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Significant Model (significant + model)
Selected AbstractsPOPULATION DIFFERENTIATION IN THE BEETLE TRIBOLIUM CASTANEUM.EVOLUTION, Issue 3 2007We used joint-scaling analyses in conjunction with rearing temperature variation to investigate the contributions of additive, non-additive, and environmental effects to genetic divergence and incipient speciation among 12 populations of the red flour beetle, Tribolium castaneum, with small levels of pairwise nuclear genetic divergence (0.033 < Nei's D < 0.125). For 15 population pairs we created a full spectrum of line crosses (two parental, two reciprocal F1's, four F2's, and eight backcrosses), reared them at multiple temperatures, and analyzed the numbers and developmental defects of offspring. We assayed a total of 219,388 offspring from 5147 families. Failed crosses occurred predominately in F2's, giving evidence of F2 breakdown within this species. In all cases where a significant model could be fit to the data on offspring number, we observed at least one type of digenic epistasis. We also found maternal and cytoplasmic effects to be common components of divergence among T. castaneum populations. In some cases, the most complex model tested (additive, dominance, epistatic, maternal, and cytoplasmic effects) did not provide a significant fit to the data, suggesting that linkage or higher order epistasis is involved in differentiation between some populations. For the limb deformity data, we observed significant genotype-by-environment interaction in most crosses and pure parent crosses tended to have fewer deformities than hybrid crosses. Complexity of genetic architecture was not correlated with either geographic distance or genetic distance. Our results support the view that genetic incompatibilities responsible for postzygotic isolation, an important component of speciation, may be a natural but serendipitous consequence of nonadditive genetic effects and structured populations. [source] Americans' Nanotechnology Risk Perception:JOURNAL OF INDUSTRIAL ECOLOGY, Issue 3 2008Assessing Opinion Change Summary Although proposed nanotechnology applications hold great promise, little is known about the potential associated risks. This lack of clarity on the level of risk associated with nanotechnology has forced people to make decisions about consumption with incomplete information. A national random digit dialing telephone survey (N= 1014) was conducted in the United States to assess knowledge of nanotechnology and perception of risk in August 2006. This investigation looks critically at individuals' responses to questions about the balance of risks and benefits of nanotechnology, both at the outset of the survey and after respondents were given a brief introduction to the potential benefits and risks of the technology. Models were created to characterzise respondents who said they did not know how nanotechnology's risks and benefits balanced in the "preinformation" condition but who, in the postinformation condition, had a different opinion. Respondents who were highly educated, members of the Republican Party, or male were more likely to switch from "don't know" in the preinformation condition to "benefits outweigh risks" in the postinformation condition, whereas respondents who were less educated, members of the Democratic Party, or female were more likely to switch from "don't know" in the preinformation condition to "risks outweigh benefits" in the postinformation condition. This is the first study to our knowledge to develop a significant model of nanotechnology risk perception change, specifically with regard to gender differences. The power of information provision to sway opinions is also supported, highlighting the importance of developing educational efforts targeting vulnerable populations. [source] A pilot study on the differences in wavefront aberrations between two ethnic groups of young generally myopic subjectsOPHTHALMIC AND PHYSIOLOGICAL OPTICS, Issue 6 2008Alejandro Cerviño Abstract A comparative population-based cross-sectional study design was used to examine the prevalence of wavefront patterns in two different ethnic groups, and the relationship of these patterns with ocular biometrics and gender. The Shin,Nippon SRW5000 open field autorefractor, the Wavefront Analysis Supported Customized Ablation (WASCA) wavefront analyser and the IOLMaster were used to determine wavefront aberrations, mean spherical equivalent (SE) refractive error and axial length (AL). Seventy-four eyes from 74 young healthy subjects (44 British Asians, 30 Caucasians; 36 men, 38 women; mean age 22.51 ± 3.89 years) with mean SE averaging ,1.90 ± 2.76 D (range ,10.88 to +2.19 D) were examined. Relationships between ethnicity, gender, AL and SE, against the wavefront high-order root mean square, and aberration components up to the fifth order, were assessed by using multiple regression and correlation analysis. AL on its own accounted for 4.7% of the variance in trefoil component (F1,72 = 4.602; p = 0.035), 13.7% of coma component (F1,72 = 12.536; p = 0.001), 6.1% of trefoil component (F1,72 = 5.705; p = 0.020) and 9.8% of coefficient (F1,72 = 8.908; p = 0.004). A significant model emerged (F2,71 = 6.164; p = 0.003) for ethnicity and axial length, accounting for 12.4% of variance in primary spherical aberration with ethnicity accounting for 8.4% of that variance. For Caucasian subjects, a significant correlation was found between axial length and (Pearson's correlation coefficient ,0.500; p = 0.005) and (Pearson's correlation coefficient ,0.423; p = 0.020). For British Asian subjects, AL was only correlated with coefficient (Pearson's correlation coefficient ,0.358; p = 0.017). Ethnicity is a factor to be considered in the variability of wavefront aberration, particularly spherical aberration. Relationship between AL and wavefront aberrations seems to vary between ethnicities. If higher order aberrations play a role in the emmetropization process, this may be different for different populations. [source] Determinants of environmental management systems standards implementation: evidence from Greek industryBUSINESS STRATEGY AND THE ENVIRONMENT, Issue 6 2002Assistant Professor George E. Halkos This paper employs logistic regression analysis to test a model that predicts the implementation or non-implementation of Environmental Management Systems Standards (EMSSs) by considering various factors as explanatory variables. The dependent variable is dichotomous: industrial firms either implementing or not implementing EMSSs. From past experience we identify 15 major variables contributing to implementation of EMSSs. A sample of 259 respondents (84 implementing and 175 not) is used to estimate the parameters of the logistic regression model employing maximum likelihood. The results show an overall significant model with four of the 15 variables significant. The significance of management perception of environmental issues on their decision to implement EMSS was confirmed with regards to their perception on win,win possibilities. Pressure on companies to improve their environmental performance does not result in higher uptake of the standards. Company image and size are important factors in its decision to implement EMSS. Copyright © 2002 John Wiley & Sons, Ltd. and ERP Environment [source] Cybernetic Model Predictive Control of a Continuous Bioreactor with Cell RecycleBIOTECHNOLOGY PROGRESS, Issue 5 2003Kapil G. Gadkar The control of poly-,-hydroxybutyrate (PHB) productivity in a continuous bioreactor with cell recycle is studied by simulation. A cybernetic model of PHB synthesis in Alcaligenes eutrophus is developed. Model parameters are identified using experimental data, and simulation results are presented. The model is interfaced to a multirate model predictive control (MPC) algorithm. PHB productivity and concentration are controlled by manipulating dilution rate and recycle ratio. Unmeasured time varying disturbances are imposed to study regulatory control performance, including unreachable setpoints. With proper controller tuning, the nonlinear MPC algorithm can track productivity and concentration setpoints despite a change in the sign of PHB productivity gain with respect to dilution rate. It is shown that the nonlinear MPC algorithm is able to track the maximum achievable productivity for unreachable setpoints under significant process/model mismatch. The impact of model uncertainty upon controller performance is explored. The multirate MPC algorithm is tested using three controllers employing models that vary in complexity of regulation. It is shown that controller performance deteriorates as a function of decreasing biological complexity. [source] | ||||||||||