Genetic parameters and evaluations from single- and multiple-trait analysis of dairy cow fertility and milk production

Genetic parameters and breeding values for dairy cow fertility were estimated from 62 443 lactation records. Two-trait analysis of fertility and milk yield was investigated as a method to estimate fertility breeding values when culling or selection based on milk yield in early lactation determines presence or absence of fertility observations in later lactations. Fertility traits were calving interval, intervals from calving to first service, calving to conception and first to last service, conception success to first service and number of services per conception. Milk production traits were 305-day milk, fat and protein yield. For fertility traits, range of estimates of heritability (h(2)) was 0.012 to 0.028 and of permanent environmental variance (c(2)) was 0.016 to 0.032. Genetic correlations (r(g)) among fertility traits were generally high ( > 0.70). Genetic correlations of fertility with milk production traits were unfavourable (range -0.11 to 0.46). Single and two-trait analyses of fertility were compared using the same data set. The estimates of h(2) and c(2) were similar for two types of analyses. However, there were differences between estimated breeding values and rankings for the same trait from single versus multi-trait analyses. The range for rank correlation was 0.69-0.83 for all animals in the pedigree and 0.89-0.96 for sires with more than 25 daughters. As single-trait method is biased due to selection on milk yield, a multi-trait evaluation of fertility with milk yield is recommended. (C) 2002 Elsevier Science B.V. All rights reserved.

A structural time series approach to modelling multiple and resurgent meat scares in Italy

This paper exploits a structural time series approach to model the time pattern of multiple and resurgent food scares and their direct and cross-product impacts on consumer response. A structural time series Almost Ideal Demand System (STS-AIDS) is embedded in a vector error correction framework to allow for dynamic effects (VEC-STS-AIDS). Italian aggregate household data on meat demand is used to assess the time-varying impact of a resurgent BSE crisis (1996 and 2000) and the 1999 Dioxin crisis. The VEC-STS-AIDS model monitors the short-run impacts and performs satisfactorily in terms of residuals diagnostics, overcoming the major problems encountered by the customary vector error correction approach.

Influence-matrix diagnostic of a data assimilation system

The influence matrix is used in ordinary least-squares applications for monitoring statistical multiple-regression analyses. Concepts related to the influence matrix provide diagnostics on the influence of individual data on the analysis - the analysis change that would occur by leaving one observation out, and the effective information content (degrees of freedom for signal) in any sub-set of the analysed data. In this paper, the corresponding concepts have been derived in the context of linear statistical data assimilation in numerical weather prediction. An approximate method to compute the diagonal elements of the influence matrix (the self-sensitivities) has been developed for a large-dimension variational data assimilation system (the four-dimensional variational system of the European Centre for Medium-Range Weather Forecasts). Results show that, in the boreal spring 2003 operational system, 15% of the global influence is due to the assimilated observations in any one analysis, and the complementary 85% is the influence of the prior (background) information, a short-range forecast containing information from earlier assimilated observations. About 25% of the observational information is currently provided by surface-based observing systems, and 75% by satellite systems. Low-influence data points usually occur in data-rich areas, while high-influence data points are in data-sparse areas or in dynamically active regions. Background-error correlations also play an important role: high correlation diminishes the observation influence and amplifies the importance of the surrounding real and pseudo observations (prior information in observation space). Incorrect specifications of background and observation-error covariance matrices can be identified, interpreted and better understood by the use of influence-matrix diagnostics for the variety of observation types and observed variables used in the data assimilation system. Copyright © 2004 Royal Meteorological Society

Allelic size standards and reference genotypes to unify international cocoa (Theobroma cacao L.) microsatellite data

Standardisation of microsatellite allele profiles between laboratories is of fundamental importance to the transferability of genetic fingerprint data and the identification of clonal individuals held at multiple sites. Here we describe two methods of standardisation applied to the microsatellite fingerprinting of 429 Theobroma cacao L. trees representing 345 accessions held in the worlds largest Cocoa Intermediate Quarantine facility: the use of a partial allelic ladder through the production of 46 cloned and sequenced allelic standards (AJ748464 to AJ48509), and the use of standard genotypes selected to display a diverse allelic range. Until now a lack of accurate and transferable identification information has impeded efforts to genetically improve the cocoa crop. To address this need, a global initiative to fingerprint all international cocoa germplasm collections using a common set of 15 microsatellite markers is in progress. Data reported here have been deposited with the International Cocoa Germplasm Database and form the basis of a searchable resource for clonal identification. To our knowledge, this is the first quarantine facility to be completely genotyped using microsatellite markers for the purpose of quality control and clonal identification. Implications of the results for retrospective tracking of labelling errors are briefly explored.

Optimal foraging when regulating intake of multiple nutrients

There is growing evidence that, rather than maximizing energy intake subject to constraints, many animals attempt to regulate intake of multiple nutrients independently. In the complex diets of animals such as herbivores, the consumption of nutritionally imbalanced foods is sometimes inevitable, forcing trade-offs between eating too much of nutrients present in the foods in relative excess against too little of those in deficit. Such situations are not adequately represented in existing formulations of foraging theory. Here we provide the necessary theory to fit this case, using an approach that combines state-space models of nutrition with Tilman's models of resource exploitation (Tilman 1982, Resource Competition and Community Structure, Princeton: Princeton University Press). Our approach was to construct a smooth fitness landscape over nutrient space, centred on a 'target' intake at which no fitness cost is incurred, and this leads to a natural classification of the simple possible fitness landscapes based on Taylor series approximations of landscape shape. We next examined how needs for multiple nutrients can be assessed experimentally using direct measures of animal performance as the common currency, so that the nutritional strategies of animals can be mapped on to the performance surface, including the position of regulated points of intake and points of nutrient balance when fed suboptimal foods. We surveyed published data and conducted an experiment to map out the performance landscape of a generalist leaf-feeding caterpillar, Spodoptera littoralis. (C) 2004 Tire Association for the Study of Animal Behaviour. Poblished by Elsevier Ltd. All rights reserved.

Rapid parallel expression in E-coli and insect cells: Analysis of five lef gene products of the Autographa californica multiple nuclear polyhedrosis virus (AcMNPV)

A number of strategies are emerging for the high throughput (HTP) expression of recombinant proteins to enable structural and functional study. Here we describe a workable HTP strategy based on parallel protein expression in E. coli and insect cells. Using this system we provide comparative expression data for five proteins derived from the Autographa californica polyhedrosis virus genome that vary in amino acid composition and in molecular weight. Although the proteins are part of a set of factors known to be required for viral late gene expression, the precise function of three of the five, late expression factors (lefs) 6, 7 and 10, is unknown. Rapid expression and characterisation has allowed the determination of their ability to bind DNA and shown a cellular location consistent with their properties. Our data point to the utility of a parallel expression strategy to rapidly obtain workable protein expression levels from many open reading frames (ORFs).

A study of the effect of heat source location in a ventilated room using multiple regression analysis

Multiple regression analysis is a statistical technique which allows to predict a dependent variable from m ore than one independent variable and also to determine influential independent variables. Using experimental data, in this study the multiple regression analysis is applied to predict the room mean velocity and determine the most influencing parameters on the velocity. More than 120 experiments for four different heat source locations were carried out in a test chamber with a high level wall mounted air supply terminal at air change rates 3-6 ach. The influence of the environmental parameters such as supply air momentum, room heat load, Archimedes number and local temperature ratio, were examined by two methods: a simple regression analysis incorporated into scatter matrix plots and multiple stepwise regression analysis. It is concluded that, when a heat source is located along the jet centre line, the supply momentum mainly influences the room mean velocity regardless of the plume strength. However, when the heat source is located outside the jet region, the local temperature ratio (the inverse of the local heat removal effectiveness) is a major influencing parameter.

Clustering techniques applied to multiple-models structures

In this work a method for building multiple-model structures is presented. A clustering algorithm that uses data from the system is employed to define the architecture of the multiple-model, including the size of the region covered by each model, and the number of models. A heating ventilation and air conditioning system is used as a testbed of the proposed method.

Dimension and coverage of multiple-models structures using clustering techniques

In this work a method for building multiple-model structures is presented. A clustering algorithm that uses data from the system is employed to define the architecture of the multiple-model, including the size of the region covered by each model, and the number of models. A heating ventilation and air conditioning system is used as a testbed of the proposed method.

Multiple-scattering in radar systems: a review

Although extensively studied within the lidar community, the multiple scattering phenomenon has always been considered a rare curiosity by radar meteorologists. Up to few years ago its appearance has only been associated with two- or three-body-scattering features (e.g. hail flares and mirror images) involving highly reflective surfaces. Recent atmospheric research aimed at better understanding of the water cycle and the role played by clouds and precipitation in affecting the Earth's climate has driven the deployment of high frequency radars in space. Examples are the TRMM 13.5 GHz, the CloudSat 94 GHz, the upcoming EarthCARE 94 GHz, and the GPM dual 13-35 GHz radars. These systems are able to detect the vertical distribution of hydrometeors and thus provide crucial feedbacks for radiation and climate studies. The shift towards higher frequencies increases the sensitivity to hydrometeors, improves the spatial resolution and reduces the size and weight of the radar systems. On the other hand, higher frequency radars are affected by stronger extinction, especially in the presence of large precipitating particles (e.g. raindrops or hail particles), which may eventually drive the signal below the minimum detection threshold. In such circumstances the interpretation of the radar equation via the single scattering approximation may be problematic. Errors will be large when the radiation emitted from the radar after interacting more than once with the medium still contributes substantially to the received power. This is the case if the transport mean-free-path becomes comparable with the instrument footprint (determined by the antenna beam-width and the platform altitude). This situation resembles to what has already been experienced in lidar observations, but with a predominance of wide- versus small-angle scattering events. At millimeter wavelengths, hydrometeors diffuse radiation rather isotropically compared to the visible or near infrared region where scattering is predominantly in the forward direction. A complete understanding of radiation transport modeling and data analysis methods under wide-angle multiple scattering conditions is mandatory for a correct interpretation of echoes observed by space-borne millimeter radars. This paper reviews the status of research in this field. Different numerical techniques currently implemented to account for higher order scattering are reviewed and their weaknesses and strengths highlighted. Examples of simulated radar backscattering profiles are provided with particular emphasis given to situations in which the multiple scattering contributions become comparable or overwhelm the single scattering signal. We show evidences of multiple scattering effects from air-borne and from CloudSat observations, i.e. unique signatures which cannot be explained by single scattering theory. Ideas how to identify and tackle the multiple scattering effects are discussed. Finally perspectives and suggestions for future work are outlined. This work represents a reference-guide for studies focused at modeling the radiation transport and at interpreting data from high frequency space-borne radar systems that probe highly opaque scattering media such as thick ice clouds or precipitating clouds.

Binding of pentagalloyl glucose to two globular proteins occurs via multiple surface sites

The interaction between pentagalloyl glucose (PGG) and two globular proteins, bovine serum albumin (BSA) and ribulose-1,5-bisphosphate carboxylase oxygenase (rubisco), was investigated by isothermal titration calorimetry (ITC). ITC data fit to a binding model consisting of two sets of multiple binding sites, which reveal similarities in the mode of binding of PGG to BSA and rubisco. In both cases, the interaction is characterized by a high number of binding sites, which suggests that binding occurs by a surface adsorption mechanism that leads to coating of the protein surface, which promotes aggregation and precipitation of the PGG-protein complex. This model was confirmed by turbidimetry analysis of the PGG-BSA interaction. Analysis of tryptophan fluorescence quenching during the interaction of PGG with BSA suggests that binding of PGG leads to some conformational changes that are energetically closer to the unfolded state of the BSA structure, because small red shifts in the resulting emission spectra were observed.

Refinement of the Clinical Scenario Evaluation Framework for Assessment of Competing Development Strategies with an Application to Multiple Sclerosis

When competing strategies for development programs, clinical trial designs, or data analysis methods exist, the alternatives need to be evaluated in a systematic way to facilitate informed decision making. Here we describe a refinement of the recently proposed clinical scenario evaluation framework for the assessment of competing strategies. The refinement is achieved by subdividing key elements previously proposed into new categories, distinguishing between quantities that can be estimated from preexisting data and those that cannot and between aspects under the control of the decision maker from those that are determined by external constraints. The refined framework is illustrated by an application to a design project for an adaptive seamless design for a clinical trial in progressive multiple sclerosis.

The 11-yr solar cycle in ERA-40 data: an update to 2008

Multiple linear regression is used to diagnose the signal of the 11-yr solar cycle in zonal-mean zonal wind and temperature in the 40-yr ECMWF Re-Analysis (ERA-40) dataset. The results of previous studies are extended to 2008 using data from ECMWF operational analyses. This analysis confirms that the solar signal found in previous studies is distinct from that of volcanic aerosol forcing resulting from the eruptions of El Chichón and Mount Pinatubo, but it highlights the potential for confusion of the solar signal and lower-stratospheric temperature trends. A correction to an error that is present in previous results of Crooks and Gray, stemming from the use of a single daily analysis field rather than monthly averaged data, is also presented.

Multiple diversity measures to identify complementary conservation areas for the Baja California peninsular cacti

The Baja California Peninsula is home to 85 species of cacti, of which 54 are endemic, highlighting its importance as a cactus diverse region within Mexico. Many species are under threat due to collection pressure and habitat loss, but ensuring maximal protection of cacti species requires a better understanding of diversity patterns. We assessed species richness, endemism, and phylogenetic and morphological diversity using herbarium records and a molecular phylogeny for 82 species of cacti found in the peninsula. The four diversity measures were estimated for the existing nature reserve network and for 314 hexagrids of 726 km2. Using the hexagrid data, we surveyed our results for areas that best complement the current protected cacti diversity in the Baja California Peninsula. Currently, the natural reserve network in Baja shelters an important amount of the cacti diversity (74% of the species, 85.9% of the phylogenetic diversity, 76% of endemics and all the growth forms). While species richness produced several solutions to complement the diversity protected, by identifying priority species (endemic species with high contribution to overall PD) one best solution is reported. Three areas (San Matías, Magdalena and Margarita Islands and El Triunfo), selected using species richness, PD and endemism, best complement the diversity currently protected, increasing species richness to 89%, PD to 94% and endemism to 89%, and should be considered in future conservation plans. Two of these areas could be included within nature reserves already established.

The location of lightning affecting the ionospheric sporadic-E layer as evidence for multiple enhancement mechanisms

We present a study of the geographic location of lightning affecting the ionospheric sporadic-E (Es) layer over the ionospheric monitoring station at Chilton, UK. Data from the UK Met Office's Arrival Time Difference (ATD) lightning detection system were used to locate lightning strokes in the vicinity of the ionospheric monitoring station. A superposed epoch study of this data has previously revealed an enhancement in the Es layer caused by lightning within 200km of Chilton. In the current paper, we use the same data to investigate the location of the lightning strokes which have the largest effect on the Es layer above Chilton. We find that there are several locations where the effect of lightning on the ionosphere is most significant statistically, each producing different ionospheric responses. We interpret this as evidence that there is more than one mechanism combining to produce the previously observed enhancement in the ionosphere.