Mathematical modeling tendencies in plant pathology

Nowadays plant diseases represent one of the major threats for crops around the world, because they carry healthy, economical, environmental and social problems. Considering this, it is necessary to have a description of the dynamics of plant disease in order to have sustainable strategies to prevent and diminish the impact of the diseases in crops. Mathematical tools have been employed to create models which give a description of epidemic dynamics; the commonly mathematical tools used are: Diseaseprogress curves, Linked Differential Equation (LDE), Area Under disease Progress Curve (AUDPC) and computer simulation. Nevertheless, there are other tools that have been employed in epidemiology of plant disease like: statistical tools, visual evaluations and pictorial assessment. Each tool has its own advantages and disadvantages. The nature of the problem and the epidemiologist necessities determine the mathematical tool to be used and the variables to be included into the model. This paperpresents review of the tools used in epidemiology of plant disease remarking their advantages and disadvantages and mathematical modeling tendencies in plant pathology

The ALMA Frontier Fields Survey

CONTEXT: Dusty star-forming galaxies are among the most prodigious systems at high redshift (z > 1), characterized by high star-formation rates and huge dust reservoirs. The bright end of this population has been well characterized in recent years, but considerable uncertainties remain for fainter dusty star-forming galaxies, which are responsible for the bulk of star formation at high redshift and thus play a key role in galaxy growth and evolution. AIMS: In this first paper of our series, we describe our methods for finding high redshift faint dusty galaxies using millimeter observations with ALMA. METHODS: We obtained ALMA 1.1 mm mosaic images for three strong-lensing galaxy clusters from the Frontier Fields Survey, which constitute some of the best studied gravitational lenses to date. The ≈2′ × 2′ mosaics overlap with the deep HST WFC3/IR footprints and encompass the high magnification regions of each cluster for maximum intrinsic source sensitivity. The combination of extremely high ALMA sensitivity and the magnification power of these clusters allows us to systematically probe the sub-mJy population of dusty star-forming galaxies over a large surveyed area. RESULTS: We present a description of the reduction and analysis of the ALMA continuum observations for the galaxy clusters Abell 2744 (z = 0.308), MACS J0416.1-2403 (z = 0.396) and MACS J1149.5+2223 (z = 0.543), for which we reach observed rms sensitivities of 55, 59 and 71 μJy beam-1 respectively. We detect 12 dusty star-forming galaxies at S/N ≥ 5.0 across the three clusters, all of them presenting coincidence with near-infrared detected counterparts in the HST images. None of the sources fall close to the lensing caustics, thus they are not strongly lensed. The observed 1.1 mm flux densities for the total sample of galaxies range from 0.41 to 2.82 mJy, with observed effective radii spanning ≲0.̋05 to 0.̋37 ± 0.̋21 . The lensing-corrected sizes of the detected sources appear to be in the same range as those measured in brighter samples, albeit with possibly larger dispersion

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

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