On the time for fold surfaces to order during the crystallization of polyethylene from the melt and its dependence on molecular parameters

New experiments underpin the interpretation of the basic division in crystallization behaviour of polyethylene in terms of whether or not there is time for the fold surface to order before the next molecular layer is added at the growth front. For typical growth rates, in Regime 11, polyethylene lamellae form with disordered {001} fold surfaces then transform, with lamellar thickening and twisting, towards the more-ordered condition found for slower crystallization in Regime 1, in which lamellae form with and retain {201} fold surfaces. Several linear and linear-low-density polyethylenes have been used to show that, for the same polymer crystallized alone or in a blend, the growth rate at which the change in initial lamellar condition occurs is reasonably constant thereby supporting the concept of a specific time for surfaces to attain the ordered {201}) state. This specific time, in the range from milliseconds to seconds, increases with molecular length, and in linear-low-density polymer, for higher branch contents. (c) 2006 Elsevier Ltd. All rights reserved.

Stages of organizational transformation in transition economies: A dynamic capabilities approach

How do organizations previously dominated by the state develop dynamic capabilities that would support their growth in a competitive market economy? We develop a theoretical framework of organizational transformation that explains the processes by which organizations learn and develop dynamic capabilities in transition economies. Specifically, the framework theorizes about the importance of, and inter-relationships between, leadership, organizational learning, dynamic capabilities, and performance over three stages of transformation. Propositions derived from this framework explain the pre-conditions enabling organizational learning, the linkages between types of learning and functions of dynamic capabilities, and the feedback from dynamic capabilities to organizational learning that allows firms in transition economies to regain their footing and build long-term competitive advantage. We focus on transition contexts, where these processes have been magnified and thus offer new insights into strategizing in radically altered environments.

Variational calculations of rovibrational states: a precise high-energy potential surface for HCN [and discussion]

We report the results of variational calculations of the rovibrational energy levels of HCN for J = 0, 1 and 2, where we reproduce all the ca. 100 observed vibrational states for all observed isotopic species, with energies up to 18000 cm$^{-1}$, to about $\pm $1 cm$^{-1}$, and the corresponding rotational constants to about $\pm $0.001 cm$^{-1}$. We use a hamiltonian expressed in internal coordinates r$_{1}$, r$_{2}$ and $\theta $, using the exact expression for the kinetic energy operator T obtained by direct transformation from the cartesian representation. The potential energy V is expressed as a polynomial expansion in the Morse coordinates y$_{i}$ for the bond stretches and the interbond angle $\theta $. The basis functions are built as products of appropriately scaled Morse functions in the bond-stretches and Legendre or associated Legendre polynomials of cos $\theta $ in the angle bend, and we evaluate matrix elements by Gauss quadrature. The hamiltonian matripx is factorized using the full rovibrational symmetry, and the basis is contracted to an optimized form; the dimensions of the final hamiltonian matrix vary from 240 $\times $ 240 to 1000 $\times $ 1000.We believe that our calculation is converged to better than 1 cm$^{-1}$ at 18 000 cm$^{-1}$. Our potential surface is expressed in terms of 31 parameters, about half of which have been refined by least squares to optimize the fit to the experimental data. The advantages and disadvantages and the future potential of calculations of this type are discussed.

Transformation of maize using silicon carbide whiskers

As the most commercially valuable cereal grown worldwide and the best-characterized in genetic terms, maize was predictably the first target for transformation among the important crops. Indeed, the first attempt at transformation of any plant was conducted on maize (1). These early efforts, however, were inevitably unsuccessful, since at that time, there were no reliable methods to permit the introduction of DNA into a cell, the expression of that DNA, and the identification of progeny derived from such a “transgenic” cell (2). Almost 20 years later, these technologies were finally combined, and the first transgenic cereals were produced. In the last few years, methods have become increasingly efficient, and transgenic maize has now been produced from protoplasts as well as from Agrobacterium-medieited or “Biolistic” delivery to embryogenic tissue (for a general comparison of methods used for maize, the reader is referred to a recent review—ref. 3). The present chapter will describe probably the simplest of the available procedures, namely the delivery of DNA to the recipient cells by vortexing them in the presence of silicon carbide (SiC) whiskers (this name will be used in preference to the term “fiber,” since it more correctly describes the single crystal nature of the material).

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.

Near infrared reflectance spectroscopy (NIRS) to predict biological parameters of maize silage: effects of particle comminution, oven drying temperature and the presence of residual moisture

Maize silage nutritive quality is routinely determined by near infrared reflectance spectroscopy (NIRS). However, little is known about the impact of sample preparation on the accuracy of the calibration to predict biological traits. A sample population of 48 maize silages representing a wide range of physiological maturities was used in a study to determine the impact of different sample preparation procedures (i.e., drying regimes; the presence or absence of residual moisture; the degree of particle comminution) on resultant NIR prediction statistics. All silages were scanned using a total of 12 combinations of sample pre-treatments. Each sample preparation combination was subjected to three multivariate regression techniques to give a total of 36 predictions per biological trait. Increased sample preparations procedure, relative to scanning the unprocessed whole plant (WP) material, always resulted in a numerical minimisation of model statistics. However, the ability of each of the treatments to significantly minimise the model statistics differed. Particle comminution was the most important factor, oven-drying regime was intermediate, and residual moisture presence was the least important. Models to predict various biological parameters of maize silage will be improved if material is subjected to a high degree of particle comminution (i.e., having been passed through a 1 mm screen) and developed on plant material previously dried at 60 degrees C. The extra effort in terms of time and cost required to remove sample residual moisture cannot be justified. (c) 2005 Elsevier B.V. All rights reserved.

Using near infrared reflectance spectroscopy (NIRS) to predict the biological parameters of maize silage

The microbial fermentability, ruminal degradability and digestibility of 48 maize silages were determined using in vitro gas production (GP), in situ degradability and in vitro digestibility procedures. The silages were produced from forage maize harvested throughout the summer of 1998, and represent a wide range of physiological maturities. Large variations among samples were observed for all biological parameters, with the exception of in vitro digestibility and the asymptote of in vitro GP. The potential of near infrared reflectance spectroscopy (NIRS) to predict the biological parameters measured was determined by regression of the biological data against the respective spectral profile. NIRS demonstrated only a moderate ability (R-2 > 0.60-0.80) to predict in vitro digestibility, modelled kinetics of gas production (excluding the asymptote of gas production) and the modelled ruminally soluble dry matter (DM) fraction. Calibration statistics for remaining biological parameters were unacceptably poor (R-2 = 0.60). (C) 2004 Elsevier B.V. All rights reserved.

Influence of vegetation on the local climate and hydrology in the tropics: sensitivity to soil parameters

Land use change with accompanying major modifications to the vegetation cover is widespread in the tropics, due to increasing demands for agricultural land, and may have significant impacts on the climate. This study investigates (1) the influence of vegetation on the local climate in the tropics; (2) how that influence varies from region to region; and (3) how the sensitivity of the local climate to vegetation, and hence land use change, depends on the hydraulic characteristics of the soil. A series of idealised experiments with the Hadley Centre atmospheric model, HadAM3, are described in which the influence of vegetation in the tropics is assessed by comparing the results of integrations with and without tropical vegetation. The sensitivity of the results to the soil characteristics is then explored by repeating the experiments with a differing, but equally valid, description of soil hydraulic parameters. The results have shown that vegetation has a significant moderating effect on the climate throughout the tropics by cooling the surface through enhanced latent heat fluxes. The influence of vegetation is, however, seasonally dependent, with much greater impacts during the dry season when the availability of surface moisture is limited. Furthermore, there are significant regional variations both in terms of the magnitude of the cooling and in the response of the precipitation. Not all regions show a feedback of vegetation on the local precipitation; this result has been related both to vegetation type and to the prevailing meteorological conditions. An important finding has been the sensitivity of the results to the specification of the soil hydraulic parameters. The introduction of more freely draining soils has changed the soil-moisture contents of the control, vegetated system and has reduced, significantly, the climate sensitivity to vegetation and by implication, land use change. Changes to the soil parameters have also had an impact on the soil hydrology and its interaction with vegetation, by altering the partitioning between fast and slow runoff processes. These results raise important questions about the representation of highly heterogeneous soil characteristics in climate models, as well as the potential influence of land use change on the soil characteristics themselves.

Relationships between transition period diet, metabolic parameters and fertility in lactating dairy cows

Cows in severe negative energy balance after calving have reduced fertility, mediated by metabolic signals influencing the reproductive system. We hypothesised that transition diet could alter metabolic status after calving, and thus influence fertility. Multiparous dairy cows were assigned to four transition groups 6 weeks pre-calving and fed: (a) basal control diet (n = 10); (b) basal diet plus barley (STARCH, n = 10); (c) basal diet plus Soypass (high protein, HiPROT, n = 11); or (d) no transition management (NoTRANS, n = 9). All cows received the same lactational diet. Blood samples, body weights and condition scores (BCS) were collected weekly. Fertility parameters were monitored using milk progesterone profiles and were not affected by transition diet. Data from all cows were then combined and analysed according to the pattern of post-partum ovarian activity. Cows with low progesterone profiles had significantly lower insulin-like growth factor-I (IGF-I) and insulin concentrations accompanied by reduced dry matter intakes (DMIs), BCS and body weight. Cows with prolonged luteal activity (PLA) were older and tended to have lower IGF-I. Analysis based on the calving to conception interval revealed that cows which failed to conceive (9/40) also had reduced IGF-I, BCS and body weight. Fertility was, therefore, decreased in cows which were in poor metabolic status following calving. This was reflected in reduced circulating IGF-I concentrations and compromised both ovarian activity and conception. There was little effect of the transition diets on these parameters. (C) 2003 Elsevier Science Inc. All rights reserved.