Summary Years of selection for desirable fruit quality traits in dessert watermelon (Citrullus lanatus) has resulted in a narrow genetic base in modern cultivars. Development of novel genomic and genetic resources offers great potential to expand genetic diversity and improve important traits in watermelon. Here, we report a high‐quality genome sequence of watermelon cultivar ‘Charleston Gray’, a principal American dessert watermelon, to complement the existing reference genome from ‘97103’, an East Asian cultivar. Comparative analyses between genomes of ‘Charleston Gray’ and ‘97103’ revealed genomic variants that may underlie phenotypic differences between the two cultivars. We then genotyped 1365 watermelon plant introduction (PI) lines maintained at the U.S. National Plant Germplasm System using genotyping‐by‐sequencing (GBS). These PI lines were collected throughout the world and belong to three Citrullus species, C. lanatus, C. mucosospermus and C. amarus. Approximately 25 000 high‐quality single nucleotide polymorphisms (SNPs) were derived from the GBS data using the ‘Charleston Gray’ genome as the reference. Population genomic analyses using these SNPs discovered a close relationship between C. lanatus and C. mucosospermus and identified four major groups in these two species correlated to their geographic locations. Citrullus amarus was found to have a distinct genetic makeup compared to C. lanatus and C. mucosospermus. The SNPs also enabled identification of genomic regions associated with important fruit quality and disease resistance traits through genome‐wide association studies. The high‐quality ‘Charleston Gray’ genome and the genotyping data of this large collection of watermelon accessions provide valuable resources for facilitating watermelon research, breeding and improvement.

Reservoir engineers use large-scale numerical models to predict the production performance in oil and gas fields. However, these models are constructed based on scarce and often inaccurate data, making their predictions highly uncertain. On the other hand, measurements of pressure and flow rates are constantly collected during the operation of the field. The assimilation of these data into the reservoir models (history matching) helps to mitigate uncertainty and improve their predictive capacity. History matching is a nonlinear inverse problem, which is typically handled using optimization and Monte Carlo methods. In practice, however, generating a set of properly history-matched models that preserve the geological realism is very challenging, especially in cases with complicated prior description, such as models with fractures and complex facies distributions. Recently, a new data-space inversion (DSI) approach was introduced in the literature as an alternative to the model-space inversion used in history matching. The essential idea is to update directly the predictions from a prior ensemble of models to account for the observed production history without updating the corresponding models. The present paper introduces a DSI implementation based on the use of an iterative ensemble smoother and demonstrates with examples that the new implementation is computationally faster and more robust than the earlier method based on principal component analysis. The new DSI is also applied to estimate the production forecast in a real field with long production history and a large number of wells. For this field problem, the new DSI obtained forecasts comparable with a more traditional ensemble-based history matching.

We present a second order logic of proportional quantifiers, SOLP, which is essentially a first order language extended with quantifiers that act upon second order variables of a given arity r, and count the fraction of elements in a subset of r-tuples of a model that satisfy a formula. Our logic is capable of expressing proportional versions of different problems of complexity up to NP-hard as, for example, the problem of deciding if at least a fraction 1/n of the set of vertices of a graph form a clique; and fragments within our logic capture complexity classes as NL and P, with auxiliary ordering relation.When restricted to monadic second order variables our logic of proportional quantifiers admits a semantic approximation based on almost linear orders, which is not as weak as other known logics with counting quantifiers (restricted to almost orders), for it does not has the bounded number of degrees property. Moreover, we show that in this almost ordered setting different fragments of this logic vary in their expressive power, and show the existence of an infinite hierarchy inside our monadic language. We extend our inexpressibility result over almost ordered structure to a fragment of SOLP, that in the presence of full order captures P. To obtain all our inexpressibility results we developed combinatorial games appropriate for these logics, whose application could go beyond the almost ordered models and hence are interesting by themselves.

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Abatement of NH3 emissions is crucial in calcareous soils under semiarid Mediterranean climates. The aim of the study was to compare NH3 emissions using different slurry application methods. An experiment was performed on a clay loam soil to evaluate NH3 emissions before sowing and at winter cereal tillering. Pig slurry was applied using two methods, one that applied slurry by splashing it over a plate (SP), and another that applied slurry in strips using trail hoses (TH). Emissions were measured using semi‐static chambers at variable intervals for 12 to 13 d (315.5 h for sowing and 287 h for tillering). Maximum NH3 flux emissions were always observed during the earliest period of measurements after slurry spreading (3.5–5 h). Before sowing, regardless of the method, accumulated NH3 losses (during 315.5 h) ranged between 2 and 3 kg NH3–N ha−1 because of the low dry matter content of the slurry (<2%), which enhanced infiltration. Losses represented about 2 to 3% of the total N applied. At cereal tillering, average accumulated losses of NH3 (during 287 h) were 1.7 kg N ha−1 using TH (1.1% of total N applied) and were as high as 5.4 kg N ha−1 (3.2% of total N applied) using SP. Because N topdressing is recommended as a measure to increase its efficiency, TH is recommended over SP. Thus, this short‐term study concludes that TH may reduce NH3 emissions in semiarid environments. Further study of these strategies is recommended under different climate and soil conditions. Core Ideas NH3 emissions from slurry splash plate (SP) spreading can be <4% of the NH4+ applied. Trail hoses (TH) reduce NH3 emissions from slurries versus SP at cereal tillering. At sowing, low slurry dry matter bridges the gap in NH3 emissions between TH and SP.