Proactive R&D management and firm growth: a punctuated equilibrium model

The external environment is characterized by periods of relative stability interspersed with periods of extreme change, implying that high performing firms must practice exploration and exploitation in order to survive and thrive. In this paper, we posit that R&D expenditure volatility indicates the presence of proactive R&D management, and is evidence of a firm moving from exploitation to exploration over time. This is consistent with a punctuated equilibrium model of R&D investment where shocks are induced by reactions to external turbulence. Using an unbalanced panel of almost 11,000 firm-years from 1997 to 2006, we show that greater fluctuations in the firm's R&D expenditure over time are associated with higher firm growth. Developing a contextual view of the relationship between R&D expenditure volatility and firm growth, we find that this relationship is weaker among firms with higher levels of corporate diversification and negative among smaller firms and those in slow clockspeed industries.

Simulation of tree-ring widths with a model for primary production, carbon allocation, and growth

We present a simple, generic model of annual tree growth, called "T". This model accepts input from a first-principles light-use efficiency model (the "P" model). The P model provides values for gross primary production (GPP) per unit of absorbed photosynthetically active radiation (PAR). Absorbed PAR is estimated from the current leaf area. GPP is allocated to foliage, transport tissue, and fine-root production and respiration in such a way as to satisfy well-understood dimensional and functional relationships. Our approach thereby integrates two modelling approaches separately developed in the global carbon-cycle and forest-science literature. The T model can represent both ontogenetic effects (the impact of ageing) and the effects of environmental variations and trends (climate and CO2) on growth. Driven by local climate records, the model was applied to simulate ring widths during the period 1958–2006 for multiple trees of Pinus koraiensis from the Changbai Mountains in northeastern China. Each tree was initialised at its actual diameter at the time when local climate records started. The model produces realistic simulations of the interannual variability in ring width for different age cohorts (young, mature, and old). Both the simulations and observations show a significant positive response of tree-ring width to growing-season total photosynthetically active radiation (PAR0) and the ratio of actual to potential evapotranspiration (α), and a significant negative response to mean annual temperature (MAT). The slopes of the simulated and observed relationships with PAR0 and α are similar; the negative response to MAT is underestimated by the model. Comparison of simulations with fixed and changing atmospheric CO2 concentration shows that CO2 fertilisation over the past 50 years is too small to be distinguished in the ring-width data, given ontogenetic trends and interannual variability in climate.

Celecoxib prevents tumor growth in an animal model by a COX-2 independent mechanism

Nonsteroidal antiinflammatory drugs (NSAIDs) have been shown to reduce cell growth in several tumors. Among these possible antineoplastic drugs are cyclooxygenase-2 (COX-2)-selective drugs, such as celecoxib, in which antitumoral mechanisms were evaluated in rats bearing Walker-256 (W256) tumor. W256 carcinosarcoma cells were inoculated subcutaneously (10(7) cells/rat) in rats submitted to treatment with celecoxib (25 mg kg(-1)) or vehicle for 14 days. Tumor growth, body-weight gain, and survival data were evaluated. The mechanisms, such as COX-2 expression and activity, oxidative stress, by means of enzymes and lipoperoxidation levels, and apoptosis mediators were also investigated. A reduction in tumor growth and an increased weight gain were observed. Celecoxib provided a higher incidence of survival compared with the control group. Cellular effects are probably COX-2 independent, because neither enzyme expression nor its activity, measured by tumoral PGE(2), showed significant difference between groups. It is probable that this antitumor action is dependent on an apoptotic way, which has been evaluated by the expression of the antiapoptotic protein Bcl-xL, in addition to the cellular changes observed by electronic microscopy. Celecoxib has also a possible involvement with redox homeostasis, because its administration caused significant changes in the activity of oxidative enzymes, such as catalase and superoxide dismutase. These results confirm the antitumor effects of celecoxib in W256 cancer model, contributing to elucidating its antitumoral mechanism and corroborating scientific literature about its effect on other types of cancer.

Bayesian Analysis for Nonlinear Regression Model Under Skewed Errors, with Application in Growth Curves

We have considered a Bayesian approach for the nonlinear regression model by replacing the normal distribution on the error term by some skewed distributions, which account for both skewness and heavy tails or skewness alone. The type of data considered in this paper concerns repeated measurements taken in time on a set of individuals. Such multiple observations on the same individual generally produce serially correlated outcomes. Thus, additionally, our model does allow for a correlation between observations made from the same individual. We have illustrated the procedure using a data set to study the growth curves of a clinic measurement of a group of pregnant women from an obstetrics clinic in Santiago, Chile. Parameter estimation and prediction were carried out using appropriate posterior simulation schemes based in Markov Chain Monte Carlo methods. Besides the deviance information criterion (DIC) and the conditional predictive ordinate (CPO), we suggest the use of proper scoring rules based on the posterior predictive distribution for comparing models. For our data set, all these criteria chose the skew-t model as the best model for the errors. These DIC and CPO criteria are also validated, for the model proposed here, through a simulation study. As a conclusion of this study, the DIC criterion is not trustful for this kind of complex model.

Ixolaris, a tissue factor inhibitor, blocks primary tumor growth and angiogenesis in a glioblastoma model

Background: The expression levels of the clotting initiator protein Tissue Factor (TF) correlate with vessel density and the histological malignancy grade of glioma patients. Increased procoagulant tonus in high grade tumors (glioblastomas) also indicates a potential role for TF in progression of this disease, and suggests that anticoagulants could be used as adjuvants for its treatment. Objectives: We hypothesized that blocking of TF activity with the tick anticoagulant Ixolaris might interfere with glioblastoma progression. Methods and results: TF was identified in U87-MG cells by flow-cytometric and functional assays (extrinsic tenase). In addition, flow-cytometric analysis demonstrated the exposure of phosphatidylserine in the surface of U87-MG cells, which supported the assembly of intrinsic tenase (FIXa/FVIIIa/FX) and prothrombinase (FVa/FXa/prothrombin) complexes, accounting for the production of FXa and thrombin, respectively. Ixolaris effectively blocked the in vitro TF-dependent procoagulant activity of the U87-MG human glioblastoma cell line and attenuated multimolecular coagulation complexes assembly. Notably, Ixolaris inhibited the in vivo tumorigenic potential of U87-MG cells in nude mice, without observable bleeding. This inhibitory effect of Ixolaris on tumor growth was associated with downregulation of VEGF and reduced tumor vascularization. Conclusion: Our results suggest that Ixolaris might be a promising agent for anti-tumor therapy in humans.

A time-varying markov-switching model for economic growth

This paper investigates economic growth’s pattern of variation across and within countries using a Time-Varying Transition Matrix Markov-Switching Approach. The model developed follows the approach of Pritchett (2003) and explains the dynamics of growth based on a collection of different states, each of which has a sub-model and a growth pattern, by which countries oscillate over time. The transition matrix among the different states varies over time, depending on the conditioning variables of each country, with a linear dynamic for each state. We develop a generalization of the Diebold’s EM Algorithm and estimate an example model in a panel with a transition matrix conditioned on the quality of the institutions and the level of investment. We found three states of growth: stable growth, miraculous growth, and stagnation. The results show that the quality of the institutions is an important determinant of long-term growth, whereas the level of investment has varying roles in that it contributes positively in countries with high-quality institutions but is of little relevance in countries with medium- or poor-quality institutions.

Growth and distribution: a revised classical model

This paper discusses distribution and the historical phases of capitalism. It assumes that technical progress and growth are taking place, and, given that, its question is on the functional distribution of income between labor and capital, having as reference classical theory of distribution and Marx’s falling tendency of the rate of profit. Based on the historical experience, it, first, inverts the model, making the rate of profit as the constant variable in the long run and the wage rate, as the residuum; second, it distinguishes three types of technical progress (capital-saving, neutral and capital-using) and applies it to the history of capitalism, having the UK and France as reference. Given these three types of technical progress, it distinguishes four phases of capitalist growth, where only the second is consistent with Marx prediction. The last phase, after World War II, should be, in principle, capital-saving, consistent with growth of wages above productivity. Instead, since the 1970s wages were kept stagnant in rich countries because of, first, the fact that the Information and Communication Technology Revolution proved to be highly capital using, opening room for a new wage of substitution of capital for labor; second, the new competition coming from developing countries; third, the emergence of the technobureaucratic or professional class; and, fourth, the new power of the neoliberal class coalition associating rentier capitalists and financiers

Evaluation of an average numerator relationship matrix model and a Bayesian hierarchical model for growth traits in Nellore cattle with uncertain paternity

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Random regression analyses using B-splines functions to model growth from birth to adult age in Canchim cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Random regression analyses using B-spline functions to model growth of Nellore cattle

The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.

Describing fatigue crack growth and load ratio effects in Al 2524 T3 alloy with an enhanced exponential model

The fatigue crack behavior in metals and alloys under constant amplitude test conditions is usually described by relationships between the crack growth rate da/dN and the stress intensity factor range Delta K. In the present work, an enhanced two-parameter exponential equation of fatigue crack growth was introduced in order to describe sub-critical crack propagation behavior of Al 2524-T3 alloy, commonly used in aircraft engineering applications. It was demonstrated that besides adequately correlating the load ratio effects, the exponential model also accounts for the slight deviations from linearity shown by the experimental curves. A comparison with Elber, Kujawski and "Unified Approach" models allowed for verifying the better performance, when confronted to the other tested models, presented by the exponential model. (C) 2012 Elsevier Ltd. All rights reserved.

Growth hormone 1 gene (GH1) polymorphisms as possible markers of the production potential of beef cattle using the Brazilian Canchim breed as a model

The growth hormone 1 gene (GH1) is a candidate gene for body weight and weight gain in cattle since it plays a fundamental role in growth regulation. We investigated the GH1 gene AluI and DdeI restriction enzyme polymorphisms, located 149 bp apart in the cattle genome, as possible markers of the production potential of Canchim crossbreed cattle, a 5/8 Charolais (Bos taurus) and 3/8 Nelore (Bos indicus) breed developed in Brazil, by evaluating the birth weight, weaning weight, yearling weight and plasma insulin-like growth factor-1 (IGF-1) concentration of 7 month to 10 months old Canchim calves (n = 204) of known genealogy and which had been genotyped for the AluI and DdeI markers. Our results showed significant effect (p < 0.05) between the homozygous DdeI+/DdeI+ polymorphism and the estimated breeding value for weaning weight (ESB-WW), while the AluI leucine homozygous (L/L) and leucine/valine (L/V) heterozygous polymorphisms showed no significant effect on the traits studied. The restriction sites of the two enzymes led to the formation of haplotypes which also exerted a significant effect (p < 0.05) on the ESB-WW, with the largest difference being 8.5 kg in favor of the homozygous L plus DdeI+/L plus DdeI+ genotype over the heterozygous L plus DdeI-/V plus DdeI+ genotype.

An improved three-dimensional model for growth of oxide films induced by laser heating

In this paper we consider a three-dimensional heat diffusion model to explain the growth of oxide films which takes place when a laser beam is shined on and heats a metallic layer deposited on a glass substrate in a normal atmospheric environment. In particular, we apply this model to the experimental results obtained for the dependence of the oxide layer thickness on the laser density power for growth of TiO2 films grown on Ti-covered glass slides. We show that there is a very good agreement between the experimental results and the theoretical predictions from our proposed three-dimensional model, improving the results obtained with the one-dimensional heat diffusion model previously reported. Our theoretical results also show the occurrence of surface cooling between consecutive laser pulses, and that the oxide track surface profile closely follows the spatial laser profile indicating that heat diffusive effects can be neglected in the growth of oxide films by laser heating. © 2001 Elsevier Science B.V.

One-dimensional analytical model for oxide thin film growth on Ti metal layers during laser heating in air

This paper presents the theoretical and experimental results for oxide thin film growth on titanium films previously deposited over glass substrate. Ti films of thickness 0.1 μm were heated by Nd:YAG laser pulses in air. The oxide tracks were created by moving the samples with a constant speed of 2 mm/s, under the laser action. The micro-topographic analysis of the tracks was performed by a microprofiler. The results taken along a straight line perpendicular to the track axis revealed a Gaussian profile that closely matches the laser's spatial mode profile, indicating the effectiveness of the surface temperature gradient on the film's growth process. The sample's micro-Raman spectra showed two strong bands at 447 and 612 cm -1 associated with the TiO 2 structure. This is a strong indication that thermo-oxidation reactions took place at the Ti film surface that reached an estimated temperature of 1160 K just due to the action of the first pulse. The results obtained from the numerical integration of the analytical equation which describes the oxidation rate (Wagner equation) are in agreement with the experimental data for film thickness in the high laser intensity region. This shows the partial accuracy of the one-dimensional model adopted for describing the film growth rate. © 2001 Elsevier Science B.V.