Why do oil importers diversify their import sources politically? : evidence from U.S. firm-level data

International politics affects oil trade. But why? We construct a firm-level dataset for all U.S. oil-importing companies over 1986-2008 to examine what kinds of firms are more responsive to change in "political distance" between the U.S. and her trading partners, measured by divergence in their UN General Assembly voting patterns. Consistent with previous macro evidence, we first show that individual firms diversify their oil imports politically, even after controlling for unobserved firm heterogeneity. We conjecture that the political pattern of oil imports from these individual firms is driven by hold-up risks, because oil trade is often associated with backward vertical FDI. To test this hold-up risk hypothesis, we investigate heterogeneity in responses by matching transaction-level import data with firm-level worldwide reserves. Our results show that long-run oil import decisions are indeed more elastic for firms with oil reserves overseas than those without, although the reverse is true in the short run. We interpret this empirical regularity as that while firms trade in the spot market can adjust their imports immediately, vertically-integrated firms with investment overseas tend to commit to term contracts in the short run even though they are more responsive to changes in international politics in the long run.

Level 2 reliability of simplified pushover methods

Pushover methods are being used as an everyday tool in engineering practice and some of them have been included in Regulatory Codes. Recently several efforts have been done trying to look at them from a probabilistic viewpoint. In this paper the authors shall present a Level 2 approach based on a probabilistic definition of the characteristic points defining the response spectra as well as a probabilistic definition of the elasto-plastic pushover curve representing the structural behavior. Comparisons with Montecarlo simulations will help to precise the accuracy of the proposed approach.

Low- and high-level transgenic expression of β2-adrenergic receptors differentially affect cardiac hypertrophy and function in Gαq-overexpressing mice

Transgenic overexpression of Gαq in the heart triggers events leading to a phenotype of eccentric hypertrophy, depressed ventricular function, marked expression of hypertrophy-associated genes, and depressed β-adrenergic receptor (βAR) function. The role of βAR dysfunction in the development of this failure phenotype was delineated by transgenic coexpression of the carboxyl terminus of the βAR kinase (βARK), which acts to inhibit the kinase, or concomitant overexpression of the β2AR at low (≈30-fold, Gαq/β2ARL), moderate (≈140-fold, Gαq/β2ARM), and high (≈1,000-fold, Gαq/β2ARH) levels above background βAR density. Expression of the βARK inhibitor had no effect on the phenotype, consistent with the lack of increased βARK levels in Gαq mice. In marked contrast, Gαq/β2ARL mice displayed rescue of hypertrophy and resting ventricular function and decreased cardiac expression of atrial natriuretic factor and α-skeletal actin mRNA. These effects occurred in the absence of any improvement in basal or agonist-stimulated adenylyl cyclase (AC) activities in crude cardiac membranes, although restoration of a compartmentalized β2AR/AC signal cannot be excluded. Higher expression of receptors in Gαq/β2ARM mice resulted in salvage of AC activity, but hypertrophy, ventricular function, and expression of fetal genes were unaffected or worsened. With ≈1,000-fold overexpression, the majority of Gαq/β2ARH mice died with cardiomegaly at 5 weeks. Thus, although it appears that excessive, uncontrolled, or generalized augmentation of βAR signaling is deleterious in heart failure, selective enhancement by overexpressing the β2AR subtype to limited levels restores not only ventricular function but also reverses cardiac hypertrophy.

Reduction in the level of Gal(alpha1,3)Gal in transgenic mice and pigs by the expression of an alpha(1,2)fucosyltransferase.

Hyperacute rejection of a porcine organ by higher primates is initiated by the binding of xenoreactive natural antibodies of the recipient to blood vessels in the graft leading to complement activation. The majority of these antibodies recognize the carbohydrate structure Gal(alphal,3)Gal (gal epitope) present on cells of pigs. It is possible that the removal or lowering of the number of gal epitopes on the graft endothelium could prevent hyperacute rejection. The Gal(alpha1,3) Gal structure is formed by the enzyme Galbeta1,4GlcNAc3-alpha-D-galactosyltransferase [alpha(1,3)GT; EC 2.4.1.51], which transfers a galactose molecule to terminal N-acetyllactosamine (N-lac) present on various glycoproteins and glycolipids. The N-lac structure might be utilized as an acceptor by other glycosyltransferases such as Galbeta1,4GlcNAc 6-alpha-D-sialyltransferase [alpha(2,6)ST], Galbeta1,4GlcNAc 3-alpha-D-Sialyltransferase [alpha(2,3)ST], or Galbeta 2-alpha-L-fucosyltransferase [alpha(1,2)FT; EC 2.4.1.691, etc. In this report we describe the competition between alpha(1,2)FT and alpha(1,3)GT in cells in culture and the generation of transgenic mice and transgenic pigs that express alpha(1,2)Fr leading to synthesis of Fucalpha,2Galbeta- (H antigen) and a concomitant decrease in the level of Gal(alpha1,3)Gal. As predicted, this resulted in reduced binding of xenoreactive natural antibodies to endothelial cells of transgenic mice and protection from complement mediated lysis.

Integrating the development of data mining and data warehouses via model-driven engineering

Data mining is one of the most important analysis techniques to automatically extract knowledge from large amount of data. Nowadays, data mining is based on low-level specifications of the employed techniques typically bounded to a specific analysis platform. Therefore, data mining lacks a modelling architecture that allows analysts to consider it as a truly software-engineering process. Bearing in mind this situation, we propose a model-driven approach which is based on (i) a conceptual modelling framework for data mining, and (ii) a set of model transformations to automatically generate both the data under analysis (that is deployed via data-warehousing technology) and the analysis models for data mining (tailored to a specific platform). Thus, analysts can concentrate on understanding the analysis problem via conceptual data-mining models instead of wasting efforts on low-level programming tasks related to the underlying-platform technical details. These time consuming tasks are now entrusted to the model-transformations scaffolding. The feasibility of our approach is shown by means of a hypothetical data-mining scenario where a time series analysis is required.

SMEs and Level 2 BIM, the Way Forward

The UK construction industry comprises a very high proportion of SMEs that is companies employing up to 250. A Department for Business, Innovation and Skills research paper, found that SMEs had a 71.2% share of work in the construction industry. Micro and small firms (i.e. those employing up to 50) had a share of 46.7% of work (Ive and Murray 2013). The Government has high ambitions for UK construction. Having been found by successive government commissioned studies to be inefficient and highly fragmented, ambitious targets have been set for the industry to achieve 33% reduction in costs and 50% faster delivery by 2025. As a significant construction client, the Government has mandated the use of Level 2 BIM from 2016 on publicly funded projects over £5 million. The adoption of BIM plays a key role in the 2025 vision but a lack of clarity persists in the industry over BIM and significant barriers are perceived to its implementation, particularly amongst SMEs. However, industry wide transformation will be challenging without serious consideration of the capabilities of this large majority. Many larger firms, having implemented Level 2 BIM are now working towards Level 3 BIM while many of the smaller firms in the industry have not even heard of BIM. It would seem that fears of a ‘two tier’ industry are perhaps being realised. This paper builds on an earlier one (Mellon & Kouider 2014) and investigates, through field work, the level of Level 2 BIM implementation amongst SMEs compared to a large organisation. Challenges and innovative solutions identified through collected data are fully discussed and compared. It is suggested that where the SME perceives barriers towards adoption of the technologies which underpin BIM, they may consider collaborative methods of working as an interim step in order to work towards realising the efficiencies and benefits that these methods can yield. While the barriers to adoption of BIM are significant, it is suggested that they are not insurmountable for the SME and some recommendations for possible solutions are made.