Assessment of functional forms of crop yield loss models of invasive plant species applied in decision support tools and bioeconomic modelling

AbstractObjectives Decision support tools (DSTs) for invasive species management have had limited success in producing convincing results and meeting users' expectations. The problems could be linked to the functional form of model which represents the dynamic relationship between the invasive species and crop yield loss in the DSTs. The objectives of this study were: a) to compile and review the models tested on field experiments and applied to DSTs; and b) to do an empirical evaluation of some popular models and alternatives. Design and methods This study surveyed the literature and documented strengths and weaknesses of the functional forms of yield loss models. Some widely used models (linear, relative yield and hyperbolic models) and two potentially useful models (the double-scaled and density-scaled models) were evaluated for a wide range of weed densities, maximum potential yield loss and maximum yield loss per weed. Results Popular functional forms include hyperbolic, sigmoid, linear, quadratic and inverse models. Many basic models were modified to account for the effect of important factors (weather, tillage and growth stage of crop at weed emergence) influencing weed–crop interaction and to improve prediction accuracy. This limited their applicability for use in DSTs as they became less generalized in nature and often were applicable to a much narrower range of conditions than would be encountered in the use of DSTs. These factors' effects could be better accounted by using other techniques. Among the model empirically assessed, the linear model is a very simple model which appears to work well at sparse weed densities, but it produces unrealistic behaviour at high densities. The relative-yield model exhibits expected behaviour at high densities and high levels of maximum yield loss per weed but probably underestimates yield loss at low to intermediate densities. The hyperbolic model demonstrated reasonable behaviour at lower weed densities, but produced biologically unreasonable behaviour at low rates of loss per weed and high yield loss at the maximum weed density. The density-scaled model is not sensitive to the yield loss at maximum weed density in terms of the number of weeds that will produce a certain proportion of that maximum yield loss. The double-scaled model appeared to produce more robust estimates of the impact of weeds under a wide range of conditions. Conclusions Previously tested functional forms exhibit problems for use in DSTs for crop yield loss modelling. Of the models evaluated, the double-scaled model exhibits desirable qualitative behaviour under most circumstances.

Functional Forms and Educational Production Functions

Different Functional Forms Are Proposed and Applied in the Context of Educational Production Functions. Three Different Specifications - the Linerar, Logit and Inverse Power Transformation (Ipt) - Are Used to Explain First Grade Students' Results to a Mathematics Achievement Test. with Ipt Identified As the Best Functional Form to Explain the Data, the Assumption of Differential Impact of Explanatory Variables on Achievement Following the Status of the Student As a Low Or High Achiever Is Retained. Policy Implications of Such Result in Terms of School Interventions Are Discussed in the Paper.

Fatigue Laws Via Functional Equations

In routine industrial design, fatigue life estimation is largely based on S-N curves and ad hoc cycle counting algorithms used with Miner's rule for predicting life under complex loading. However, there are well known deficiencies of the conventional approach. Of the many cumulative damage rules that have been proposed, Manson's Double Linear Damage Rule (DLDR) has been the most successful. Here we follow up, through comparisons with experimental data from many sources, on a new approach to empirical fatigue life estimation (A Constructive Empirical Theory for Metal Fatigue Under Block Cyclic Loading', Proceedings of the Royal Society A, in press). The basic modeling approach is first described: it depends on enforcing mathematical consistency between predictions of simple empirical models that include indeterminate functional forms, and published fatigue data from handbooks. This consistency is enforced through setting up and (with luck) solving a functional equation with three independent variables and six unknown functions. The model, after eliminating or identifying various parameters, retains three fitted parameters; for the experimental data available, one of these may be set to zero. On comparison against data from several different sources, with two fitted parameters, we find that our model works about as well as the DLDR and much better than Miner's rule. We finally discuss some ways in which the model might be used, beyond the scope of the DLDR.

Dendritic atrophy constricts functional maps in resonance and impedance properties of hippocampal model neurons

A gradient in the density of hyperpolarization-activated cyclic-nucleotide gated (HCN) channels is necessary for the emergence of several functional maps within hippocampal pyramidal neurons. Here, we systematically analyzed the impact of dendritic atrophy on nine such functional maps, related to input resistance and local/transfer impedance properties, using conductance-based models of hippocampal pyramidal neurons. We introduced progressive dendritic atrophy in a CA1 pyramidal neuron reconstruction through a pruning algorithm, measured all functional maps in each pruned reconstruction, and arrived at functional forms for the dependence of underlying measurements on dendritic length. We found that, across frequencies, atrophied neurons responded with higher efficiency to incoming inputs, and the transfer of signals across the dendritic tree was more effective in an atrophied reconstruction. Importantly, despite the presence of identical HCN-channel density gradients, spatial gradients in input resistance, local/transfer resonance frequencies and impedance profiles were significantly constricted in reconstructions with dendrite atrophy, where these physiological measurements across dendritic locations converged to similar values. These results revealed that, in atrophied dendritic structures, the presence of an ion channel density gradient alone was insufficient to sustain homologous functional maps along the same neuronal topograph. We assessed the biophysical basis for these conclusions and found that this atrophy-induced constriction of functional maps was mediated by an enhanced spatial spread of the influence of an HCN-channel cluster in atrophied trees. These results demonstrated that the influence fields of ion channel conductances need to be localized for channel gradients to express themselves as homologous functional maps, suggesting that ion channel gradients are necessary but not sufficient for the emergence of functional maps within single neurons.

STABILITY AND FOLDING OF MUTANT FORMS OF ISO-1 CYTOCHROME-C FROM SACCHAROMYCES CEREVISIAE

Partially functional forms of iso-1-cytochrome c from Saccharomyces cerevisiae were obtained by replacements of the evolutionarily conserved proline 71 with valine, isoleucine and threonine (Ernst et.al.,1985). Pro-71 lies at the juncture of two short helical regions and is believed to be important for proper local polypeptide chain folding within the iso-1-cytochrome c structure.^ To study folding in the absence of intermolecular disulfide dimer formation the free sulfhydryl group of Cys-102 was modified in both wild type and mutant proteins with an alkylating reagent, methyl methanethiosulfonate. Spectral analysis of the wild type and mutant proteins shows that the native-like functional (or partially functional) folded structure of cytochrome c is retained in the chemically modified derivatives. The replacement of Pro-71 with valine, isoleucine or threonine reduces the intensity of the 696 nm absorbance band which is an indicator of the Met-80 ligation to the heme. Thermal stability and guanidine hydrochloride unfolding studies of the mutant proteins shows a destabilization of the protein as a result of mutation. The degree of destabilization depends on the chemical nature of the substituent amino acid in the mutant protiens.^ Kinetics of folding/unfolding reactions of the proteins were monitored by fluorescence changes using stopped flow mixing to obtain guanidine hydrochloride concentration jumps ending below, within, and above the transition zone. The replacement of Pro-71 alters the rate on one of the fastest phases, $\tau\sb3$, while the two other phases, $\tau\sb1$ & $\tau\sb2$, remain the same.^ Slow refolding kinetic studies indicate that replacement of Pro-71 does not completely eliminate the absorbance or fluorescence detected slow phases leading to the conclusion that Pro-71 is not involved in the generation of the slow phases in the folding kinetics of iso-1-cytochrome c.^ The alkaline conformational change involving the disappearance of the 696 nm absorbance band occurs with increasing pH in the alkaline pH region (Davis et al., 1974). The apparent pK of this conformational change in mutant proteins is shifted as much as two pH units compared to wild type. The equilibrium and kinetic data of alkaline transition for the wild type follows a simple mechanism proposed by Davis et al., (1974) for horse heart cytochrome c. A more complex mechanism is proposed for the behavior of the mutant proteins. ^

Bayesian models for longitudinal data

Longitudinal data, where data are repeatedly observed or measured on a temporal basis of time or age provides the foundation of the analysis of processes which evolve over time, and these can be referred to as growth or trajectory models. One of the traditional ways of looking at growth models is to employ either linear or polynomial functional forms to model trajectory shape, and account for variation around an overall mean trend with the inclusion of random eects or individual variation on the functional shape parameters. The identification of distinct subgroups or sub-classes (latent classes) within these trajectory models which are not based on some pre-existing individual classification provides an important methodology with substantive implications. The identification of subgroups or classes has a wide application in the medical arena where responder/non-responder identification based on distinctly diering trajectories delivers further information for clinical processes. This thesis develops Bayesian statistical models and techniques for the identification of subgroups in the analysis of longitudinal data where the number of time intervals is limited. These models are then applied to a single case study which investigates the neuropsychological cognition for early stage breast cancer patients undergoing adjuvant chemotherapy treatment from the Cognition in Breast Cancer Study undertaken by the Wesley Research Institute of Brisbane, Queensland. Alternative formulations to the linear or polynomial approach are taken which use piecewise linear models with a single turning point, change-point or knot at a known time point and latent basis models for the non-linear trajectories found for the verbal memory domain of cognitive function before and after chemotherapy treatment. Hierarchical Bayesian random eects models are used as a starting point for the latent class modelling process and are extended with the incorporation of covariates in the trajectory profiles and as predictors of class membership. The Bayesian latent basis models enable the degree of recovery post-chemotherapy to be estimated for short and long-term followup occasions, and the distinct class trajectories assist in the identification of breast cancer patients who maybe at risk of long-term verbal memory impairment.

Validation of FHWA crash models for rural intersections - Lessons learned

A national-level safety analysis tool is needed to complement existing analytical tools for assessment of the safety impacts of roadway design alternatives. FHWA has sponsored the development of the Interactive Highway Safety Design Model (IHSDM), which is roadway design and redesign software that estimates the safety effects of alternative designs. Considering the importance of IHSDM in shaping the future of safety-related transportation investment decisions, FHWA justifiably sponsored research with the sole intent of independently validating some of the statistical models and algorithms in IHSDM. Statistical model validation aims to accomplish many important tasks, including (a) assessment of the logical defensibility of proposed models, (b) assessment of the transferability of models over future time periods and across different geographic locations, and (c) identification of areas in which future model improvements should be made. These three activities are reported for five proposed types of rural intersection crash prediction models. The internal validation of the model revealed that the crash models potentially suffer from omitted variables that affect safety, site selection and countermeasure selection bias, poorly measured and surrogate variables, and misspecification of model functional forms. The external validation indicated the inability of models to perform on par with model estimation performance. Recommendations for improving the state of the practice from this research include the systematic conduct of carefully designed before-and-after studies, improvements in data standardization and collection practices, and the development of analytical methods to combine the results of before-and-after studies with cross-sectional studies in a meaningful and useful way.

Growth of confined cancer spheroids : a combined experimental marker, critical modelling approach

A critical step in the dissemination of ovarian cancer is the formation of multicellular spheroids from cells shed from the primary tumour. The objectives of this study were to apply bioengineered three-dimensional (3D) microenvironments for culturing ovarian cancer spheroids in vitro and simultaneously to build on a mathematical model describing the growth of multicellular spheroids in these biomimetic matrices. Cancer cells derived from human epithelial ovarian carcinoma were embedded within biomimetic hydrogels of varying stiffness and grown for up to 4 weeks. Immunohistochemistry, imaging and growth analyses were used to quantify the dependence of cell proliferation and apoptosis on matrix stiffness, long-term culture and treatment with the anti-cancer drug paclitaxel. The mathematical model was formulated as a free boundary problem in which each spheroid was treated as an incompressible porous medium. The functional forms used to describe the rates of cell proliferation and apoptosis were motivated by the experimental work and predictions of the mathematical model compared with the experimental output. This work aimed to establish whether it is possible to simulate solid tumour growth on the basis of data on spheroid size, cell proliferation and cell death within these spheroids. The mathematical model predictions were in agreement with the experimental data set and simulated how the growth of cancer spheroids was influenced by mechanical and biochemical stimuli including matrix stiffness, culture duration and administration of a chemotherapeutic drug. Our computational model provides new perspectives on experimental results and has informed the design of new 3D studies of chemoresistance of multicellular cancer spheroids.

Does energy substitution affect carbon dioxide emissions : income relationship?

Considerable discussion has taken place during the last decade regarding the role of economic growth in determining environmental quality. Using data from 30 OECD countries for the period 1960-2003 and the nonparametric method of generalized additive models, which enables us to use flexible functional forms, this paper examines the environmental Kuznets curve hypothesis for carbon dioxide (CO2). We find that the reduction of coal share in energy use has a significant effect on CO2. Our results imply that economic growth is not sufficient to decrease CO2 emissions.

Decomposition of the environmental Kuznets curve : scale, technique, and composition effects

This study decomposed the determinants of environmental quality into scale, technique, and composition effects. We applied a semiparametric method of generalized additive models, which enabled us to use flexible functional forms and include several independent variables in the model. The differences in the technique effect were found to play a crucial role in reducing pollution. We found that the technique effect was sufficient to reduce sulfur dioxide emissions. On the other hand, its effect was not enough to reduce carbon dioxide (CO2) emissions and energy use, except for the case of CO2 emissions in high-income countries.

Maidontuottajatila ja ravinnepolitiikka: Tilan toimintamekanismit, politiikan tarve ja ohjauskeinojen vaikuttavuus

Tutkielman tarkoituksena on rakentaa malli, jolla voidaan arvioida maitotilan toimintaa monipuolisesti ravinnehuuhtouman kannalta. Tavoitteena on ennen muuta analyyttinen tarkastelu siten, että kuitenkin huomioiden maidontuotannon ominaispiirteet, keskeisinä esimerkkeinä ravinnon, maidontuotannon ja lannan ominaisuuksien väliset riippuvuudet. Analyysissa tarkastellaan tilanomistajan yksityisen hyödynmaksimoinnin ja yhteiskunnan tavoitteiden eroavaisuutta. Lisäksi johdetaan optimaaliset ohjauskeinot ja arvioidaan eräiden yksinkertaisten ohjauskeinojen vaikuttavuutta. Mallin analysoinnin perusteella yksityinen ja yhteiskunnallinen optimiratkaisu eroavat toisistaan kaikkien päätösmuuttujien osalta. Ei voida kuitenkaan yleispätevästi sanoa muutosten merkittävyyttä tai suuntaa ottamatta kantaa mallin funktiomuotoihin ja parametriarvoihin. Optimaaliset ohjauskeinot tulisi asettaa keinolannoitteen ja lannan levitykselle, väkirehuruokinnalle ja säilörehun viljelylle, mutta ei eläinten määrälle. Toisaalta optimaaliset ohjauskeinot ovat hyvin monimutkaisia. Tarkasteltujen yksinkertaisempien ohjauskeinojen vaikuttavuutta ei voida tarkasti arvioida analyyttisella tasolla. Numeeristen tulosten perusteella yhteiskunnallisessa optimissa eläinmäärä olisi hieman yksityistä optimia pienempi, väkirehun käyttö vähäisempää, enemmän peltoa allokoitaisiin säilörehun viljelyyn ja lannoitustasot olisivat kautta linjan hieman pienemmät. Lannanlevitykset eroavat etäisyyden suhteen: molemmissa tapauksissa lannanlevityksen intensiteetti kasvaa kohti tilan keskusta kuljettaessa, mutta yksityisessä optimissa lähimmälle pellolle dumpataan kaikki ylimääräinen lanta, kun taas yhteiskunnallisessa optimissa lanta levitetään tasaisemmin eri pelloille. Ero kokonaishyvinvoinnissa jää pieneksi, mutta eläinmäärän kasvu kärjistäisi lannan dumppauksen aiheuttamia huuhtoumahaittoja. Yksinkertaisista ohjauskeinoista lannoitusrajoitus sekä ravinne- ja keinolannoitevero osoittautuivat kohtalaisen käyttökelpoisiksi numeeristen tulosten perusteella. Sen sijaan eläinmäärän rajoittaminen ja lannan kuljetuskustannuksia kompensoivat tuet vaikuttavat tulosten perusteella huonoilta ratkaisuilta.

Local Structural and Environmental Factors Define the Efficiency of an RNA Pseudoknot Involved in Programmed Ribosomal Frameshift Process

In programmed -1 ribosomal frameshift, an RNA pseudoknot stalls the ribosome at specific sequence and restarts translation in a new reading frame. A precise understanding of structural characteristics of these pseudoknots and their PRF inducing ability has not been clear to date. To investigate this phenomenon, we have studied various structural aspects of a -1 PRF inducing RNA pseudoknot from BWYV using extensive molecular dynamics simulations. A set of functional and poorly functional forms, for which previous mutational data were available, were chosen for analysis. These structures differ from each other by either single base substitutions or base-pair replacements from the native structure. We have rationalized how certain mutations in RNA pseudoknot affect its function; e.g., a specific base substitution in loop 2 stabilizes the junction geometry by forming multiple noncanonical hydrogen bonds, leading to a highly rigid structure that could effectively resist ribosome-induced unfolding, thereby increasing efficiency. While, a CG to AU pair substitution in stem 1 leads to loss of noncanonical hydrogen bonds between stems and loop, resulting in a less stable structure and reduced PRF inducing ability, inversion of a pair in stem 2 alters specific base-pair geometry that might be required in ribosomal recognition of nucleobase groups, negatively affecting pseudoknot functioning. These observations illustrate that the ability of an RNA pseudoknot to induce -1 PRF with an optimal rate depends on several independent factors that contribute to either the local conformational variability or geometry

Essays on economics networks

This thesis belongs to the growing field of economic networks. In particular, we develop three essays in which we study the problem of bargaining, discrete choice representation, and pricing in the context of networked markets. Despite analyzing very different problems, the three essays share the common feature of making use of a network representation to describe the market of interest.

In Chapter 1 we present an analysis of bargaining in networked markets. We make two contributions. First, we characterize market equilibria in a bargaining model, and find that players' equilibrium payoffs coincide with their degree of centrality in the network, as measured by Bonacich's centrality measure. This characterization allows us to map, in a simple way, network structures into market equilibrium outcomes, so that payoffs dispersion in networked markets is driven by players' network positions. Second, we show that the market equilibrium for our model converges to the so called eigenvector centrality measure. We show that the economic condition for reaching convergence is that the players' discount factor goes to one. In particular, we show how the discount factor, the matching technology, and the network structure interact in a very particular way in order to see the eigenvector centrality as the limiting case of our market equilibrium.

We point out that the eigenvector approach is a way of finding the most central or relevant players in terms of the “global” structure of the network, and to pay less attention to patterns that are more “local”. Mathematically, the eigenvector centrality captures the relevance of players in the bargaining process, using the eigenvector associated to the largest eigenvalue of the adjacency matrix of a given network. Thus our result may be viewed as an economic justification of the eigenvector approach in the context of bargaining in networked markets.

As an application, we analyze the special case of seller-buyer networks, showing how our framework may be useful for analyzing price dispersion as a function of sellers and buyers' network positions.

Finally, in Chapter 3 we study the problem of price competition and free entry in networked markets subject to congestion effects. In many environments, such as communication networks in which network flows are allocated, or transportation networks in which traffic is directed through the underlying road architecture, congestion plays an important role. In particular, we consider a network with multiple origins and a common destination node, where each link is owned by a firm that sets prices in order to maximize profits, whereas users want to minimize the total cost they face, which is given by the congestion cost plus the prices set by firms. In this environment, we introduce the notion of Markovian traffic equilibrium to establish the existence and uniqueness of a pure strategy price equilibrium, without assuming that the demand functions are concave nor imposing particular functional forms for the latency functions. We derive explicit conditions to guarantee existence and uniqueness of equilibria. Given this existence and uniqueness result, we apply our framework to study entry decisions and welfare, and establish that in congested markets with free entry, the number of firms exceeds the social optimum.

Literature Review of Integrated Impact Assessment Models of Climate Change with Emphasis on Damage Functions

35 p.