dehesa during last years, an example of them are seca episodes, a disease of oak trees that results in drying and final death. This condition is caused by a fungus, but very likely triggered by external hydrological related conditions like air temperature and soil water content.&#160; Remote sensing techniques have been widely used as the best alternative to monitor vegetation patterns over these areas. However, the presence of clouds and the fixed spatiotemporal resolution of these sensors constitute a limitation in more local studies.This work proposes the combined use of remote sensing by both terrestrial photography and satelital sensors, and hydrometeorological information as data sources for improving the hydrological characterization of vegetation in dehesa areas. The study was carried out in the Santa Clotilde experimental area, within the Carde&#241;a-Montoro Natural Park (southern Spain). Three years of local sub-daily terrestrial photography and hydrometeorological information allowed us to define different hydrometeorological/ecohydrological indicators that are representative of key vegetation states. This local information is linked with vegetation indexes derived from high spatial resolution satellite information (i.e., Landsat TM, ETM+ and OLI (30 m x 30 m) and Sentinel-2 (10 m x 10 m) and distributed meteorological variables to extend the results from the local to the watershed scale. The promising results will be used in a short future as the basis of an advanced monitoring service where meteorological seasonal forecast information could be used to derive key indicators and help in a priori diagnosis of the system facilitating decisions making.This work has been funded by project SIERRA Seguimiento hIdrol&#243;gico de la vEgetaci&#243;n en monta&#241;a mediteRr&#225;nea mediante fusi&#243;n de sensores Remotos en Andaluc&#237;a), with the economic collaboration of the European Funding for Rural Development (FEDER) and the Office for Economy, Knowledge, Enterprises and University of the Andalusian Regional Government.

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