Regulation of dormancy in barley by blue light and after-ripening : effects on abscisic acid and gibberellin metabolism

White light strongly promotes dormancy in freshly harvested cereal grains, whereas dark and after-ripening have the opposite effect. We have analyzed the interaction of light and after-ripening on abscisic acid (ABA) and gibberellin (GA) metabolism genes and dormancy in barley (Hordeum vulgare ‘Betzes’). Analysis of gene expression in imbibed barley grains shows that different ABA metabolism genes are targeted by white light and after-ripening. Of the genes examined, white light promotes the expression of an ABA biosynthetic gene, HvNCED1, in embryos. Consistent with this result, enzyme-linked immunosorbent assays show that dormant grains imbibed under white light have higher embryo ABA content than grains imbibed in the dark. After-ripening has no effect on expression of ABA biosynthesis genes, but promotes expression of an ABA catabolism gene (HvABA8′OH1), a GA biosynthetic gene (HvGA3ox2), and a GA catabolic gene (HvGA2ox3) following imbibition. Blue light mimics the effects of white light on germination, ABA levels, and expression of GA and ABA metabolism genes. Red and far-red light have no effect on germination, ABA levels, or HvNCED1. RNA interference experiments in transgenic barley plants support a role of HvABA8′OH1 in dormancy release. Reduced HvABA8′OH1 expression in transgenic HvABA8′OH1 RNAi grains results in higher levels of ABA and increased dormancy compared to nontransgenic grains.

Timing and source constraints on the relationship between mafic and felsic intrusions in the Emeiashan large igneous province

Several I- and A-type granite, syenite plutons and spatially associated, giant Fe–Ti–V deposit-bearing mafic ultramafic layered intrusions occur in the Pan–Xi(Panzhihua–Xichang) area within the inner zone of the Emeishan large igneous province (ELIP). These complexes are interpreted to be related to the Emeishan mantle plume. We present LA-ICP-MS and SIMS zircon U–Pb ages and Hf–Nd isotopic compositions for the gabbros, syenites and granites from these complexes. The dating shows that the age of the felsic intrusive magmatism (256.2 ± 3.0–259.8 ± 1.6 Ma) is indistinguishable from that of the mafic intrusive magmatism (255.4 ± 3.1–259.5 ± 2.7 Ma) and represents the final phase of a continuous magmatic episode that lasted no more than 10 Myr. The upper gabbros in the mafic–ultramafic intrusions are generally more isotopically enriched (lower eNd and eHf) than the middle and lower gabbros, suggesting that the upper gabbros have experienced a higher level of crustal contamination than the lower gabbros. The significantly positive eHf(t) values of the A-type granites and syenites (+4.9 to +10.8) are higher than those of the upper gabbros of the associated mafic intrusion, which shows that they cannot be derived by fractional crystallization of these bodies. They are however identical to those of the mafic enclaves (+7.0 to +11.4) and middle and lower gabbros, implying that they are cogenetic. We suggest that they were generated by fractionation of large-volume, plume-related basaltic magmas that ponded deep in the crust. The deep-seated magma chamber erupted in two stages: the first near a density minimum in the basaltic fractionation trend and the second during the final stage of fractionation when the magma was a low density Fe-poor, Si-rich felsic magma. The basaltic magmas emplaced in the shallowlevel magma chambers differentiated to form mafic–ultramafic layered intrusions accompanied by a small amount of crustal assimilation through roof melting. Evolved A-type granites (synenites and syenodiorites) were produced dominantly by crystallization in the deep crustal magma chamber. In contrast, the I-type granites have negative eNd(t) [-6.3 to -7.5] and eHf(t) [-1.3 to -6.7] values, with the Nd model ages (T Nd DM2) of 1.63-1.67 Ga and Hf model ages (T Hf DM2) of 1.56-1.58 Ga, suggesting that they were mainly derived from partial melting of Mesoproterozoic crust. In combination with previous studies, this study also shows that plume activity not only gave rise to reworking of ancient crust, but also significant growth of juvenile crust in the center of the ELIP.

A critical analysis of business process management education and alignment with industry demand : an Australian perspective

Business Process Management (BPM) is accepted globally as an organizational approach to enhance productivity and drive cost efficiencies. Studies confirm a shortage of BPM skilled professionals with limited opportunities to develop the required BPM expertise. This study investigates this gap starting from a critical analysis of BPM courses offered by Australian universities and training institutions. These courses were analyzed and mapped against a leading BPM capability framework to determine how well current BPM education and training offerings in Australia address the core capabilities required by BPM professionals globally. To determine the BPM skill-sets sought by industry, online recruitment advertisements were collated, analyzed, and mapped against this BPM capability framework. The outcomes provide a detailed overview on the alignment of available BPM education/training and industry demand. These insights are useful for BPM professionals and their employers to build awareness of the BPM capabilities required for a BPM mature organization. Universities and other training institutions will benefit from these results by understanding where demand is, where the gaps are, and what other BPM education providers are supplying. This structured comparison method could continue to provide a common ground for future discussion across university-industry boundaries and continuous alignment of their respective practices.

Stiffness-damping matching method of an ECAS system based on LQG control

A novel method of matching stiffness and continuous variable damping of an ECAS (electronically controlled air suspension) based on LQG (linear quadratic Gaussian) control was proposed to simultaneously improve the road-friendliness and ride comfort of a two-axle school bus. Taking account of the suspension nonlinearities and target-height-dependent variation in suspension characteristics, a stiffness model of the ECAS mounted on the drive axle of the bus was developed based on thermodynamics and the key parameters were obtained through field tests. By determining the proper range of the target height for the ECAS of the fully-loaded bus based on the design requirements of vehicle body bounce frequency, the control algorithm of the target suspension height (i.e., stiffness) was derived according to driving speed and road roughness. Taking account of the nonlinearities of a continuous variable semi-active damper, the damping force was obtained through the subtraction of the air spring force from the optimum integrated suspension force, which was calculated based on LQG control. Finally, a GA (genetic algorithm)-based matching method between stepped variable damping and stiffness was employed as a benchmark to evaluate the effectiveness of the LQG-based matching method. Simulation results indicate that compared with the GA-based matching method, both dynamic tire force and vehicle body vertical acceleration responses are markedly reduced around the vehicle body bounce frequency employing the LQG-based matching method, with peak values of the dynamic tire force PSD (power spectral density) decreased by 73.6%, 60.8% and 71.9% in the three cases, and corresponding reduction are 71.3%, 59.4% and 68.2% for the vehicle body vertical acceleration. A strong robustness to variation of driving speed and road roughness is also observed for the LQG-based matching method.

Regulating virtual worlds : considering participant-driven approaches

There are a number of pressing issues facing contemporary online environments that are causing disputes among participants and platform operators and increasing the likelihood of external regulation. A number of solutions have been proposed, including industry self-governance, top-down regulation and emergent self-governance such as EVE Online’s “Council of Stellar Management”. However, none of these solutions seem entirely satisfying; facing challenges from developers who fear regulators will not understand their platforms, or players who feel they are not sufficiently empowered to influence the platform, while many authors have raised concerns over the implementation of top-down regulation, and why the industry may be well-served to pre-empt such action. This paper considers case studies of EVE Online and the offshore gambling industry, and whether a version of self-governance may be suitable for the future of the industry.

Rough set based approach to text classification

Textual document set has become an important and rapidly growing information source in the web. Text classification is one of the crucial technologies for information organisation and management. Text classification has become more and more important and attracted wide attention of researchers from different research fields. In this paper, many feature selection methods, the implement algorithms and applications of text classification are introduced firstly. However, because there are much noise in the knowledge extracted by current data-mining techniques for text classification, it leads to much uncertainty in the process of text classification which is produced from both the knowledge extraction and knowledge usage, therefore, more innovative techniques and methods are needed to improve the performance of text classification. It has been a critical step with great challenge to further improve the process of knowledge extraction and effectively utilization of the extracted knowledge. Rough Set decision making approach is proposed to use Rough Set decision techniques to more precisely classify the textual documents which are difficult to separate by the classic text classification methods. The purpose of this paper is to give an overview of existing text classification technologies, to demonstrate the Rough Set concepts and the decision making approach based on Rough Set theory for building more reliable and effective text classification framework with higher precision, to set up an innovative evaluation metric named CEI which is very effective for the performance assessment of the similar research, and to propose a promising research direction for addressing the challenging problems in text classification, text mining and other relative fields.