Unifying compactly supported and Matern covariance functions in spatial statistics

The Matern family of covariance functions has played a central role in spatial statistics for decades, being a flexible parametric class with one parameter determining the smoothness of the paths of the underlying spatial field. This paper proposes a family of spatial covariance functions, which stems from a reparameterization of the generalized Wendland family. As for the Matern case, the proposed family allows for a continuous parameterization of the smoothness of the underlying Gaussian random field, being additionally compactly supported.More importantly, we show that the proposed covariance family generalizes the Matern model which is attained as a special limit case. This implies that the (reparametrized) Generalized Wendland model is more flexible than the Matern model with an extra-parameter that allows for switching from compactly to globally supported covariance functions.Our numerical experiments elucidate the speed of convergence of the proposed model to the Matern model. We also inspect the asymptotic distribution of the maximum likelihood method when estimating the parameters of the proposed covariance models under both increasing and fixed domain asymptotics. The effectiveness of our proposal is illustrated by analyzing a georeferenced dataset of mean temperatures over a region of French, and performing a re-analysis of a large spatial point referenced dataset of yearly total precipitation anomalies. (C) 2022 Published by Elsevier Inc

Production cross-sections and momentum distributions of fragments from neutron-deficient 36Ar at 1.05 A.GeV

We have measured production cross sections and longitudinal momentum distributions of fragments from neutron-deficient 36Ar at 1.05 A.GeV. The production cross-sections show excellent agreement with the predictions of the semiempirical formula EPAX. We have compared these results, involving extremly neutron deficient nuclei, with model calculations to extract informa tion about the response of these models close to the driplines. The longitudinal momentum distributions have also been extracted and are compared with the Goldhaber and Morrissey systematics.Comment: 16 pages, 6 figure

A selective view of climatological data and likelihood estimation

This article gives a narrative overview of what constitutes climatological data and their typical features, with a focus on aspects relevant to statistical modeling. We restrict the discussion to univariate spatial fields and focus on maximum likelihood estimation. To address the problem of enormous datasets, we study three common approximation schemes: tapering, direct misspecification, and composite likelihood for Gaussian and nonGaussian distributions. We focus particularly on the so-called 'sinh-arcsinh distribution', obtained through a specific transformation of the Gaussian distribution. Because it has flexible marginal distributions - possibly skewed and/or heavy-tailed - it has a wide range of applications. One appealing property of the transformation involved is the existence of an explicit inverse transformation that makes likelihood-based methods straightforward. We describe a simulation study illustrating the effects of the different approximation schemes. To the best of our knowledge, a direct comparison of tapering, direct misspecification, and composite likelihood has never been made previously, and we show that direct misspecification is inferior. In some metrics, composite likelihood has a minor advantage over tapering. We use the estimation approaches to model a high-resolution global climate change field. All simulation code is available as a Docker container and is thus fully reproducible. Additionally, the present article describes where and how to get various climate datasets. (c) 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND licens

The Use of a Vaginal Conductivity Probe to Influence Calf Sex Ratio via Altered Insemination Time

One hundred eighty-nine mixed breed beef heifers from 13 consignors enrolled in the MACEP heifer development project were utilized in this study. Heifers were synchronized by feeding 0.5 mg melengestrol acetate (MGA) per head per day for 14 days followed by an injection of prostaglandin F2a (PGF2a; 25 mg Lutalyse®) 17 days after the last MGA feeding. Each heifer was fitted with a Heatwatch® transmitter on the morning of PGF2a administration to facilitate detection of estrus. Vaginal conductivity measurements were taken using an Ovatec® probe every 12 hours for 96 hours beginning at the time of PGF2a injection. Heifers randomly assigned to produce a female calf were inseminated near the onset of estrus (as indicated by probe values of £ 55 on the decline). Heifers randomly assigned to produce a male calf were inseminated approximately 24 hours after the onset of estrus (as indicated by probe values of ³ 60 on the incline). All heifers not inseminated by 96 hours after PGF2a were mass inseminated in an attempt to impregnate as many heifers as possible. Heifers that were diagnosed as pregnant as a result of the artificial insemination were subjected to ultrasonography for fetal sex determination. Only 70 of the 189 heifers (37.0%) exhibited estrus according to Heatwatch® and incidence of estrus was influenced by heifer average daily gain, reproductive tract score, and disposition score. Heifers receiving a disposition score of 3 (78.7) had a higher (P\u3c.05) probe reading at AI than those receiving a disposition score of 1 or 2 (70.8 and 72.5, respectively). Heifers with probe readings at insemination of 80 - 84 and \u3e 84 had lower (P\u3c.05) pregnancy rates to AI (13.6 and 0.0%, respectively) than heifers with probe readings in the ranges of \u3c 60, 60 - 64, 65 - 69, 70 - 74, and 75 - 79 (35.7, 40.9, 31.4, 35.3, and 26.9% respectively). Heifers that were bred when probe values were increasing had a lower (P\u3c.05) percentage of male fetuses (34.4%) than those bred during a period of decreasing probe values (69.2% male fetuses). These results demonstrate that a vaginal conductivity probe may be a useful tool to determine an insemination time that could potentially alter calf sex ratio

Measurement of two-halo neutron transfer reaction p(11^{11}Li,9^{9}Li)t at 3AA MeV

The p(\nuc{11}{Li},\nuc{9}{Li})t reaction has been studied for the first time at an incident energy of 3$A$ MeV delivered by the new ISAC-2 facility at TRIUMF. An active target detector MAYA, build at GANIL, was used for the measurement. The differential cross sectionshave been determined for transitions to the \nuc{9}{Li} ground andthe first excited states in a wide range of scattering angles. Multistep transfer calculations using different \nuc{11}{Li} model wave functions, shows that wave functions with strong correlations between the halo neutrons are the most successful in reproducing the observation.Comment: 6 pages, 3 figures, submitted to Physical Review Letter

Monitoring Energy Efficiency in Buildings with Wireless Sensor Networks: NRG-WiSe Building

Teoría de la Señal y Comunicacione

First observation of 54Zn and its decay by two-proton emission

The nucleus 54Zn has been observed for the first time in an experiment at the SISSI/LISE3 facility of GANIL in the quasi-fragmentation of a 58Ni beam at 74.5 MeV/nucleon in a natNi target. The fragments were analysed by means of the ALPHA-LISE3 separator and implanted in a silicon-strip detector where correlations in space and time between implantation and subsequent decay events allowed us to generate almost background free decay spectra for about 25 different nuclei at the same time. Eight 54Zn implantation events were observed. From the correlated decay events, the half-life of 54Zn is determined to be 3.2 +1.8/-0.8 ms. Seven of the eight implantations are followed by two-proton emission with a decay energy of 1.48(2) MeV. The decay energy and the partial half-life are compared to model predictions and allow for a test of these two-proton decay models.Comment: 4 pages, 4 figures, accepted for publication in PR

Remote and field level quantification of vegetation covariates for malaria mapping in three rice agro-village complexes in Central Kenya

<p>Abstract</p> <p>Background</p> <p>We examined algorithms for malaria mapping using the impact of reflectance calibration uncertainties on the accuracies of three vegetation indices (VI)'s derived from QuickBird data in three rice agro-village complexes Mwea, Kenya. We also generated inferential statistics from field sampled vegetation covariates for identifying riceland <it>Anopheles arabiensis </it>during the crop season. All aquatic habitats in the study sites were stratified based on levels of rice stages; flooded, land preparation, post-transplanting, tillering, flowering/maturation and post-harvest/fallow. A set of uncertainty propagation equations were designed to model the propagation of calibration uncertainties using the red channel (band 3: 0.63 to 0.69 μm) and the near infra-red (NIR) channel (band 4: 0.76 to 0.90 μm) to generate the Normalized Difference Vegetation Index (NDVI) and the Soil Adjusted Vegetation Index (SAVI). The Atmospheric Resistant Vegetation Index (ARVI) was also evaluated incorporating the QuickBird blue band (Band 1: 0.45 to 0.52 μm) to normalize atmospheric effects. In order to determine local clustering of riceland habitats <it>Gi*(d) </it>statistics were generated from the ground-based and remotely-sensed ecological databases. Additionally, all riceland habitats were visually examined using the spectral reflectance of vegetation land cover for identification of highly productive riceland <it>Anopheles </it>oviposition sites.</p> <p>Results</p> <p>The resultant VI uncertainties did not vary from surface reflectance or atmospheric conditions. Logistic regression analyses of all field sampled covariates revealed emergent vegetation was negatively associated with mosquito larvae at the three study sites. In addition, floating vegetation (-ve) was significantly associated with immature mosquitoes in Rurumi and Kiuria (-ve); while, turbidity was also important in Kiuria. All spatial models exhibit positive autocorrelation; similar numbers of log-counts tend to cluster in geographic space. The spectral reflectance from riceland habitats, examined using the remote and field stratification, revealed post-transplanting and tillering rice stages were most frequently associated with high larval abundance and distribution.</p> <p>Conclusion</p> <p>NDVI, SAVI and ARVI generated from QuickBird data and field sampled vegetation covariates modeled cannot identify highly productive riceland <it>An. arabiensis </it>aquatic habitats. However, combining spectral reflectance of riceland habitats from QuickBird and field sampled data can develop and implement an Integrated Vector Management (IVM) program based on larval productivity.</p