Effect of pyramiding Bt and CpTI genes on resistance of cotton to Helicoverpa armigera (Lepidoptera: Noctuidae) under laboratory and field conditions

Transgenic cotton (Gossypium hirsutum L.) varieties, adapted to China, have been bred that express two genes for resistance to insects. the Cry1Ac gene from Bacillus thuringiensis (Berliner) (Bt), and a trypsin inhibitor gene from cowpea (CpTI). Effectiveness of the double gene modification in conferring resistance to cotton bollworm, Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae), was studied in laboratory and field experiments. In each experiment, performance of Bt+CpTI cotton was compared with Bt cotton and to a conventional nontransgenic variety. Larval survival was lower on both types of transgenic variety, compared with the conventional cotton. Survival of first-, second-, and third-stage larvae was lower on Bt+CpTI cotton than on Bt cotton. Plant structures differed in level of resistance, and these differences were similar on Bt and Bt+CpTI cotton. Likewise, seasonal trends in level of resistance in different plant structures were similar in Bt and Bt+CpTI cotton. Both types of transgenic cotton interfered with development of sixth-stage larvae to adults, and no offspring was produced by H. armigera that fed on Bt or Bt+CpTI cotton from the sixth stage onward. First-, second-, and third-stage larvae spent significantly less time feeding on transgenic cotton than on conventional cotton, and the reduction in feeding time was significantly greater on Bt+CpTI cotton than on Bt cotton. Food conversion efficiency was lower on transgenic varieties than on conventional cotton, but there was no significant difference between Bt and Bt+CpTI cotton. In 3-yr field experimentation, bollworm densities were greatly suppressed on transgenic as compared with conventional cotton, but no significant differences between Bt and Bt+CpTI cotton were found. Overall, the results from laboratory work indicate that introduction of the CpTI gene in Bt cotton raises some components of resistance in cotton against H. armigera, but enhanced control of H. armigera under field conditions, due to expression of the CpTI gene, was not demonstrate

Possible discovery of the r-process characteristics in the abundances of metal-rich barium stars

We study the abundance distributions of a sample of metal-rich barium stars provided by Pereira et al. (2011) to investigate the s- and r-process nucleosynthesis in the metal-rich environment. We compared the theoretical results predicted by a parametric model with the observed abundances of the metal-rich barium stars. We found that six barium stars have a significant r-process characteristic, and we divided the barium stars into two groups: the r-rich barium stars ($C_r>5.0$, [La/Nd]\,$<0$) and normal barium stars. The behavior of the r-rich barium stars seems more like that of the metal-poor r-rich and CEMP-r/s stars. We suggest that the most possible formation mechanism for these stars is the s-process pollution, although their abundance patterns can be fitted very well when the pre-enrichment hypothesis is included. The fact that we can not explain them well using the s-process nucleosynthesis alone may be due to our incomplete knowledge on the production of Nd, Eu, and other relevant elements by the s-process in metal-rich and super metal-rich environments (see details in Pereira et al. 2011).Comment: 5 pages, 5 figures, accepted for publication in A&

Effect of solute content and temperature on the deformation mechanisms and critical resolved shear stress in Mg-Al and Mg-Zn alloys

The influence of solute atoms (Al and Zn) on the deformation mechanisms and the critical resolved shear stress for basal slip in Mg alloys at 298 K and 373 K was ascertained by micropillar compression tests in combination with high-throughput processing techniques based on the diffusion couples. It was found that the presence of solute atoms enhances the size effect at 298 K as well as the localization of deformation in slip bands, which is associated with large strain bursts in the resolved shear stress ($\tau_{RSS}$)-strain ($\epsilon$) curves. Deformation in pure Mg and Mg alloys was more homogeneous at 373 K and the influence of the micropillar size on the critical resolved shear stress was much smaller. In this latter case, it was possible to determine the effect of solute content on the critical resolved shear stress for basal slip in Mg-Al and Mg-Zn alloys

Investigation for the puzzling abundance pattern of the neutron-capture elements in the ultra metal-poor star: CS 30322-023

The s-enhanced and very metal-poor star CS 30322-023 shows a puzzling abundance pattern of the neutron-capture elements, i.e. several neutron-capture elements such as Ba, Pb etc. show enhancement, but other neutron-capture elements such as Sr, Eu etc. exhibit deficient with respect to iron. The study to this sample star could make people gain a better understanding of s- and r-process nucleosynthesis at low metallicity. Using a parametric model, we find that the abundance pattern of the neutron-capture elements could be best explained by a star that was polluted by an AGB star and the CS 30322-023 binary system formed in a molecular cloud which had never been polluted by r-process material. The lack of r-process material also indicates that the AGB companion cannot have undergone a type-1.5 supernova, and thus must have had an initial mass below 4.0M$_\odot$, while the strong N overabundance and the absence of a strong C overabundance indicate that the companion's initial mass was larger than 2.0M$_\odot$. The smaller s-process component coefficient of this star illustrates that there is less accreted material of this star from the AGB companion, and the sample star should be formed in the binary system with larger initial orbital separation where the accretion-induced collapse (AIC) mechanism can not work.Comment: 13 pages, 2 figure

A parametric time frequency-conditional Granger causality method using ultra-regularized orthogonal least squares and multiwavelets for dynamic connectivity analysis in EEGs

Objective: This study proposes a new para-metric TF-CGC (time-frequency conditional Granger causality) method for high-precision connectivity analysis over time and frequency domain in multivariate coupling nonstationary systems, and applies it to source EEG signals to reveal dynamic interaction patterns in oscillatory neo-cortical sensorimotor networks. Methods: The Geweke's spectral measure is combined with the TVARX (time-varying autoregressive with exogenous input) model-ling approach, which uses multiwavelet-based ul-tra-regularized orthogonal least squares (UROLS) algo-rithm aided by APRESS (adjustable prediction error sum of squares), to obtain high-resolution time-varying CGC representations. The UROLS-APRESS algorithm, which adopts both the regularization technique and the ultra-least squares criterion to measure not only the signal themselves but also the weak derivatives of them, is a novel powerful method in constructing time-varying models with good generalization performance, and can accurately track smooth and fast changing causalities. The generalized measurement based on CGC decomposition is able to eliminate indirect influences in multivariate systems. Re-sults: The proposed method is validated on two simulations and then applied to source level motor imagery (MI) EEGs, where the predicted distributions are well recovered with high TF precision, and the detected connectivity patterns of MI-EEGs are physiologically interpretable and yield new insights into the dynamical organization of oscillatory cor-tical networks. Conclusion: Experimental results confirm the effectiveness of the TF-CGC method in tracking rapidly varying causalities of EEG-based oscillatory networks. Significance: The novel TF-CGC method is expected to provide important information of neural mechanisms of perception and cognition

A review of closed-form Cramér-Rao Bounds for DOA estimation in the presence of Gaussian noise under a unified framework

The Cramér-Rao Bound (CRB) for direction of arrival (DOA) estimation has been extensively studied over the past four decades, with a plethora of CRB expressions reported for various parametric models. In the literature, there are different methods to derive a closed-form CRB expression, but many derivations tend to involve intricate matrix manipulations which appear difficult to understand. Starting from the Slepian-Bangs formula and following the simplest derivation approach, this paper reviews a number of closed-form Gaussian CRB expressions for the DOA parameter under a unified framework, based on which all the specific CRB presentations can be derived concisely. The results cover three scenarios: narrowband complex circular signals, narrowband complex noncircular signals, and wideband signals. Three signal models are considered: the deterministic model, the stochastic Gaussian model, and the stochastic Gaussian model with the a priori knowledge that the sources are spatially uncorrelated. Moreover, three Gaussian noise models distinguished by the structure of the noise covariance matrix are concerned: spatially uncorrelated noise with unknown either identical or distinct variances at different sensors, and arbitrary unknown noise. In each scenario, a unified framework for the DOA-related block of the deterministic/stochastic CRB is developed, which encompasses one class of closed-form deterministic CRB expressions and two classes of stochastic ones under the three noise models. Comparisons among different CRBs across classes and scenarios are presented, yielding a series of equalities and inequalities which reflect the benchmark for the estimation efficiency under various situations. Furthermore, validity of all CRB expressions are examined, with some specific results for linear arrays provided, leading to several upper bounds on the number of resolvable Gaussian sources in the underdetermined case