Does corn market uncertainty impact the US ethanol prices?

The growing interest in biofuel as a green energy source has intensified the linkages between corn and ethanol markets, especially in the United States that represents the largest producing and exporting country for ethanol in the world. In this study, we examine the effect of corn market uncertainty on the price changes of US ethanol applying a set of GARCH‐jump models. We find that the US ethanol price changes react positively to the corn market volatility shocks after controlling for the effect of oil price uncertainty. In addition, we document that the impact of corn price volatility on the US ethanol prices appears to be asymmetric. Specifically, only the positive corn market volatility shocks are found to influence the ethanol market returns. Our findings also suggest that time‐varying jumps do exist in the ethanol market.     

Surviving within the amoebal exocyst: the <Emphasis Type="Italic">Mycobacterium avium</Emphasis> complex paradigm

Background  

Most of environmental mycobacteria have been previously demonstrated to resist free-living amoeba with subsequent increased virulence and resistance to antibiotics and biocides. The Mycobacterium avium complex (MAC) comprises of environmental organisms that inhabit a wide variety of ecological niches and exhibit a significant degree of genetic variability. We herein studied the intra-ameobal location of all members of the MAC as model organisms for environmental mycobacteria.     

Whole Mitochondrial and Plastid Genome SNP Analysis of Nine Date Palm Cultivars Reveals Plastid Heteroplasmy and Close Phylogenetic Relationships among Cultivars

Date palm is a very important crop in western Asia and northern Africa, and it is the oldest domesticated fruit tree with archaeological records dating back 5000 years. The huge economic value of this crop has generated considerable interest in breeding programs to enhance production of dates. One of the major limitations of these efforts is the uncertainty regarding the number of date palm cultivars, which are currently based on fruit shape, size, color, and taste. Whole mitochondrial and plastid genome sequences were utilized to examine single nucleotide polymorphisms (SNPs) of date palms to evaluate the efficacy of this approach for molecular characterization of cultivars. Mitochondrial and plastid genomes of nine Saudi Arabian cultivars were sequenced. For each species about 60 million 100 bp paired-end reads were generated from total genomic DNA using the Illumina HiSeq 2000 platform. For each cultivar, sequences were aligned separately to the published date palm plastid and mitochondrial reference genomes, and SNPs were identified. The results identified cultivar-specific SNPs for eight of the nine cultivars. Two previous SNP analyses of mitochondrial and plastid genomes identified substantial intra-cultivar ( = intra-varietal) polymorphisms in organellar genomes but these studies did not properly take into account the fact that nearly half of the plastid genome has been integrated into the mitochondrial genome. Filtering all sequencing reads that mapped to both organellar genomes nearly eliminated mitochondrial heteroplasmy but all plastid SNPs remained heteroplasmic. This investigation provides valuable insights into how to deal with interorganellar DNA transfer in performing SNP analyses from total genomic DNA. The results confirm recent suggestions that plastid heteroplasmy is much more common than previously thought. Finally, low levels of sequence variation in plastid and mitochondrial genomes argue for using nuclear SNPs for molecular characterization of date palm cultivars.     

Probing the relationship between Gram-negative and Gram-positive S1 proteins by sequence analysis

Escherichia coli ribosomal protein S1 is required for the translation initiation of messenger RNAs, in particular when their Shine–Dalgarno sequence is degenerated. Closely related forms of the protein, composed of the same number of domains (six), are found in all Gram-negative bacteria. More distant proteins, generally formed of fewer domains, have been identified, by sequence similarities, in Gram-positive bacteria and are also termed ‘S1 proteins’. However in the absence of functional information, it is generally difficult to ascertain their relationship with Gram-negative S1. In this article, we report the solution structure of the fourth and sixth domains of the E. coli protein S1 and show that it is possible to characterize their β-barrel by a consensus sequence that allows a precise identification of all domains in Gram-negative and Gram-positive S1 proteins. In addition, we show that it is possible to discriminate between five domain types corresponding to the domains 1, 2, 3, 4–5 and 6 of E. coli S1 on the basis of their sequence. This enabled us to identify the nature of the domains present in Gram-positive proteins and, subsequently, to probe the filiations between all forms of S1.     

Genetic analysis of agronomic traits in a cross between sugarcane (Saccharum officinarum L.) and its presumed progenitor (S. robustum Brandes & Jesw. ex Grassl)

Saccharum robustum Brandes & Jesw. ex Grassl has been suggested as the immediate progenitor species of cultivated sugarcane (S. officinarum L.) [4]. Chromosome pairing and assortment in these two species were previously studied by genetic analysis of single-dose DNA markers in parents in and 44 F₁ progeny of a cross between euploid, meiotically regular 2n=80S. officinarum LA Purple andS. robustum Mol 5829 [2]. This same population was subsequently clonally propagated and evaluated in replicated trials for quantitative traits important to sugarcane breeders. Numbers of stalks, tasseled stalks, and stalks with smut, and the average diameter of two stalks were determined one day prior to harvest. At harvest, plant material from each plot was weighed and evaluated for pol (sucrose content) and fiber percentages. Clones were significantly different (P<0.01) for all traits analyzed. Associations of 83 single-dose arbitrarily primed PCR genetic markers with quantitative trait loci (QTL) of recorded traits was determined by single-factor ANOVA, and multiple regression. QTL analysis revealed markers significantly (P<0.05) associated with the expression of each trait analyzed. Markers associated with QTL after multiple regression were tested for digenic linear × linear epistatic interactions. The various multilocus models explained between 23% and 58% of the total phenotypic variation and 32% and 76% of the genotypic variation for the various traits. Digenic interactions were uncommon. Implications for marker-assisted selection in sugarcane and sugarcane domestication are discussed.     

Advances in application of machine learning to life cycle assessment: a literature review

Purpose

Life Cycle Assessment (LCA) is the process of systematically assessing impacts when there is an interaction between the environment and human activity. Machine learning (ML) with LCA methods can help contribute greatly to reducing impacts. The sheer number of input parameters and their uncertainties that contribute to the full life cycle make a broader application of ML complex and difficult to achieve. Hence a systems engineering approach should be taken to apply ML in isolation to aspects of the LCA. This study addresses the challenge of leveraging ML methods to deliver LCA solutions. The overarching hypothesis is that: LCA underpinned by ML methods and informed by dynamic data paves the way to more accurate LCA while supporting life cycle decision making.

Methods

In this study, previous research on ML for LCA were considered, and a literature review was undertaken.

Results

The results showed that ML can be a useful tool in certain aspects of the LCA. ML methods were shown to be applied efficiently in optimization scenarios in LCA. Finally, ML methods were integrated as part of existing inventory databases to streamline the LCA across many use cases.

Conclusions

The conclusions of this article summarise the characteristics of existing literature and provide suggestions for future work in limitations and gaps which were found in the literature.

     

A high-frequency lung injury mechanism in blunt thoracic impact

When a mechanical load is applied very rapidly to the thoracic wall, part of the internal damage is suspected to be due to a "high-frequency" injury mechanism, that is, a phenomenon in which waves are involved. This paper addresses a specific high-frequency mechanism for lung injury in which a stress wave is generated through rapid acceleration of the body wall. Displacement-related injuries, which are rather "low-frequency" phenomena, are not considered. The present work was done in the context of assessing behind armor blunt trauma (injury to thoracic organs occurring when a bullet is stopped by a body armor) through mathematical modeling. One aspect of the thorax response to high-speed blunt impact and an associated injury mechanism are investigated based on an idealized model of thorax and a set of computations presented in previous papers. The injury mechanism considered elucidates a possible mathematical relationship between the acceleration at the surface of the thoracic wall and the occurrence of lung injury.