Effect of corn silage from an herbicide-tolerant genetically modified variety on milk production and absence of transgenic DNA in milk

Data from 60 multiparous Holstein cows were used in a 12-wk continuous design feeding trial. Cows were allocated to 1 of 4 experimental treatments (T1 to T4). In T1 and T2, the total mixed ration (TMR) contained either corn silage from the genetically modified (GM) variety Chardon Liberty Link, which is tolerant to the herbicide glufosinate ammonium, or its near isogenic nonGM counterpart, whereas the TMR used in T3 and T4 contained corn silage from the commercially available nonGM varieties Fabius and Antares, respectively. The objectives of the study were to determine if the inserted gene produced a marked effect on chemical composition, nutritive value, feed intake, and milk production, and to determine if transgenic DNA and the protein expressed by the inserted gene could be detected in bovine milk. The nutritive value, fermentation characteristics, mineral content, and amino acid composition of all 4 silages were similar. There were no significant treatment effects on milk yield, milk composition, and yield of milk constituents, and the dry matter (DM) intake of the GM variety was not significantly different from the 2 commercial varieties. However, although the DM intake noted for the nonGM near-isogenic variety was similar to the commercial varieties, it was significantly lower when compared with the GM variety. Polymerase chain reaction analyses of milk samples collected at wk 1, 6, and 12 of the study showed that none of the 90 milk samples tested positive, above a detection limit of 2.5 ng of total genomic DNA/mL of milk, for either tDNA (event T25) or the single-copy endogenous Zea mays gene, alcohol dehydrogenase. Using ELISA assays, the protein expressed by the T25 gene was not detected in milk.

Ruthenium complexes of C,C '-bis(ethynyl)carboranes: an investigation of electronic interactions mediated by spherical pseudo-aromatic spacers

The complexes [Ru(1-C=C-1,10-C2B8H9)(dppe)Cp*] (3a), [Ru(1-C C-1,12-C2B10H11)(dppe)-Cp*] (3b), [{Ru(dppe)Cp*}(2){mu-1,10-(C C)(2)-1,10-C2B8H8}] (4a) and [{Ru(dppe)Cp*}(2){mu-1,12-(C C)2- 1,12-C2B10-H-10}] (4b), which form a representative series of mono- and bimetallic acetylide complexes featuring 10- and 12-vertex carboranes embedded within the dethynyl bridging ligand, have been prepared and structurally characterized. In addition, these compounds have been examined spectroscopically (UV-is-NIR, IR) in all accessible redox states. The significant separation of the two, one-electron anodic waves observed in the cyclic voltammograms of the bimetallic complexes 4a and 4b is largely independent of the nature of the electrolyte and is attributed to stabilization of the intermediate redox products [4a](+) and [4b](+) through interactions between the metal centers across a distance of ca. 12.5 angstrom. The mono-oxidized bimetallic complexes (4a](+) and [4b](+) exhibit spectroscopic properties consistent with a description of these species in terms of valence-localized (class II) mixed-valence compounds, including a unique low-energy electronic absorption band, attributed to an, IVCT-type transition that tails into the IR region. DFT calculations with model systems [4a-H](+) and [4b-H](+) featuring simplified ligand sets reproduce the observed spectroscopic data and localized electronic structures for the mixed-valence cations [4a](+) and [4b](+).

On differentiating ground clutter and insect echoes from Doppler weather radars using archived data

Normally wind measurements from Doppler radars rely on the presence of rain. During fine weather, insects become a potential radar target for wind measurement. However, it is difficult to separate ground clutter and insect echoes when spectral or polarimetric methods are not available. Archived reflectivity and velocity data from repeated scans provide alternative methods. The probability of detection (POD) method, which maps areas with a persistent signal as ground clutter, is ineffective when most scans also contain persistent insect echoes. We developed a clutter detection method which maps the standard deviation of velocity (SDV) over a large number of scans, and can differentiate insects and ground clutter close to the radar. Beyond the range of persistent insect echoes, the POD method more thoroughly removes ground clutter. A new, pseudo-probability clutter map was created by combining the POD and SDV maps. The new map optimised ground clutter detection without removing insect echoes.

Conditioning of incremental variational data assimilation, with application to the Met Office system

Implementations of incremental variational data assimilation require the iterative minimization of a series of linear least-squares cost functions. The accuracy and speed with which these linear minimization problems can be solved is determined by the condition number of the Hessian of the problem. In this study, we examine how different components of the assimilation system influence this condition number. Theoretical bounds on the condition number for a single parameter system are presented and used to predict how the condition number is affected by the observation distribution and accuracy and by the specified lengthscales in the background error covariance matrix. The theoretical results are verified in the Met Office variational data assimilation system, using both pseudo-observations and real data.

Integration of a 3D Variational data assimilation scheme with a coastal area morphodynamic model of Morecambe Bay

This paper describes the implementation of a 3D variational (3D-Var) data assimilation scheme for a morphodynamic model applied to Morecambe Bay, UK. A simple decoupled hydrodynamic and sediment transport model is combined with a data assimilation scheme to investigate the ability of such methods to improve the accuracy of the predicted bathymetry. The inverse forecast error covariance matrix is modelled using a Laplacian approximation which is calibrated for the length scale parameter required. Calibration is also performed for the Soulsby-van Rijn sediment transport equations. The data used for assimilation purposes comprises waterlines derived from SAR imagery covering the entire period of the model run, and swath bathymetry data collected by a ship-borne survey for one date towards the end of the model run. A LiDAR survey of the entire bay carried out in November 2005 is used for validation purposes. The comparison of the predictive ability of the model alone with the model-forecast-assimilation system demonstrates that using data assimilation significantly improves the forecast skill. An investigation of the assimilation of the swath bathymetry as well as the waterlines demonstrates that the overall improvement is initially large, but decreases over time as the bathymetry evolves away from that observed by the survey. The result of combining the calibration runs into a pseudo-ensemble provides a higher skill score than for a single optimized model run. A brief comparison of the Optimal Interpolation assimilation method with the 3D-Var method shows that the two schemes give similar results.

Influence of the quasi-biennial oscillation on the extratropical winter stratosphere in an atmospheric general circulation model and in reanalysis data

The interannual variability of the stratospheric polar vortex during winter in both hemispheres is observed to correlate strongly with the phase of the quasi-biennial oscillation (QBO) in tropical stratospheric winds. It follows that the lack of a spontaneously generated QBO in most atmospheric general circulation models (AGCMs) adversely affects the nature of polar variability in such models. This study examines QBO–vortex coupling in an AGCM in which a QBO is spontaneously induced by resolved and parameterized waves. The QBO–vortex coupling in the AGCM compares favorably to that seen in reanalysis data [from the 40-yr ECMWF Re-Analysis (ERA-40)], provided that careful attention is given to the definition of QBO phase. A phase angle representation of the QBO is employed that is based on the two leading empirical orthogonal functions of equatorial zonal wind vertical profiles. This yields a QBO phase that serves as a proxy for the vertical structure of equatorial winds over the whole depth of the stratosphere and thus provides a means of subsampling the data to select QBO phases with similar vertical profiles of equatorial zonal wind. Using this subsampling, it is found that the QBO phase that induces the strongest polar vortex response in early winter differs from that which induces the strongest late-winter vortex response. This is true in both hemispheres and for both the AGCM and ERA-40. It follows that the strength and timing of QBO influence on the vortex may be affected by the partial seasonal synchronization of QBO phase transitions that occurs both in observations and in the model. This provides a mechanism by which changes in the strength of QBO–vortex correlations may exhibit variability on decadal time scales. In the model, such behavior occurs in the absence of external forcings or interannual variations in sea surface temperatures.

An effective approach for land-cover classification from airborne lidar fused with co-registered data

Airborne lidar provides accurate height information of objects on the earth and has been recognized as a reliable and accurate surveying tool in many applications. In particular, lidar data offer vital and significant features for urban land-cover classification, which is an important task in urban land-use studies. In this article, we present an effective approach in which lidar data fused with its co-registered images (i.e. aerial colour images containing red, green and blue (RGB) bands and near-infrared (NIR) images) and other derived features are used effectively for accurate urban land-cover classification. The proposed approach begins with an initial classification performed by the Dempster–Shafer theory of evidence with a specifically designed basic probability assignment function. It outputs two results, i.e. the initial classification and pseudo-training samples, which are selected automatically according to the combined probability masses. Second, a support vector machine (SVM)-based probability estimator is adopted to compute the class conditional probability (CCP) for each pixel from the pseudo-training samples. Finally, a Markov random field (MRF) model is established to combine spatial contextual information into the classification. In this stage, the initial classification result and the CCP are exploited. An efficient belief propagation (EBP) algorithm is developed to search for the global minimum-energy solution for the maximum a posteriori (MAP)-MRF framework in which three techniques are developed to speed up the standard belief propagation (BP) algorithm. Lidar and its co-registered data acquired by Toposys Falcon II are used in performance tests. The experimental results prove that fusing the height data and optical images is particularly suited for urban land-cover classification. There is no training sample needed in the proposed approach, and the computational cost is relatively low. An average classification accuracy of 93.63% is achieved.

The du2J mouse model of ataxia and absence epilepsy has deficient cannabinoid CB1 receptor-mediated signalling

Key point summary • Cerebellar ataxias are progressive debilitating diseases with no known treatment and are associated with defective motor function and, in particular, abnormalities to Purkinje cells. • Mutant mice with deficits in Ca2+ channel auxiliary α2δ-2 subunits are used as models of cerebellar ataxia. • Our data in the du2J mouse model shows an association between the ataxic phenotype exhibited by homozygous du2J/du2J mice and increased irregularity of Purkinje cell firing. • We show that both heterozygous +/du2J and homozygous du2J/du2J mice completely lack the strong presynaptic modulation of neuronal firing by cannabinoid CB1 receptors which is exhibited by litter-matched control mice. • These results show that the du2J ataxia model is associated with deficits in CB1 receptor signalling in the cerebellar cortex, putatively linked with compromised Ca2+ channel activity due to reduced α2δ-2 subunit expression. Knowledge of such deficits may help design therapeutic agents to combat ataxias. Abstract Cerebellar ataxias are a group of progressive, debilitating diseases often associated with abnormal Purkinje cell (PC) firing and/or degeneration. Many animal models of cerebellar ataxia display abnormalities in Ca2+ channel function. The ‘ducky’ du2J mouse model of ataxia and absence epilepsy represents a clean knock-out of the auxiliary Ca2+ channel subunit, α2δ-2, and has been associated with deficient Ca2+ channel function in the cerebellar cortex. Here, we investigate effects of du2J mutation on PC layer (PCL) and granule cell (GC) layer (GCL) neuronal spiking activity and, also, inhibitory neurotransmission at interneurone-Purkinje cell(IN-PC) synapses. Increased neuronal firing irregularity was seen in the PCL and, to a less marked extent, in the GCL in du2J/du2J, but not +/du2J, mice; these data suggest that the ataxic phenotype is associated with lack of precision of PC firing, that may also impinge on GC activity and requires expression of two du2J alleles to manifest fully. du2J mutation had no clear effect on spontaneous inhibitory postsynaptic current (sIPSC) frequency at IN-PC synapses, but was associated with increased sIPSC amplitudes. du2J mutation ablated cannabinoid CB1 receptor (CB1R)-mediated modulation of spontaneous neuronal spike firing and CB1Rmediated presynaptic inhibition of synaptic transmission at IN-PC synapses in both +/du2J and du2J/du2J mutants; effects that occurred in the absence of changes in CB1R expression. These results demonstrate that the du2J ataxia model is associated with deficient CB1R signalling in the cerebellar cortex, putatively linked with compromised Ca2+ channel activity and the ataxic phenotype.

Does terrorism threaten human rights? Evidence from panel data

Using panel data for 111 countries over the period 1982–2002, we employ two indexes that cover a wide range of human rights to empirically analyze whether and to what extent terrorism affects human rights. According to our results,terrorism significantly, but not dramatically, diminishes governments’ respect for basic human rights such as the absence of extrajudicial killings, political imprisonment, and torture. The result is robust to how we measure terrorist attacks, to the method of estimation, and to the choice of countries in our sample. However, we find no effect of terrorism on empowerment rights.

Forecasting US output growth with non-linear models in the presence of data uncertainty

We consider the impact of data revisions on the forecast performance of a SETAR regime-switching model of U.S. output growth. The impact of data uncertainty in real-time forecasting will affect a model's forecast performance via the effect on the model parameter estimates as well as via the forecast being conditioned on data measured with error. We find that benchmark revisions do affect the performance of the non-linear model of the growth rate, and that the performance relative to a linear comparator deteriorates in real-time compared to a pseudo out-of-sample forecasting exercise.

Absence of Melatonin Induces Night-Time Hepatic Insulin Resistance and Increased Gluconeogenesis Due to Stimulation of Nocturnal Unfolded Protein Response

It is known that the circadian rhythm in hepatic phosphoenolpyruvate carboxykinase expression (a limiting catalytic step of gluconeogenesis) and hepatic glucose production is maintained by both daily oscillation in autonomic inputs to the liver and night feeding behavior. However, increased glycemia and reduced melatonin (Mel) levels have been recently shown to coexist in diabetic patients at the end of the night period. In parallel, pinealectomy (PINX) is known to cause glucose intolerance with increased basal glycemia exclusively at the end of the night. The mechanisms that underlie this metabolic feature are not completely understood. Here, we demonstrate that PINX rats show night-time hepatic insulin resistance characterized by reduced insulin-stimulated RAC-alpha serine/threonine-protein kinase phosphorylation and increased phosphoenolpyruvate carboxykinase expression. In addition, PINX rats display increased conversion of pyruvate into glucose at the end of the night. The regulatory mechanism suggests the participation of unfolded protein response (UPR), because PINX induces night-time increase in activating transcription factor 6 expression and prompts a circadian fashion of immunoglobulin heavy chain-binding protein, activating transcription factor 4, and CCAAT/enhancer-binding protein-homologous protein expression with Zenith values at the dark period. PINX also caused a night-time increase in Tribble 3 and regulatory-associated protein of mammalian target of rapamycin; both were reduced in liver of PINX rats treated with Mel. Treatment of PINX rats with 4-phenyl butyric acid, an inhibitor of UPR, restored night-time hepatic insulin sensitivity and abrogated gluconeogenesis in PINX rats. Altogether, the present data show that a circadian oscillation of UPR occurs in the liver due to the absence of Mel. The nocturnal UPR activation is related with night-time hepatic insulin resistance and increased gluconeogenesis in PINX rats. (Endocrinology 152: 1253-1263, 2011)

Evolutionary fuzzy clustering of relational data

This paper is concerned with the computational efficiency of fuzzy clustering algorithms when the data set to be clustered is described by a proximity matrix only (relational data) and the number of clusters must be automatically estimated from such data. A fuzzy variant of an evolutionary algorithm for relational clustering is derived and compared against two systematic (pseudo-exhaustive) approaches that can also be used to automatically estimate the number of fuzzy clusters in relational data. An extensive collection of experiments involving 18 artificial and two real data sets is reported and analyzed. (C) 2011 Elsevier B.V. All rights reserved.

Regression analysis of mean quality-adjusted survival time based on pseudo-observations

Regression models for the mean quality-adjusted survival time are specified from hazard functions of transitions between two states and the mean quality-adjusted survival time may be a complex function of covariates. We discuss a regression model for the mean quality-adjusted survival (QAS) time based on pseudo-observations, which has the advantage of directly modeling the effect of covariates in the QAS time. Both Monte Carlo Simulations and a real data set are studied. Copyright (C) 2009 John Wiley & Sons, Ltd.

Non-durable consumption and real-estate prices in Brazil: panel-data analysis at the state level

Housing is an important component of wealth for a typical household in many countries. The objective of this paper is to investigate the effect of real-estate price variation on welfare, trying to close a gap between the welfare literature in Brazil and that in the U.S., the U.K., and other developed countries. Our first motivation relates to the fact that real estate is probably more important here than elsewhere as a proportion of wealth, which potentially makes the impact of a price change bigger here. Our second motivation relates to the fact that real-estate prices boomed in Brazil in the last five years. Prime real estate in Rio de Janeiro and São Paulo have tripled in value in that period, and a smaller but generalized increase has been observed throughout the country. Third, we have also seen a recent consumption boom in Brazil in the last five years. Indeed, the recent rise of some of the poor to middle-income status is well documented not only for Brazil but for other emerging countries as well. Regarding consumption and real-estate prices in Brazil, one cannot imply causality from correlation, but one can do causal inference with an appropriate structural model and proper inference, or with a proper inference in a reduced-form setup. Our last motivation is related to the complete absence of studies of this kind in Brazil, which makes ours a pioneering study. We assemble a panel-data set for the determinants of non-durable consumption growth by Brazilian states, merging the techniques and ideas in Campbell and Cocco (2007) and in Case, Quigley and Shiller (2005). With appropriate controls, and panel-data methods, we investigate whether house-price variation has a positive effect on non-durable consumption. The results show a non-negligible significant impact of the change in the price of real estate on welfare consumption), although smaller then what Campbell and Cocco have found. Our findings support the view that the channel through which house prices affect consumption is a financial one.

A risk management approach to emerging market's sovereign debt sustainability with an application to Brazilian data

In this paper we study the question of debt sustainability from a risk management perspective. The debt accumulation equation for any country involves variables that are stochastic and closely intertwined. When these aspects are taken into consideration the notion of debt sustainability is expanded to studying the stochastic properties of the debt dynamics. We illustrate the methodology by studying the Brazilian case. We find that even though the debt could be sustainable in the absence of risk, there are paths in which it is clearly unsustainable. Furthermore, we show that properties of the debt dynamics are closely related to the spreads on sovereign dollar denominated debt.