Effect of elevated CO2 and high temperature on seed-set and grain quality of rice

Hybrid vigour may help overcome the negative effects of climate change in rice. A popular rice hybrid (IR75217H), a heat-tolerant check (N22), and a mega-variety (IR64) were tested for tolerance of seed-set and grain quality to high-temperature stress at anthesis at ambient and elevated [CO2]. Under an ambient air temperature of 29 °C (tissue temperature 28.3 °C), elevated [CO2] increased vegetative and reproductive growth, including seed yield in all three genotypes. Seed-set was reduced by high temperature in all three genotypes, with the hybrid and IR64 equally affected and twice as sensitive as the tolerant cultivar N22. No interaction occurred between temperature and [CO2] for seed-set. The hybrid had significantly more anthesed spikelets at all temperatures than IR64 and at 29 °C this resulted in a large yield advantage. At 35 °C (tissue temperature 32.9 °C) the hybrid had a higher seed yield than IR64 due to the higher spikelet number, but at 38 °C (tissue temperature 34–35 °C) there was no yield advantage. Grain gel consistency in the hybrid and IR64 was reduced by high temperatures only at elevated [CO2], while the percentage of broken grains increased from 10% at 29 °C to 35% at 38 °C in the hybrid. It is concluded that seed-set of hybrids is susceptible to short episodes of high temperature during anthesis, but that at intermediate tissue temperatures of 32.9 °C higher spikelet number (yield potential) of the hybrid can compensate to some extent. If the heat tolerance from N22 or other tolerant donors could be transferred into hybrids, yield could be maintained under the higher temperatures predicted with climate change

Spatially resolved characterization of InGaAs/GaAs quantum dot structures by scanning spreading resistance microscopy

Cross-sectional scanning spreading resistance microscopy (SSRM) is used to investigate stacked InGaAs/GaAs quantum dot(QD)structures with different doping schemes. Spatially resolved imaging of the QDs by SSRM is demonstrated. The SSRM contrast obtained for the QD layers is found to depend on doping in the structure. In the undoped structures both QD-layers and QDs within the layers could be resolved, while in the dopedstructures the QD layers appear more or less uniformly broadened. The origin of the SSRM contrast in the QD layer in the different samples is discussed and correlated with doping schemes.T. Hakkarainen, O. Douhéret, and S. Anand would like to acknowledge the Swedish Research Council VR for fi- nancial support and the Kurt-Alice Wallenberg KAW foundation for financing the microscope. L. Fu, H. H. Tan, and C. Jagadish would like to acknowledge the Australian Research Council ARC for financial support and Australian National Fabrication Facility ANFF for access to the facilities

TAMARIND EXTRACT INHIBITS CYTOCHROME P450 (CYP3A4 ISOZYME) - AN IN VITRO STUDY

Objective: The aim of the present study was to analyze the effect of the aqueous fruit pulp extract of Tamarindus indica L. (tamarind extract) on cytochrome P 450 isoform CYP3A4.Methods: Tamarind extract at different concentrations from 5 to 100 μg/ml was examined for its inhibitory property toward cytochrome P 450 isoform CYP3A4. The various concentrations of tamarind extract, potassium phosphate buffer, CYP450 reagent, and substrate 7-Benzyloxy-4- trifluoromethylcoumarin were added to a 96-well plate. The mixtures were preincubated for 20 min at room temperature. The reaction was started by a mixture of free constituted substrate and NADP+ and incubated at room temperature for 30–60 min. The reaction was stopped by Tris-HCl buffer, pH 10.5. The fluorescent intensities of the products were measured by PerkinElmer Enspire fluorescence reader using an excitation and emission wavelength of 405 nm and 460 nm, respectively. Inhibitory concentration (IC50) was calculated by plotting concentrations of tamarind extract against the corresponding percentage inhibition.Results: All the tested concentrations of extract except 5 μg/ml showed good inhibition against CYP3A4 in a dose-dependent manner. The IC50 value of tamarind for CYP3A4 inhibitory activity was found to be 27.89 μg/ml.Conclusion: T. indica aqueous fruit pulp extract exhibited an inhibitory effect on CYP34A, thereby indicating the possibilities of herb-drug interaction if these extracts are coadministered with the prescribed drugs that are metabolized by CYP3A4

Increasing the coupling efficiency of a microdisk laser to waveguides by using well designed spiral structures

In this article, we optimize the coupling efficiency from a GaAs microdisk resonator into a single mode spiral waveguide. A classical microdisk resonator coupling light into a nonevanescent straight waveguide reaches a typical coupling efficiency of 67%. We show that the introduction of a spiral waveguide that works both as a waveguide and circular Bragg reflector can improve such efficiency to almost 90%. The same structure with the addition of a taper can couple up to 80% of the generated power into a slot waveguide.The authors would like to acknowledge the funding from the Australian Research Council for this project

Myocardial FFR (Fractional Flow Reserve) in patients with angiographically intermediate coronary artery stenosis - an initial institutional experience

Background: The clinical significance of coronary artery stenosis of intermediate severity can be difficult to determine. The management of intermediate coronary lesions, defined by a diameter stenosis of ≥40% to ≤70%, continues to be a therapeutic dilemma for cardiologists. The 2-dimensional representation of the arterial lesion provided by angiography is limited in distinguishing intermediate lesions that require stenting from those that simply need appropriate medical therapy. In the era of drug-eluting stents, some might propose that stenting all intermediate coronary lesions is an appropriate solution. However, the possibility of procedural complications such as coronary dissection, no reflow phenomenon, in-stent restenosis, and stent thrombosis requires accurate stratification of patients with intermediate coronary lesions to appropriate therapy. Myocardial fractional flow reserve (FFR) is an index of the functional severity of coronary stenosis that is calculated from pressure measurements made during coronary angiography. The objective of the study is to evaluate the usefulness of FFR in patients with angiographically intermediate coronary artery stenosis.Methods: 20 patients with intermediate coronary stenosis and chest pain of uncertain origin. The Exercise Electrocardiography (TMT), Myocardial Perfusion Imaging study (MPI), Quantitative Coronary Angiography (QCA) were compared with the results of FFR measurements.Results: 20 patients were undergone FFR measurement during the study period. With the mean age of 57.25±11.2 and male patients were 16 (80%), female patients 4 (20%), in all 13 patients with an FFR of 0.75 tested negative for reversible myocardial ischemia on TMT and MPI study. No revascularization procedures were performed in 7 (35%) patients, and no adverse cardiovascular events were noted in all these patients during 6 months of follow-up.Conclusions: In patients with coronary stenosis of intermediate severity, FFR appears to be a useful index of the functional severity of the stenosis and the need for coronary revascularization.

Using Parallel Genetic Algorithms for Estimating Model Parameters in Complex Reactive Transport Problems

In this study, we present the details of an optimization method for parameter estimation of one-dimensional groundwater reactive transport problems using a parallel genetic algorithm (PGA). The performance of the PGA was tested with two problems that had published analytical solutions and two problems with published numerical solutions. The optimization model was provided with the published experimental results and reasonable bounds for the unknown kinetic reaction parameters as inputs. Benchmarking results indicate that the PGA estimated parameters that are close to the published parameters and it also predicted the observed trends well for all four problems. Also, OpenMP FORTRAN parallel constructs were used to demonstrate the speedup of the code on an Intel quad-core desktop computer. The parallel code showed a linear speedup with an increasing number of processors. Furthermore, the performance of the underlying optimization algorithm was tested to evaluate its sensitivity to the various genetic algorithm (GA) parameters, including initial population size, number of generations, and parameter bounds. The PGA used in this study is generic and can be easily scaled to higher-order water quality modeling problems involving real-world application

One-dimensional and multi-dimensional substring selectivity estimation

With the increasing importance of XML, LDAP directories, and text-based information sources on the Internet, there is an ever-greater need to evaluate queries involving (sub)string matching. In many cases, matches need to be on multiple attributes/dimensions, with correlations between the multiple dimensions. Effective query optimization in this context requires good selectivity estimates. In this paper, we use pruned count-suffix trees (PSTs) as the basic data structure for substring selectivity estimation. For the 1-D problem, we present a novel technique called MO (Maximal Overlap). We then develop and analyze two 1-D estimation algorithms, MOC and MOLC, based on MO and a constraint-based characterization of all possible completions of a given PST. For the k -D problem, we first generalize PSTs to multiple dimensions and develop a space- and time-efficient probabilistic algorithm to construct k -D PSTs directly. We then show how to extend MO to multiple dimensions. Finally, we demonstrate, both analytically and experimentally, that MO is both practical and substantially superior to competing algorithms.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42330/1/778-9-3-214_00090214.pd

QuickSel: Quick Selectivity Learning with Mixture Models

Estimating the selectivity of a query is a key step in almost any cost-based query optimizer. Most of today's databases rely on histograms or samples that are periodically refreshed by re-scanning the data as the underlying data changes. Since frequent scans are costly, these statistics are often stale and lead to poor selectivity estimates. As an alternative to scans, query-driven histograms have been proposed, which refine the histograms based on the actual selectivities of the observed queries. Unfortunately, these approaches are either too costly to use in practice---i.e., require an exponential number of buckets---or quickly lose their advantage as they observe more queries. In this paper, we propose a selectivity learning framework, called QuickSel, which falls into the query-driven paradigm but does not use histograms. Instead, it builds an internal model of the underlying data, which can be refined significantly faster (e.g., only 1.9 milliseconds for 300 queries). This fast refinement allows QuickSel to continuously learn from each query and yield increasingly more accurate selectivity estimates over time. Unlike query-driven histograms, QuickSel relies on a mixture model and a new optimization algorithm for training its model. Our extensive experiments on two real-world datasets confirm that, given the same target accuracy, QuickSel is 34.0x-179.4x faster than state-of-the-art query-driven histograms, including ISOMER and STHoles. Further, given the same space budget, QuickSel is 26.8%-91.8% more accurate than periodically-updated histograms and samples, respectively