Digital Commons Network^™

Contemporary Challenges And Opportunities For The Management Of Bird Damage At Field Crop Establishment, Christophe Sausse, Alice Baux, Michel Bertrand, Elsa Bonnaud, Sonia Canavelli, Alexandra Destrez, Page E. Klug, Lourdes Olivera, Ethel Rodriguez, Guilllermo Tellechea, Sebastian Zuil

United States Department of Agriculture Wildlife Services: Staff Publications

Bird damage, from sowing to crop establishment, is an important issue for farmers in many parts of the world. However, reliable and cost-effective solutions remain elusive because management tools and research on the subject are limited. The spatial variability of damage across landscapes and the adaptative behaviour of birds create further challenges. Additionally, the issue must be tackled at the landscape scale and involve a variety of stakeholders with conflicting interests and objectives. We summarize some of the challenges and opportunities identified to face these difficulties and address four major research directions for operational solutions including 1) crop damage assessment, …

Cubesats Deliver New Insights Into Agricultural Water Use At Daily And 3 M Resolutions, Bruno Aragon, Matteo G. Ziliani, Rasmus Houborg, Trenton E. Franz, Matthew F. Mccabe

School of Natural Resources: Faculty Publications

Earth observation has traditionally required a compromise in data collection. That is, one could sense the Earth with high spatial resolution occasionally; or with lower spatial fidelity regularly. For many applications, both frequency and detail are required. Precision agriculture is one such example, with sub-10 m spatial, and daily or sub-daily retrieval representing a key goal. Towards this objective, we produced the first cloud-free 3 m daily evaporation product ever retrieved from space, leveraging recently launched nano-satellite constellations to showcase this emerging potential. Focusing on three agricultural fields located in Nebraska, USA, high-resolution crop water use estimates are delivered via …

Cabra: A Novel Large-Sample Dataset For Brazilian Catchments, Andre Almagro, Paulo Tarso S. Oliveira, Antonio Alves Meira Neto, Tirthankar Roy, Peter Troch

Department of Civil and Environmental Engineering: Faculty Publications

In this paper, we present the Catchments Attributes for Brazil (CABra), which is a large-sample dataset for Brazilian catchments that includes long-term data (30 years) for 735 catchments in eight main catchment attribute classes (climate, streamflow, groundwater, geology, soil, topography, land cover, and hydrologic disturbance). We have collected and synthesized data from multiple sources (ground stations, remote sensing, and gridded datasets). To prepare the dataset, we delineated all the catchments using the Multi-Error-Removed Improved-Terrain Digital Elevation Model (MERIT DEM) and the coordinates of the streamflow stations provided by the Brazilian Water Agency, where only the stations with 30 years (1980–2010) …

Meta-Analysis Identifies Pleiotropic Loci Controlling Phenotypic Trade-Offs In Sorghum, Ravi V. Mural, Marcin Grzybowski, Miao Chenyong, Alyssa Damke, Sirjan Sapkota, Richard E. Boyles, Maria G. Salas Fernandez, Patrick S. Schnable, Brandi Sigmon, Stephen Kresovich, James C. Schnable

Department of Plant Pathology: Faculty Publications

Community association populations are composed of phenotypically and genetically diverse accessions. Once these populations are genotyped, the resulting marker data can be reused by different groups investigating the genetic basis of different traits. Because the same genotypes are observed and scored for a wide range of traits in different environments, these populations represent a unique resource to investigate pleiotropy. Here, we assembled a set of 234 separate trait datasets for the Sorghum Association Panel, a group of 406 sorghum genotypes widely employed by the sorghum genetics community. Comparison of genome-wide association studies (GWAS) conducted with two independently generated marker sets …

Drone-Based Magnetic Surveying In Eastern Nebraska, Sulaiman Albadi

Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research

A magnetic survey is one of the methods used by scientists to detect subsurface features. Magnetic surveys can be carried out by walking on the surface of the earth with a magnetic field reading device called a magnetometer. Alternatively, a magnetometer can be installed on a moving platform (aircraft, boat, drone, bicycle) to conduct a more efficient magnetic survey. The geophysics team at the University of Nebraska at Lincoln assembled a drone-based magnetic survey system in 2019 (Jacobson and Filina, 2019) that has proven effective in magnetic readings over the Northern Bounding Fault (NBF) in eastern Nebraska (Jacobson and Filina, …

University Of Nebraska Unmanned Aerial System (Uas) Profiling During The Lapse-Rate Field Campaign, Ashraful Islam, Ajay Shankar, Adam Houston, Carrick Detweiler

School of Computing: Faculty Publications

This paper describes the data collected by the University of Nebraska-Lincoln (UNL) as part of the field deployments during the Lower Atmospheric Process Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE) flight campaign in July 2018. The UNL deployed two multirotor unmanned aerial systems (UASs) at multiple sites in the San Luis Valley (Colorado, USA) for data collection to support three science missions: convection initiation, boundary layer transition, and cold air drainage flow. We conducted 172 flights resulting in over 21 h of cumulative flight time. Our novel design for the sensor housing onboard the UAS was employed …

Determining Crop Available Nutrients From Manure, Charles Shapiro, Leslie J. Johnson, Amy Schmidt, Richard Koelsch

University of Nebraska-Lincoln Extension: Historical Materials

This NebGuide discusses the availability and use of manure nutrients for field crop production. When managed correctly, nutrients in livestock manure can be a valuable resource. When managed improperly, however, these same nutrients represent a potential environmental pollutant. Accurate crediting of manure nutrients within a total crop nutrient program is fundamental to utilizing manure as a resource. This NebGuide illustrates how to estimate the crop available manure nutrients (part c, Figure 1) and calculate an agronomically based manure application rate. There are other tools available that do the calculations for you. This NebGuide will explain each step of the process. …

Corrigendum To: Psxii-19 Urine Metabolomics Analysis Associated With Feed Efficiency On Crossbred Steers During The Growing And Finishing Period On Forage- And Concentrate-Based Diets, Virginia Artegoitia, John Newman, Ron Lewis, Andrew P. Foote, Harvey C. Freetly

Roman L. Hruska U.S. Meat Animal Research Center: Reports

No abstract provided.

The R Journal (June 2021) 13(1): Complete Issue, The R Foundation

The R Journal

Editorial, Dianne Cook

Contributed Research Articles

SEEDCCA: An Integrated R-Package for Canonical Correlation Analysis and Partial Least Squares, Bo-Young Kim, Yunju Im, and Jae Keun Yoo

npcure: An R Package for Nonparametric Inference in Mixture Cure Models, Ana López-Cheda, M. Amalia Jácome, and Ignacio López-de-Ullibarri

A Method for Deriving Information from Running R Code, Mark P. J. van der Loo

JMcmprsk: An R Package for Joint Modelling of Longitudinal and Survival Data with Competing Risks, Hong Wang, Ning Li, Shanpeng Li, and Gang Li

Wide-to-tall Data Reshaping Using Regular Expressions and the nc Package, Toby Dylan Hocking

Linear Regression with …

Optical Phonon Modes, Static And High-Frequency Dielectric Constants, And Effective Electron Mass Parameter In Cubic In2O3, Megan Stokey, Rafal Korlacki, Sean Knight, Alexander Ruder, Matthew J. Hilfiker, Zbigniew Galazka, Klaus Irmscher, Yuxuan Zhang, Hongping Zhao, Vanya Darakchieva, Mathias Schubert

Department of Electrical and Computer Engineering: Faculty Publications

A complete set of all optical phonon modes predicted by symmetry for bixbyite structure indium oxide is reported here from a combination of far-infrared and infrared spectroscopic ellipsometry, as well as first principles calculations. Dielectric function spectra measured on high quality, marginally electrically conductive melt grown single bulk crystals are obtained on a wavelength-by-wavelength (also known as point-by-point) basis and by numerical reduction of a subtle free charge carrier Drude model contribution. A four-parameter semi-quantum model is applied to determine all 16 pairs of infrared-active transverse and longitudinal optical phonon modes, including the high-frequency dielectric constant, ε_∞=4.05±0.05. The …

Promise And Complexity Of Lupus Mouse Models, Erica Moore, Joshua A. Reynolds, Anne Davidson, Stefania Gallucci, Laurence Morel, Deepak A. Rao, Howard A. Young, Chaim Putterman

United States Public Health Resources

As a follow up to a 2010 meeting deliberating on the benefits of studying mouse models of systemic lupus erythematosus (SLE), the virtual conference “Mouse models of lupus 10 years later” convened on 10 December 2020 to address a challenging decade that saw few new therapies approved, despite leaps in knowledge

Abnormalities in both innate and adaptive immunity characterize SLE, a systemic autoimmune disease with potentially severe consequences in patients. Treatment has traditionally been limited to broad-acting, side-effect-heavy immunosuppressants, which are also incompletely effective. Thus, the need for specific therapies targeting the pathogenic mechanisms of SLE remains unmet. Affirming the …

Krippendorffsalpha: An R Package For Measuring Agreement Using Krippendorff's Alpha Coefficient, John Hughes

The R Journal

R package krippendorffsalpha provides tools for measuring agreement using Krippendorff’s α coefficient, a well-known nonparametric measure of agreement (also called inter-rater reliability and various other names). This article first develops Krippendorff’s α in a natural way and situates α among statistical procedures. Then, the usage of package krippendorffsalpha is illustrated via analyses of two datasets, the latter of which was collected during an imaging study of hip cartilage. The package permits users to apply the α methodology using built-in distance functions for the nominal, ordinal, interval, or ratio levels of measurement. User-defined distance functions are also supported. The fitting function …

Robustness In Network (Robin): An R Package For Comparison And Validation Of Communities, Valeria Policastro, Dario Righelli, Annamaria Carissimo, Luisa Cutillo, Italia De Feis

The R Journal

In network analysis, many community detection algorithms have been developed. However, their implementation leaves unaddressed the question of the statistical validation of the results. Here, we present robin (ROBustness In Network), an R package to assess the robustness of the community structure of a network found by one or more methods to give indications about their reliability. The procedure initially detects if the community structure found by a set of algorithms is statistically significant and then compares two selected detection algorithms on the same graph to choose the one that better fits the network of interest. We demonstrate the use …

Pdynmc: A Package For Estimating Linear Dynamic Panel Data Models Based On Nonlinear Moment Conditions, Markus Fritsch, Andrew Adrian Yu Pua, Joachim Schnurbus

The R Journal

This paper introduces pdynmc, an R package that provides users sufficient flexibility and precise control over the estimation and inference in linear dynamic panel data models. The package primarily allows for the inclusion of nonlinear moment conditions and the use of iterated GMM; additionally, visualizations for data structure and estimation results are provided. The current implementation reflects recent developments in literature, uses sensible argument defaults, and aligns commercial and noncommercial estimation commands. Since the understanding of the model assumptions is vital for setting up plausible estimation routines, we provide a broad introduction of linear dynamic panel data models directed towards …

Linear Regression With Stationary Errors: The R Package Slm, Emmanuel Caron, Jérôme Dedecker, Bertrand Michel

The R Journal

This paper introduces the R package slm, which stands for Stationary Linear Models. The package contains a set of statistical procedures for linear regression in the general context where the error process is strictly stationary with a short memory. We work in the setting of Hannan (1973), who proved the asymptotic normality of the (normalized) least squares estimators (LSE) under very mild conditions on the error process. We propose different ways to estimate the asymptotic covariance matrix of the LSE and then to correct the type I error rates of the usual tests on the parameters (as well as confidence …

Regularized Transformation Models: The Tramnet Package, Lucas Kook, Torsten Hothorn

The R Journal

The tramnet package implements regularized linear transformation models by combining the flexible class of transformation models from tram with constrained convex optimization implemented in CVXR. Regularized transformation models unify many existing and novel regularized regression models under one theoretical and computational framework. Regularization strategies implemented for transformation models in tramnet include the Lasso, ridge regression, and the elastic net and follow the parameterization in glmnet. Several functionalities for optimizing the hyperparameters, including model-based optimization based on the mlrMBO package, are implemented. A multitude of S3 methods is deployed for visualization, handling, and simulation purposes. This work aims at illustrating all …

The Hbv.Ianigla Hydrological Model, Ezequiel Toum, Mariano H. Masiokas, Ricardo Villalba, Pierre Pitte, Lucas Ruiz

The R Journal

Over the past 40 years, the HBV (Hydrologiska Byråns Vattenbalansavdelning) hydrological model has been one of the most used worldwide due to its robustness, simplicity, and reliable results. Despite these advantages, the available versions impose some limitations for research studies in mountain watersheds dominated by ice-snow melt runoff (i.e., no glacier module, a limited number of elevation bands, among other constraints). Here we present HBV.IANIGLA, a tool for hydroclimatic studies in regions with steep topography and/or cryospheric processes which provides a modular and extended implementation of the HBV model as an R package. To our knowledge, this is the first …

Clustcurv: An R Package For Determining Groups In Multiple Curves, Nora M. Villanueva, Marta Sestelo, Luis Meira-Machado, Javier Roca-Pardiñas

The R Journal

In many situations, it could be interesting to ascertain whether groups of curves can be performed, especially when confronted with a considerable number of curves. This paper introduces an R package, known as clustcurv, for determining clusters of curves with an automatic selection of their number. The package can be used for determining groups in multiple survival curves as well as for multiple regression curves. Moreover, it can be used with large numbers of curves. An illustration of the use of clustcurv is provided, using both real data examples and artificial data

Rlumcarlo: Simulating Cold Light Using Monte Carlo Methods, Sebastian Kreutzer, Johannes Friedrich, Vasilis Pagonis, Christian Laag, Ena Rajovic, Christoph Schmidt

The R Journal

The luminescence phenomena of insulators and semiconductors (e.g., natural minerals such as quartz) have various application domains. For instance, Earth Sciences and archaeology exploit luminescence as a dating method. Herein, we present the R package RLumCarlo implementing sets of luminescence models to be simulated with Monte Carlo (MC) methods. MC methods make a powerful ally to all kinds of simulation attempts involving stochastic processes. Luminescence production is such a stochastic process in the form of charge (electron-hole pairs) interaction within insulators and semiconductors. To simulate luminescence-signal curves, we distribute single and independent MC processes to virtual MC clusters. RLumCarlo comes …

Statistical Quality Control With The Qcr Package, Miguel Flores, Rubén Fernández-Casal, Salvador Naya, Javier Tarrío-Saavedra

The R Journal

The R package qcr for Statistical Quality Control (SQC) is introduced and described. It includes a comprehensive set of univariate and multivariate SQC tools that completes and increases the SQC techniques available in R. Apart from integrating different R packages devoted to SQC (qcc, MSQC), qcr provides nonparametric tools that are highly useful when Gaussian assumption is not met. This package computes standard univariate control charts for individual measurements, [], S, R, p, np, c, u, EWMA, and CUSUM. In addition, it includes functions to perform multivariate control charts such as Hotelling T² , MEWMA and MCUSUM. As …

Gofcopula: Goodness-Of-Fit Tests For Copulae, Ostap Okhrin, Simon Trimborn, Martin Waltz

The R Journal

The last decades show an increased interest in modeling various types of data through copulae. Different copula models have been developed, which lead to the challenge of finding the best fitting model for a particular dataset. From the other side, a strand of literature developed a list of different Goodness-of-Fit (GoF) tests with different powers under different conditions. The usual practice is the selection of the best copula via the p-value of the GoF test. Although this method is not purely correct due to the fact that non-rejection does not imply acception, this strategy is favored by practitioners. Unfortunately, …

Garchx: Flexible And Robust Garch-X Modeling, Genaro Sucarrat

The R Journal

The garchx package provides a user-friendly, fast, flexible, and robust framework for the estimation and inference of GARCH(p, q,r)-X models, where p is the ARCH order, q is the GARCH order, r is the asymmetry or leverage order, and ’X’ indicates that covariates can be included. Quasi Maximum Likelihood (QML) methods ensure estimates are consistent and standard errors valid, even when the standardized innovations are non-normal or dependent, or both. Zero-coefficient restrictions by omission enable parsimonious specifications, and functions to facilitate the non-standard inference associated with zero-restrictions in the null-hypothesis are provided. Finally, in the formal comparisons of …

Onestep: Le Cam's One-Step Estimation Procedure, Alexandre Brouste, Christophe Dutang, Darel Noutsa Mieniedou

The R Journal

The OneStep package proposes principally an eponymic function that numerically computes Le Cam’s one-step estimator, which is asymptotically efficient and can be computed faster than the maximum likelihood estimator for large datasets. Monte Carlo simulations are carried out for several examples (discrete and continuous probability distributions) in order to exhibit the performance of Le Cam’s one-step estimation procedure in terms of efficiency and computational cost on observation samples of finite size.

Wide-To-Tall Data Reshaping Using Regular Expressions And The Nc Package, Toby Dylan Hocking

The R Journal

Regular expressions are powerful tools for extracting tables from non-tabular text data. Capturing regular expressions that describe the information to extract from column names can be especially useful when reshaping a data table from wide (few rows with many regularly named columns) to tall (fewer columns with more rows). We present the R package nc (short for named capture), which provides functions for wide-to-tall data reshaping using regular expressions. We describe the main new ideas of nc, and provide detailed comparisons with related R packages (stats, utils, data.table, tidyr, tidyfast, tidyfst, reshape2, cdata).

Stratamatch: Prognostic Score Stratification Using A Pilot Design, Rachael C. Aikens, Joseph Rigdon, Justin Lee, Michael Baiocchi, Andrew B. Goldstone, Peter Chiu, Y Joseph Woo, Jonathan H. Chen

The R Journal

Optimal propensity score matching has emerged as one of the most ubiquitous approaches for causal inference studies on observational data. However, outstanding critiques of the statistical properties of propensity score matching have cast doubt on the statistical efficiency of this technique, and the poor scalability of optimal matching to large data sets makes this approach inconvenient if not infeasible for sample sizes that are increasingly commonplace in modern observational data. The stratamatch package provides implementation support and diagnostics for ‘stratified matching designs,’ an approach that addresses both of these issues with optimal propensity score matching for large-sample observational studies. First, …

Editorial, Dianne Cook

The R Journal

First, some news about the journal board. Welcome to Gavin Simpson, who joins as a new Executive Editor! In addition, welcome to our new Associate Editors Nicholas Tierney, Isabella Gollini, Rasmus Bååth, Mark van der Loo, Elizabeth Sweeney, Louis Aslett and Katarina Domijan. With the large volume of submissions, the Associate Editors now play a vital role in processing articles.

Penphcure: Variable Selection In Proportional Hazards Cure Model With Time-Varying Covariates, Alessandro Beretta, Cédric Heuchenne

The R Journal

We describe the penPHcure R package, which implements the semiparametric proportional-hazards (PH) cure model of Sy and Taylor (2000) extended to time-varying covariates and the variable selection technique based on its SCAD-penalized likelihood proposed by Beretta and Heuchenne (2019a). In survival analysis, cure models are a useful tool when a fraction of the population is likely to be immune from the event of interest. They can separate the effects of certain factors on the probability of being susceptible and on the time until the occurrence of the event. Moreover, the penPHcure package allows the user to simulate data from a …

Novel And Fast Peridynamic Models For Material Degradation And Failure, Siavash Jafarzadeh

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

Fracture is one of the main mechanisms of structural failure. Corroded surfaces with chemically-induced damage are, notably, potential sites for crack initiation and propagation in metals, which can lead to catastrophic failure of structures. Despite some progress in simulating fracture and damage using classical models, realistic prediction of complex damage progression and failure has been out of reach for many decades. Peridynamics (PD), a nonlocal theory introduced in 2000, opened up new avenues in modeling material degradation and failure. Existing numerical methods used to discretize PD equations, however, are quite expensive as the PD nonlocal interactions make them unaffordable for …

Presence-Absence Sampling Plans For Stink Bugs (Hemiptera: Pentatomidae) In The Midwest Region Of The United States, Rafael Carlesso Aita, Daniela T. Pezzini, Eric C. Burkness, Christina D. Difonzo, Deborah L. Finke, Thomas E. Hunt, Janet J. Knodel, Christian H. Krupke, Lia Marchi-Werle, Brian Mccornack, Andrew P. Michel, Christopher R. Philips, Nicholas J. Seiter, Adam J. Varenhorst, Robert J. Wright, William D. Hutchison, Robert L. Koch

Department of Entomology: Faculty Publications

Stink bugs represent an increasing risk to soybean production in the Midwest region of the United States. The current sampling protocol for stink bugs in this region is tailored for population density estimation and thus is more relevant to research purposes. A practical decision-making framework with more efficient sampling effort for management of herbivorous stink bugs is needed. Therefore, a binomial sequential sampling plan was developed for herbivorous stink bugs in the Midwest region. A total of 146 soybean fields were sampled across 11 states using sweep nets in 2016, 2017, and 2018. The binomial sequential sampling plans were developed …

Quantifying High-Temperature Stress On Soybean Canopy Photosynthesis: The Unique Role Of Sun-Induced Chlorophyll Fluorescence, Hyungsuk Kimm, Kaiyu Guan, Charles H. Burroughs, Bin Peng, Elizabeth A. Ainsworth, Carl J. Bernacchi, Caitlin E. Moore, Etsushi Kumagai, Xi Yang, Joseph A. Berry, Genghong Wu

United States Department of Agriculture-Agricultural Research Service / University of Nebraska-Lincoln: Faculty Publications

High temperature and accompanying high vapor pressure deficit often stress plants without causing distinctive changes in plant canopy structure and consequential spectral signatures. Sun-induced chlorophyll fluorescence (SIF), because of its mechanistic link with photosynthesis, may better detect such stress than remote sensing techniques relying on spectral reflectance signatures of canopy structural changes. However, our understanding about physiological mechanisms of SIF and its unique potential for physiological stress detection remains less clear. In this study, we measured SIF at a high-temperature experiment, Temperature Free-Air Controlled Enhancement, to explore the potential of SIF for physiological investigations. The experiment provided a gradient of …