Biotechnology and Economic Development: The Economic Benefits of Maize Streak Virus Tolerant Maize in Kenya

For countries that could not benefit from the Green Revolution due to heterogeneous and unfavorable biophysical environments, agricultural biotechnology potentially provides a means of improving the quality and quantity of agricultural production. This paper analyses some of the major issues relating to the utilization of biotechnology in Kenya. A partial equilibrium trade model is applied to Kenya's corn market to study the potential of genetically modified maize that is tolerant to the Maize Streak Virus. The model accounts for home production and consumption; the positive results of the welfare estimation are disaggregated between consumers, large and small Kenyan corn farms.Community/Rural/Urban Development, Research and Development/Tech Change/Emerging Technologies,

Diversification and manager autonomy in fund families: Implications for investors

This paper aims to investigate the consequences of investing in a single fund family for investors. In essence, we focus on the correlation among portfolio holdings of funds with effects in terms of under-diversification for mutual fund investors, especially, if they invest in the same fund family. We also explore the fund manager autonomy in portfolio holding allocation within families and determine the characteristics of those fund families with higher autonomy. Our results show that a higher correlation among funds not only implies that families offer a lower diversification to investors; it also has a negative effect on their performance. However, investors’ performance benefits from a higher manager autonomy. Consequently, investors who select a single fund family could obtain higher returns in smaller fund families with considerable experience that do not belong to a banking or insurance group, as in the former, diversification and manager autonomy are higher

Intrinsic and extrinsic comparison results for isoperimetric quotients and capacities in weighted manifolds

Let (M, g)be a complete non-compact Riemannian manifold together with a function eh, which weights the Hausdorff measures associated to the Riemannian metric. In this work we assume lower or upper radial bounds on some weighted or unweighted curvatures of Mto deduce comparisons for the weighted isoperimetric quotient and the weighted capacity of metric balls in Mcentered at a point o ∈M. As a consequence, we obtain parabolicity and hyperbolicity criteria for weighted manifolds generalizing previous ones. A basic tool in our study is the analysis of the weighted Laplacian of the distance function from o. The technique extends to non-compact submanifolds properly immersed in Munder certain control on their weighted mean curvature

The Effects of the Peak-Peak Correlation on the Peak Model of Hierarchical Clustering

In two previous papers a semi-analytical model was presented for the hierarchical clustering of halos via gravitational instability from peaks in a random Gaussian field of density fluctuations. This model is better founded than the extended Press-Schechter model, which is known to agree with numerical simulations and to make similar predictions. The specific merger rate, however, shows a significant departure at intermediate captured masses. The origin of this was suspected as being the rather crude approximation used for the density of nested peaks. Here, we seek to verify this suspicion by implementing a more accurate expression for the latter quantity which accounts for the correlation among peaks. We confirm that the inclusion of the peak-peak correlation improves the specific merger rate, while the good behavior of the remaining quantities is preserved.Comment: ApJ accepted. 15 pages, including 4 figures. Also available at ftp://pcess1.am.ub.es/pub/ApJ/effectpp.ps.g

Galápago leproso – Mauremys leprosa (Schweigger, 1812)

Reptiles - Orden Quelonios - Familia Geoemydidae en la Enciclopedia Virtual de Vertebrados Españoles, http://www.vertebradosibericos.org/.A comprehensive review of the natural history of the Mediterranean stripe-necked terrapin Mauremys leprosa in Spain.Peer reviewe

Multivariate synthetic streamflow generation using a hybrid model based on artificial neural networks

International audienceA model for multivariate streamflow generation is presented, based on a multilayer feedforward neural network. The structure of the model results from two components, the neural network (NN) deterministic component and a random component which is assumed to be normally distributed. It is from this second component that the model achieves the ability to incorporate effectively the uncertainty associated with hydrological processes, making it valuable as a practical tool for synthetic generation of streamflow series. The NN topology and the corresponding analytical explicit formulation of the model are described in detail. The model is calibrated with a series of monthly inflows to two reservoir sites located in the Tagus River basin (Spain), while validation is performed through estimation of a set of statistics that is relevant for water resources systems planning and management. Among others, drought and storage statistics are computed and compared for both the synthetic and historical series. The performance of the NN-based model was compared to that of a standard autoregressive AR(2) model. Results show that NN represents a promising modelling alternative for simulation purposes, with interesting potential in the context of water resources systems management and optimisation. Keywords: neural networks, perceptron multilayer, error backpropagation, hydrological scenario generation, multivariate time-series.

Estimates for the ergodic measure and polynomial stability of plane stochastic curve shortening flow

We establish moment estimates for the invariant measure of a stochastic partial differential equation describing motion by mean curvature flow in (1+1) dimension, leading to polynomial stability of the associated Markov semigroup. We also prove maximal dissipativity for the related Kolmogorov operator

The Spiral that Vanished: The Application of Non-Contact Recording Techniques to an Elusive Rock Art Motif at Castlerigg Stone Circle in Cumbria

This article describes the recording of stone 11 of the Castlerigg stone circle in Cumbria through two different non-contact techniques: laser scanning and ground-based remote sensing. Despite the unproblematic recording of modern graffiti, neither technique was able to document the spiral photographed and rubbed in 1995. It is concluded that the spiral was most probably painted and has since faded away due to natural events. The discovery and loss of of the spiral motif in Castlerigg is seen as a cautionary tale. In particular, it seems to suggest that it is time to take advantage of the novel technologies based on the digitisation of 3D surfaces with millimetre and submillimetre accuracy such as laser scanning and ground-based remote sensing. They offer many advantages to the recording of prehistoric carvings. In addition to avoiding direct contact with the rock surface eliminating the preservation concerns raised by other techniques, both produce high quality images (laser scaning offering a greater potential for this, but at higher cost) having a much higher level of objectivity, and precision and accuracy far beyond those of traditional recording methods such as wax rubbings and scale drawings

Multivariate synthetic streamflow generation using a hybrid model based on artificial neural networks

A model for multivariate streamflow generation is presented, based on a multilayer feedforward neural network. The structure of the model results from two components, the neural network (NN) deterministic component and a random component which is assumed to be normally distributed. It is from this second component that the model achieves the ability to incorporate effectively the uncertainty associated with hydrological processes, making it valuable as a practical tool for synthetic generation of streamflow series. The NN topology and the corresponding analytical explicit formulation of the model are described in detail. The model is calibrated with a series of monthly inflows to two reservoir sites located in the Tagus River basin (Spain), while validation is performed through estimation of a set of statistics that is relevant for water resources systems planning and management. Among others, drought and storage statistics are computed and compared for both the synthetic and historical series. The performance of the NN-based model was compared to that of a standard autoregressive AR(2) model. Results show that NN represents a promising modelling alternative for simulation purposes, with interesting potential in the context of water resources systems management and optimisation.</p> <p style='line-height: 20px;'><b>Keywords: </b>neural networks, perceptron multilayer, error backpropagation, hydrological scenario generation, multivariate time-series.</p>

Mutant glycyl-tRNA synthetase (Gars) ameliorates SOD1G93A motor neuron degeneration phenotype but has little affect on Loa dynein heavy chain mutant mice

Background: In humans, mutations in the enzyme glycyl-tRNA synthetase (GARS) cause motor and sensory axon loss in the peripheral nervous system, and clinical phenotypes ranging from Charcot-Marie-Tooth neuropathy to a severe infantile form of spinal muscular atrophy. GARS is ubiquitously expressed and may have functions in addition to its canonical role in protein synthesis through catalyzing the addition of glycine to cognate tRNAs. Methodology/Principal findings: We have recently described a new mouse model with a point mutation in the Gars gene resulting in a cysteine to arginine change at residue 201. Heterozygous Gars^{C201R/+} mice have locomotor and sensory deficits. In an investigation of genetic mutations that lead to death of motor and sensory neurons, we have crossed the Gars^{C201R/+} mice to two other mutants: the TgSOD1^{G93A} model of human amyotrophic lateral sclerosis and the Legs at odd angles mouse (Dync1h1^{Loa}) which has a defect in the heavy chain of the dynein complex. We found the Dync1h1^{Loa/+}; Gars^{C201R/+} double heterozygous mice are more impaired than either parent, and this is may be an additive effect of both mutations. Surprisingly, the Gars^{C201R} mutation significantly delayed disease onset in the SOD1^{G93A}; Gars^{C201R/+} double heterozygous mutant mice and increased lifespan by 29% on the genetic background investigated. Conclusions/Significance: These findings raise intriguing possibilities for the study of pathogenetic mechanisms in all three mouse mutant strains