The term
semidomain
refers to a subset
S
of an integral domain
R
, in which the pairs
(
S
,
+
)
and
(
S
,
·
)
are semigroups with identities. If
S
contains no additive inverses except 0, we say that
...S
is additively reduced. By taking polynomial expressions with coefficients in
S
and exponents in a torsion-free monoid
M
, we obtain the additively reduced monoid semidomain
S
M
. In this paper, we investigate the factorization properties of such semidomains, providing necessary and sufficient conditions for them to be bounded factorization semidomains, finite factorization semidomains, and unique factorization semidomains. We also identify large classes of semidomains with full and infinite elasticity. Throughout the paper, we present examples to help elucidate the arithmetic of additively reduced monoid semidomains.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
A three-stage model development process facilitates the integration of modelling, phenotyping, and functional gene/QTL detection and effectively advances modelling of genotype×environment×management ...interactions.
Abstract
In spite of the increasing expectation for process-based crop modelling to capture genotype (G) by environment (E) by management (M) interactions to support breeding selections, it remains a challenge to use current crop models to accurately predict phenotypes from genotypes or from candidate genes. We use wheat as a target crop and the APSIM farming systems model (Holzworth et al., 2014) as an example to analyse the current status of process-based crop models with a major focus on need to improve simulation of specific eco-physiological processes and their linkage to underlying genetic controls. For challenging production environments in Australia, we examine the potential opportunities to capture physiological traits, and to integrate genetic and molecular approaches for future model development and applications. Model improvement will require both reducing the uncertainty in simulating key physiological processes and enhancing the capture of key observable traits and underlying genetic control of key physiological responses to environment. An approach consisting of three interactive stages is outlined to (i) improve modelling of crop physiology, (ii) develop linkage from model parameter to genotypes and further to loci or alleles, and (iii) further link to gene expression pathways. This helps to facilitate the integration of modelling, phenotyping, and functional gene detection and to effectively advance modelling of G×E×M interactions. While gene-based modelling is not always needed to simulate G×E×M, including well-understood gene effects can improve the estimation of genotype effects and prediction of phenotypes. Specific examples are given for enhanced modelling of wheat in the APSIM framework.
Abstract
We present an ALMA-Herschel joint analysis of sources detected by the ALMA Lensing Cluster Survey (ALCS) at 1.15 mm. Herschel/PACS and SPIRE data at 100–500
μ
m are deblended for 180 ALMA ...sources in 33 lensing cluster fields that are detected either securely (141 sources; in our main sample) or tentatively at S/N ≥ 4 with cross-matched HST/Spitzer counterparts, down to a delensed 1.15 mm flux density of ∼0.02 mJy. We performed far-infrared spectral energy distribution modeling and derived the physical properties of dusty star formation for 125 sources (109 independently) that are detected at >2
σ
in at least one Herschel band. A total of 27 secure ALCS sources are not detected in any Herschel bands, including 17 optical/near-IR-dark sources that likely reside at
z
= 4.2 ± 1.2. The 16th, 50th, and 84th percentiles of the redshift distribution are 1.15, 2.08, and 3.59, respectively, for ALCS sources in the main sample, suggesting an increasing fraction of
z
≃ 1 − 2 galaxies among fainter millimeter sources (
f
1150
∼ 0.1 mJy). With a median lensing magnification factor of
μ
=
2.6
−
0.8
+
2.6
, ALCS sources in the main sample exhibit a median intrinsic star formation rate of
94
−
54
+
84
M
⊙
yr
−1
, lower than that of conventional submillimeter galaxies at similar redshifts by a factor of ∼3. Our study suggests weak or no redshift evolution of dust temperature with
L
IR
< 10
12
L
⊙
galaxies within our sample at
z
≃ 0 − 2. At
L
IR
> 10
12
L
⊙
, the dust temperatures show no evolution across
z
≃ 1–4 while being lower than those in the local universe. For the highest-redshift source in our sample (
z
= 6.07), we can rule out an extreme dust temperature (>80 K) that was reported for MACS0416 Y1 at
z
= 8.31.
Genetic improvement in sorghum breeding programs requires the assessment of adaptation traits in small-plot breeding trials across multiple environments. Many of these phenotypic assessments are made ...by manual measurement or visual scoring, both of which are time consuming and expensive. This limits trial size and the potential for genetic gain. In addition, these methods are typically restricted to point estimates of particular traits, such as leaf senescence or flowering and do not capture the dynamic nature of crop growth. In water-limited environments in particular, information on leaf area development over time would provide valuable insight into water use and adaptation to water scarcity during specific phenological stages of crop development. Current methods to estimate plant leaf area index (LAI) involve destructive sampling and are not practical in breeding. Unmanned aerial vehicles (UAV) and proximal-sensing technologies open new opportunities to assess these traits multiple times in large small-plot trials. We analyzed vegetation-specific crop indices obtained from a narrowband multi-spectral camera on board a UAV platform flown over a small pilot trial with 30 plots (10 genotypes randomized within 3 blocks). Due to variable emergence we were able to assess the utility of these vegetation indices to estimate canopy cover and LAI over a large range of plant densities. We found good correlations between the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) with plant number per plot, canopy cover and LAI both during the vegetative growth phase (pre-anthesis) and at maximum canopy cover shortly after anthesis. We also analyzed the utility of time-sequence data to assess the senescence pattern of sorghum genotypes known as fast (senescent) or slow senescing (stay-green) types. The Normalized Difference Red Edge (NDRE) index which estimates leaf chlorophyll content was most useful in characterizing the leaf area dynamics/senescence patterns of contrasting genotypes. These methods to monitor dynamics of green and senesced leaf area are suitable for out-scaling to enhance phenotyping of additional crop canopy characteristics and likely crop yield responses among genotypes across large fields and multiple dates.
A subsemiring
S
of
R
is called a
positive semiring
provided that
S
consists of nonnegative numbers and
1
∈
S
. Here we study factorizations in both the additive monoid
(
S
,
+
)
and the ...multiplicative monoid
(
S
\
{
0
}
,
·
)
. In particular, we investigate when, for a positive semiring
S
, both
(
S
,
+
)
and
(
S
\
{
0
}
,
·
)
have the following properties: atomicity, the ACCP, the bounded factorization property (BFP), the finite factorization property (FFP), and the half-factorial property (HFP). It is well known that in the context of cancellative and commutative monoids, the chain of implications HFP
⇒
BFP and FFP
⇒
BFP
⇒
ACCP
⇒
atomicity holds. Here we construct classes of positive semirings wherein both the additive and multiplicative structures satisfy each of these properties, and we also give examples to show that, in general, none of the implications in the previous chain is reversible.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
ABSTRACT
We combine archival ALMA data targeting the Hubble Ultra Deep Field (HUDF) to produce the deepest currently attainable 1-mm maps of this key region. Our deepest map covers 4.2 arcmin2, with ...a beamsize of 1.49 arcsec $\, {\times }\, 1.07\,$ arcsec at an effective frequency of 243 GHz (1.23 mm). It reaches an rms of 4.6 μJy beam$^{-1}$, with 1.5 arcmin2 below 9.0 μJy beam−1, an improvement of ${\gt }\,$5 per cent (and up to 50 per cent in some regions) over the best previous map. We also make a wider, shallower map, covering 25.4 arcmin2. We detect 45 galaxies in the deep map down to 3.6$\sigma$, 10 more than previously detected, and 39 of these galaxies have JWST counterparts. A stacking analysis on the positions of ALMA-undetected JWST galaxies yields 10 per cent more signal compared to previous stacking analyses, and we find that detected sources plus stacking contribute (10.0 ${\pm }$ 0.5) Jy deg−2 to the cosmic infrared background (CIB) at 1.23 mm. Although this is short of the (uncertain) background level of about 20 Jy deg−2, we show that our measurement is consistent with the background if the HUDF is a mild (${\sim }\, 2\sigma$) negative CIB fluctuation, and that the contribution from faint undetected objects is small and converging. This suggests that JWST has detected essentially all of the galaxies that contribute to the CIB, as anticipated from the strong correlation between galaxy stellar mass and obscured star formation.
Aims. We present and study spatially resolved imaging obtained with the Atacama Large Millimeter/submillimeter Array (ALMA) of multiple 12CO(J = 6 − 5, 8−7, and 9−8) and two H2O(202−111 and 211−202) ...emission lines and cold dust continuum toward the gravitationally lensed dusty star-forming galaxy SPT 0346-52 at z = 5.656. Methods. Using a visibility-domain source-plane reconstruction we probe the structure and dynamics of the different components of the interstellar medium (ISM) in this galaxy down to scales of 1 kpc in the source plane. Results. Measurements of the intrinsic sizes of the different CO emission lines indicate that the higher J transitions trace more compact regions in the galaxy. Similarly, we find smaller dust continuum intrinsic sizes with decreasing wavelength, based on observations at rest frame 130, 300, and 450 μm. The source shows significant velocity structure, and clear asymmetry where an elongated structure is observed in the source plane with significant variations in their reconstructed sizes. This could be attributed to a compact merger or turbulent disk rotation. The differences in velocity structure through the different line tracers, however, hint at the former scenario in agreement with previous CII line imaging results. Measurements of the CO line ratios and magnifications yield significant variations as a function of velocity, suggesting that modeling of the ISM using integrated values could be misinterpreted. Modeling of the ISM in SPT 0346-52 based on delensed fluxes indicates a highly dense and warm medium, qualitatively similar to that observed in high-redshift quasar hosts.
Full text
Available for:
FMFMET, NUK, UL, UM, UPUK
We present the discovery of five new dwarf galaxies, Andromeda XXIII-XXVII, located in the outer halo of M31. These galaxies were discovered during the second year of data from the Pan-Andromeda ...Archaeological Survey (PAndAS), a photometric survey of the M31/M33 subgroup conducted with the MegaPrime/MegaCam wide-field camera on the Canada-France-Hawaii Telescope. The current PAndAS survey now provides an almost complete panoramic view of the M31 halo out to an average projected radius of ~150 kpc. Here we present for the first time the metal-poor stellar density map for this whole region, not only as an illustration of the discovery space for satellite galaxies, but also as a birds-eye view of the ongoing assembly process of an L * disk galaxy. Four of the newly discovered satellites appear as well-defined spatial overdensities of stars lying on the expected locus of metal-poor (--2.5 < Fe/H < --1.3) red giant branch stars at the distance of M31. The fifth overdensity, And XXVII, is embedded in an extensive stream of such stars and is possibly the remnant of a strong tidal disruption event. Based on distance estimates from horizontal branch magnitudes, all five have metallicities typical of dwarf spheroidal galaxies ranging from Fe/H =--1.7 ? 0.2 to Fe/H =--1.9 ? 0.2 and absolute magnitudes ranging from MV = --7.1 ? 0.5 to MV = --10.2 ? 0.5. These five additional satellites bring the number of dwarf spheroidal galaxies in this region to 25 and continue the trend whereby the brighter dwarf spheroidal satellites of M31 generally have much larger half-light radii than their Milky Way counterparts. With an extended sample of M31 satellite galaxies, we also revisit the spatial distribution of this population and in particular we find that, within the current projected limits of the PAndAS survey, the surface density of satellites is essentially constant out to 150 kpc. This corresponds to a radial density distribution of satellites varying as r --1, a result seemingly in conflict with the predictions of cosmological simulations.
Sorghum (
L. Moench) is a C4 tropical grass that plays an essential role in providing nutrition to humans and livestock, particularly in marginal rainfall environments. The timing of head development ...and the number of heads per unit area are key adaptation traits to consider in agronomy and breeding but are time consuming and labor intensive to measure. We propose a two-step machine-based image processing method to detect and count the number of heads from high-resolution images captured by unmanned aerial vehicles (UAVs) in a breeding trial. To demonstrate the performance of the proposed method, 52 images were manually labeled; the precision and recall of head detection were 0.87 and 0.98, respectively, and the coefficient of determination (
) between the manual and new methods of counting was 0.84. To verify the utility of the method in breeding programs, a geolocation-based plot segmentation method was applied to pre-processed ortho-mosaic images to extract >1000 plots from original RGB images. Forty of these plots were randomly selected and labeled manually; the precision and recall of detection were 0.82 and 0.98, respectively, and the coefficient of determination between manual and algorithm counting was 0.56, with the major source of error being related to the morphology of plants resulting in heads being displayed both within and outside the plot in which the plants were sown, i.e., being allocated to a neighboring plot. Finally, the potential applications in yield estimation from UAV-based imagery from agronomy experiments and scouting of production fields are also discussed.
PDF
