In this project, the angles of miniature rose petals throughout the course of their bloom were measured with a digital protractor constructed using a function plotting software. The angle was then modeled as a function of time, and an analogy was drawn from the blooming of rose petals to the logistic growth of populations. The digital method of measurement and the logistic growth model were also applied to cyclamen and hyacinth petals.

Forest growth models are important to the forestry community because they provide means for predicting future yields and exploring different forest management practices. The purpose of this thesis is to develop an individual tree forest growth model applicable for the province of Nova Scotia. The Acadian forest of Nova Scotia is a prime example a mixed species forest which is best modelled with individual tree models. Individual tree models also permit modelling variable-density management regimes, which are important as the Province investigates new silviculture options. Rather than use the conventional regression techniques, our individual tree growth and yield model was developed using neural networks. The growth and yield model was comprised of three different neural networks: a network for each survivability, diameter increment and height increment. In general, the neural network modelling approach fit the provincial data reasonably well. In order to have a model applicable to each species in the Province, species was included as a model input; the models were able to distinguish between species and to perform nearly as well as species-specific models. It was also found that including site and stocking level indicators as model inputs improved the model. Furthermore, it was found that the GIS-based site quality index developed at UNB could be used as a site indicator rather than land capability. Finally, the trained neural networks were used to create a growth and yield model which would be limited to shorter prediction periods and a larger scale.

This simulation study examined the performance of the curve-of-factors growth model when serial correlation and growth processes were present in the first-level factor structure. As previous research has shown (Ferron, Dailey, & Yi, 2002; Kwok, West, & Green, 2007; Murphy & Pituch, 2009) estimates of the fixed effects and their standard errors were unbiased when serial correlation was present in the data but unmodeled. However, variance components were estimated poorly across the examined serial correlation conditions. Two new models were also examined: one curve-of-factors model was fitted with a first-order autoregressive serial correlation parameter, and a second curve-of-factors model was fitted with first-order autoregressive and moving average serial correlation parameters. The models were developed in an effort to measure growth and serial correlation processes within the same data set. Both models fitted with serial correlation parameters were able to accurately reproduce the serial correlation parameter and approximate the true growth trajectory. However, estimates of the variance components and the standard errors of the fixed effects were problematic. The two models also produced inadmissible solutions across all conditions. Of the three models, the curve-of-factors model had the best overall performance. / text

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Microalgae have been recognized as one of the most promising feedstocks for biofuel production. In the Regional Algal Feedstock Testbed (RAFT) project, scientists and engineers have been working on various topics including improving cultivation strategy, optimizing culture system, developing production models, controlling contamination, and so on. One of the objectives in this project is to improve an algae cultivation model for productivity prediction and techno-economic assessment. The model adopted in this project is the Huesemann Algae Biomass Growth (HABG) model which is based upon strain characteristics obtained from laboratory experiments. However, because the model assumed optimal growth conditions for microalgae, it over-predicted biomass growth significantly when its results were compared to outdoor raceway experimental data. For example, in an attempt to control contamination, culture salinity was raised to a high level. The high salinity may limit growth of contaminants, but it also causes stress on salinity sensitive strains of microalgae. Researchers also lowered nutrient fertilization rates in order to minimize fertilizer input and cost of production. However, this introduced nutrient stress and lowered the growth rate of microalgae. In the raceways used in the RAFT project, shade covered a large fraction of the culture surface when solar angle was low. All of these growth limiting factors were not included in the original model. In this study, salinity stress, nitrogen limitation and shading effect were incorporated into the model. Growth rate reduction due to salinity stress and nitrogen limitation were quantified through laboratory experiments. An innovative concept of nitrogen availability was introduced, which estimates the nitrogen stress factor without measuring intracellular nitrogen. The shading factor was calculated based on solar position during the day and raceway geometry. The modification greatly improved the model accuracy. In addition to HABG model improvements, this study also focused on nutrient application. Several experiments were performed in both indoor and outdoor systems to improve field cultivation practices. The nitrogen experiments provided not only the growth kinetics that improved the growth model, but also demonstrated that high lipid accumulation rate was triggered at different nitrogen stress intensities for different strains. Stress should be applied depending the saturation demand of the final lipid product. In order to quickly evaluate the nitrogen status in the culture, a nitrogen stress index using optical density was proposed. Experiments in RAFT experiments supported the feasibility of applying the method in outdoor cultivation. This study also investigated maximum biomass yields of nitrogen and phosphorus for producing S. obliquus biomass with indoor bench scale experiments. The results were tested in the outdoor raceways and demonstrated the potential of using fertilizer more efficiently in microalgae cultivation.

Basal area and dominant height growth and survival models incorporating general response to silvicultural treatments for loblolly pine stands were developed using data from various silvicultural experiments across Southern United States. Growth models for treated stands were developed by multiplying base-line growth models with modifier response functions/multipliers accounting for effects of thinning, fertilization, and control of competing vegetation. Chapman-Richards functions were used to model the base-line growth. Separate response functions to mid-rotation thinning and fertilization effects were developed. The thinning response function was based on duration and rate parameters and is sensitive to stand age at the time of thinning, time since thinning, and intensity of thinning. The fertilization response functions were based on Weibull distribution and the magnitude of responses varies with time since application of fertilizers, type of fertilizer elements applied, and rate of application. Response functions were integrated as a multiplier to base-line models. Response to early control of competing vegetation was incorporated into base-line models through multiplier factors. Multiplier factors were calculated based on growth difference between treated and untreated stands. A difference function, derived from differential equation with age, initial stand density, and site index served as the base-line survival model. The survival model was adjusted for thinning treatment by including an additional independent variable that represents thinning intensity. No adjustment was required for survival model in response to fertilization and competing vegetation control. All growth models were unbiased and had adequate performance in predicting basal area and dominant height following treatments. Models were developed to represent general growth trends in response to treatments. The response functions developed here can be viewed as general response functions. / Ph. D.

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The demand for STEM college graduates is increasing. However, recent studies show there are not enough STEM majors to fulfill this need. This deficiency can be partially attributed to a gender discrepancy in the number of female STEM graduates and to the high rate of attrition of STEM majors. As STEM attrition has been associated with students being unprepared for STEM coursework, it is important to understand how STEM graduates change in achievement levels from middle school through high school and to have accurate readiness indicators for first-year STEM coursework. This study aimed to address these issues by comparing the achievement growth of STEM majors to non-STEM majors by gender in Science, Math, and Reading from Grade 6 to Grade 11 through latent growth models (LGMs). Then STEM Readiness Benchmarks were established in Science and Math on the Iowas (IAs) for typical first-year STEM courses and validity evidence was provided for the benchmarks. Results from the LGM analyses indicated that STEM graduates start at higher achievement levels in Grade 6 and maintain higher achievement levels through Grade 11 in all subjects. In addition, gender differences were examined. The findings indicate that students with high achievement levels self-select as STEM majors, regardless of gender. In addition, they suggest that students who are not on-track for a STEM degree may need to begin remediation prior to high school. Results from the benchmark analyses indicate that STEM coursework is more demanding and that students need to be better prepared academically in science and math if planning to pursue a STEM degree. In addition, the STEM Readiness Benchmarks were more accurate in predicting success in STEM courses than if general college readiness benchmarks were utilized. Also, students who met the STEM Readiness Benchmarks were more likely to graduate with a STEM degree. This study provides valuable information on STEM readiness to students, educators, and college admissions officers. Findings from this study can be used to better understand the level of academic achievement necessary to be successful as a STEM major and to provide guidance for students considering STEM majors in college. If students are being encouraged to purse STEM majors, it is important they have accurate information regarding their chances of success in STEM coursework.

This thesis consists of three essays on macroeconomic aspects of climate change. Technological Trends and the Intertemporal Incentives For Fossil-Fuel Use analyzes how (the expectations about) the future developments of different kinds of technology affect the intertemporal incentives for fossil-fuel use. I find that improvements in the future state of technologies for alternative-energy generation, energy efficiency and total factor productivity all increase fossil-fuel use before the change takes place. The effect of changes in the efficiency of non-energy inputs is the reverse, while the effect of changes in fossil-fuel based energy technology is ambiguous. These conclusions are robust to a number of variations of the assumptions made. The Role of the Nature of Damages considers to what extent the choice of modeling climate impacts as affecting productivity, utility or the depreciation of capital affects the behavior of integrated assessment models. I carry out my analysis in two different ways. Firstly, under some simplifying assumptions, I derive a simple formula for the optimal tax on fossil-fuel use that adds up the three different types of climate effects. Secondly, I use a two-period model with exogenous climate to analyze how the allocation of fossil-fuel use over time is affected by the effects of climate change. I find that this is sensitive to the assumptions made. Indirect Effects of Climate Change investigates how direct effects of climate change in some countries have indirect effects on other countries going through changing world market prices of goods and financial instruments. When calculating the total effects of climate change, these indirect effects must also be taken into account. I first derive these indirect effects in a many-country model. Reaching agreements about reductions in the emissions of greenhouse gases is made difficult by the negative correlation there seems to be between emissions of greenhouse gases and the vulnerability to climate change. I argue, based on a stylized two country example, that trade in goods will tend to make the countries' interests more aligned while trade in financial instruments will tend to make the countries' interests less aligned.

Entrepreneur is the destructor of present mechanism, but entrepreneur also can be the value creator of company. If company can make good use of the energy of the entrepreneur, entrepreneur will create enormous value for the company. So how to manipulate the power of entrepreneur becomes an important issue. This article discusses this issue from a perspective of Corporate Venture Capital. According to the independent-unit characteristic of CVC, start-up can avoid rigid bureaucracy and culture. The whole value creation process is as follows: Through CVC, parent company supports entrepreneur to build up business, and parent company will receive strategic value when start-up succeeds. There are two kinds of strategic value; one is the purpose of investment plan, another one is the activation of Corporate Entrepreneurship. As we know, when the core element of investment plan is entrepreneur, the plan is basically different from other plans. The essence of the investment plan which is based on the power of entrepreneur is Corporate Entrepreneurship. The definition of CE in this article is the process in which company makes use of individual entrepreneurship under the common vision to do innovative activities to create strategic value for the organization. In other words, from CVC perspective, the managing model of CE is the new venture growth model. CVC can follow the new venture growth model to support entrepreneur to build up business, and the success of start-up can return strategic value to parent company and promote the Corporate Entrepreneurship of parent company. After the discussion of the ecosystem, culture and investment cases of IC design industry in Taiwan, we interview three professional in CVC area to get further details. Then we build the new venture growth model for company to make good use of the power of entrepreneurs.