An account and analysis of the implementation of various ebook business models at QUT, Australia

QUT (Queensland University of Technology) is a leading university based in the city of Brisbane, Queensland, Australia and is a selectively research intensive university with 2,500 higher degree research students and an overall student population of 45,000 students. The transition from print to online resources is largely completed and the library now provides access to 450,000 print books, 1,000 print journals, 600,000 ebooks, 120,000 ejournals and 100,000 online videos. The ebook collection is now used three times as much as the print book collection. This paper focuses on QUT Library’s ebook strategy and the challenges of building and managing a rapidly growing collection of ebooks using a range of publishers, platforms, and business and financial models. The paper provides an account of QUT Library’s experiences in using Patron Driven Acquisition (PDA) using eBook Library (EBL); the strategic procurement of publisher and subject collections by lease and outright purchase models, the more recent transition to Evidence Based Selection (EBS) options provided by some publishers, and its piloting of etextbook models. The paper provides an in-depth analysis of each of these business models at QUT, focusing on access verses collection development, usage, cost per use, and value for money.

Predicting survival of western rock lobsters Panulirus cygnus using discriminant analysis of hemolymph parameters taken immediately following simulated handling treatments

Instances of morbidity amongst rock lobsters (Panulirus cygnus) arriving at factories in Western Australia (WA) have been attributed to stress during post-harvest handling. This study used discriminant analysis to determine whether physiological correlates of stress following a period of simulated post-harvest handling had any validity as predictors of future rejection or morbidity of western rock lobsters. Groups of 230 western rock lobsters were stored for 6 h in five environments (submerged/flowing sea water, submerged/re-circulating sea water, humid air, flowing sea water spray, and re-circulated sea water spray). The experiment was conducted in late spring (ambient sea water 22°C), and repeated again in early autumn (ambient sea water 26°C). After 6 h treatment, each lobster was graded for acceptability for live export, numbered, and its hemolymph was sampled. The samples were analysed for a number of physiological and health status parameters. The lobsters were then stored for a week in tanks in the live lobster factory to record mortality. The mortality of lobsters in the factory was associated with earlier deviations in hemolymph parameters as they emerged from the storage treatments. Discriminant analysis (DA) of the hemolymph assays enabled the fate of 80-90% of the lobsters to be correctly categorised within each experiment. However, functions derived from one experiment were less accurate at predicting mortality when applied to the other experiments. One of the reasons for this was the higher mortality and the more severe patho-physiological changes observed in lobsters stored in humid air or sprays at the higher temperature. The analysis identified lactate accumulation during emersion and associated physiological and hemocyte-related effects as a major correlate of mortality. Reducing these deviations, for example by submerged transport, is expected to ensure high levels of survival. None of the indicators tested predicted mortality with total accuracy. The simplest and most accurate means of comparing emersed treatments was to count the mortality afterwards.

Identification of dynamical systems with fractional derivative damping models using inverse sensitivity analysis

The problem of identifying parameters of time invariant linear dynamical systems with fractional derivative damping models, based on a spatially incomplete set of measured frequency response functions and experimentally determined eigensolutions, is considered. Methods based on inverse sensitivity analysis of damped eigensolutions and frequency response functions are developed. It is shown that the eigensensitivity method requires the development of derivatives of solutions of an asymmetric generalized eigenvalue problem. Both the first and second order inverse sensitivity analyses are considered. The study demonstrates the successful performance of the identification algorithms developed based on synthetic data on one, two and a 33 degrees of freedom vibrating systems with fractional dampers. Limited studies have also been conducted by combining finite element modeling with experimental data on accelerances measured in laboratory conditions on a system consisting of two steel beams rigidly joined together by a rubber hose. The method based on sensitivity of frequency response functions is shown to be more efficient than the eigensensitivity based method in identifying system parameters, especially for large scale systems.

Parameter estimation and sensitivity analysis of fat deposition models in beef steers using acslXtreme.

The Davis Growth Model (a dynamic steer growth model encompassing 4 fat deposition models) is currently being used by the phenotypic prediction program of the Cooperative Research Centre (CRC) for Beef Genetic Technologies to predict P8 fat (mm) in beef cattle to assist beef producers meet market specifications. The concepts of cellular hyperplasia and hypertrophy are integral components of the Davis Growth Model. The net synthesis of total body fat (kg) is calculated from the net energy available after accounting tor energy needs for maintenance and protein synthesis. Total body fat (kg) is then partitioned into 4 fat depots (intermuscular, intramuscular, subcutaneous, and visceral). This paper reports on the parameter estimation and sensitivity analysis of the DNA (deoxyribonucleic acid) logistic growth equations and the fat deposition first-order differential equations in the Davis Growth Model using acslXtreme (Hunstville, AL, USA, Xcellon). The DNA and fat deposition parameter coefficients were found to be important determinants of model function; the DNA parameter coefficients with days on feed >100 days and the fat deposition parameter coefficients for all days on feed. The generalized NL2SOL optimization algorithm had the fastest processing time and the minimum number of objective function evaluations when estimating the 4 fat deposition parameter coefficients with 2 observed values (initial and final fat). The subcutaneous fat parameter coefficient did indicate a metabolic difference for frame sizes. The results look promising and the prototype Davis Growth Model has the potential to assist the beef industry meet market specifications.

Novel conditional mouse models for targeted kidney research : Emphasis on the analysis of the biological function of nephrin

Nephrin is a transmembrane protein belonging to the immunoglobulin superfamily and is expressed primarily in the podocytes, which are highly differentiated epithelial cells needed for primary urine formation in the kidney. Mutations leading to nephrin loss abrogate podocyte morphology, and result in massive protein loss into urine and consequent early death in humans carrying specific mutations in this gene. The disease phenotype is closely replicated in respective mouse models. The purpose of this thesis was to generate novel inducible mouse-lines, which allow targeted gene deletion in a time and tissue-specific manner. A proof of principle model for succesful gene therapy for this disease was generated, which allowed podocyte specific transgene replacement to rescue gene deficient mice from perinatal lethality. Furthermore, the phenotypic consequences of nephrin restoration in the kidney and nephrin deficiency in the testis, brain and pancreas in rescued mice were investigated. A novel podocyte-specific construct was achieved by using standard cloning techniques to provide an inducible tool for in vitro and in vivo gene targeting. Using modified constructs and microinjection procedures two novel transgenic mouse-lines were generated. First, a mouse-line with doxycycline inducible expression of Cre recombinase that allows podocyte-specific gene deletion was generated. Second, a mouse-line with doxycycline inducible expression of rat nephrin, which allows podocyte-specific nephrin over-expression was made. Furthermore, it was possible to rescue nephrin deficient mice from perinatal lethality by cross-breeding them with a mouse-line with inducible rat nephrin expression that restored the missing endogenous nephrin only in the kidney after doxycycline treatment. The rescued mice were smaller, infertile, showed genital malformations and developed distinct histological abnormalities in the kidney with an altered molecular composition of the podocytes. Histological changes were also found in the testis, cerebellum and pancreas. The expression of another molecule with limited tissue expression, densin, was localized to the plasma membranes of Sertoli cells in the testis by immunofluorescence staining. Densin may be an essential adherens junction protein between Sertoli cells and developing germ cells and these junctions share similar protein assembly with kidney podocytes. This single, binary conditional construct serves as a cost- and time-efficient tool to increase the understanding of podocyte-specific key proteins in health and disease. The results verified a tightly controlled inducible podocyte-specific transgene expression in vitro and in vivo as expected. These novel mouse-lines with doxycycline inducible Cre recombinase and with rat nephrin expression will be useful for conditional gene targeting of essential podocyte proteins and to study in detail their functions in the adult mice. This is important for future diagnostic and pharmacologic development platforms.

Complete cytogenetic response and major molecular response as surrogate outcomes for overall survival in first-line treatment of chronic myelogenous leukemia: A case study for technology appraisal on the basis of surrogate outcomes evidence

Objectives In 2012, the National Institute for Health and Care Excellence assessed dasatinib, nilotinib, and standard-dose imatinib as first-line treatment of chronic phase chronic myelogenous leukemia (CML). Licensing of these alternative treatments was based on randomized controlled trials assessing complete cytogenetic response (CCyR) and major molecular response (MMR) at 12 months as primary end points. We use this case study to illustrate the validation of CCyR and MMR as surrogate outcomes for overall survival in CML and how this evidence was used to inform National Institute for Health and Care Excellence’s recommendation on the public funding of these first-line treatments for CML. Methods We undertook a systematic review and meta-analysis to quantify the association between CCyR and MMR at 12 months and overall survival in patients with chronic phase CML. We estimated life expectancy by extrapolating long-term survival from the weighted overall survival stratified according to the achievement of CCyR and MMR. Results Five studies provided data on the observational association between CCyR or MMR and overall survival. Based on the pooled association between CCyR and MMR and overall survival, our modeling showed comparable predicted mean duration of survival (21–23 years) following first-line treatment with imatinib, dasatinib, or nilotinib. Conclusions This case study illustrates the consideration of surrogate outcome evidence in health technology assessment. Although it is often recommended that the acceptance of surrogate outcomes be based on randomized controlled trial data demonstrating an association between the treatment effect on both the surrogate outcome and the final outcome, this case study shows that policymakers may be willing to accept a lower level of evidence (i.e., observational association).

Anti-TNF treatment in juvenile idiopathic arthritis and associated uveitis : Clinical perspectives on growth, uveitis, and drug survival

Juvenile idiopathic arthritis (JIA) is a heterogeneous group of childhood chronic arthritides, associated with chronic uveitis in 20% of cases. For JIA patients responding inadequately to conventional disease-modifying anti-rheumatic drugs (DMARDs), biologic therapies, anti-tumor necrosis factor (anti-TNF) agents are available. In this retrospective multicenter study, 258 JIA-patients refractory to DMARDs and receiving biologic agents during 1999-2007 were included. Prior to initiation of anti-TNFs, growth velocity of 71 patients was delayed in 75% and normal in 25%. Those with delayed growth demonstrated a significant increase in growth velocity after initiation of anti-TNFs. Increase in growth rate was unrelated to pubertal growth spurt. No change was observed in skeletal maturation before and after anti-TNFs. The strongest predictor of change in growth velocity was growth rate prior to anti-TNFs. Change in inflammatory activity remained a significant predictor even after decrease in glucocorticoids was taken into account. In JIA-associated uveitis, impact of two first-line biologic agents, etanercept and infliximab, and second-line or third-line anti-TNF agent, adalimumab, was evaluated. In 108 refractory JIA patients receiving etanercept or infliximab, uveitis occurred in 45 (42%). Uveitis improved in 14 (31%), no change was observed in 14 (31%), and in 17 (38%) uveitis worsened. Uveitis improved more frequently (p=0.047) and frequency of annual uveitis flares was lower (p=0.015) in those on infliximab than in those on etanercept. In 20 patients taking adalimumab, 19 (95%) had previously failed etanercept and/or infliximab. In 7 patients (35%) uveitis improved, in one (5%) worsened, and in 12 (60%) no change occurred. Those with improved uveitis were younger and had shorter disease duration. Serious adverse events (AEs) or side-effects were not observed. Adalimumab was effective also in arthritis. Long-term drug survival (i.e. continuation rate on drug) with etanercept (n=105) vs. infliximab (n=104) was at 24 months 68% vs. 68%, and at 48 months 61% vs. 48% (p=0.194 in log-rank analysis). First-line anti-TNF agent was discontinued either due to inefficacy (etanercept 28% vs. infliximab 20%, p=0.445), AEs (7% vs. 22%, p=0.002), or inactive disease (10% vs. 16%, p=0.068). Females, patients with systemic JIA (sJIA), and those taking infliximab as the first therapy were at higher risk for treatment discontinuation. One-third switched to the second anti-TNF agent, which was discontinued less often than the first. In conclusion, in refractory JIA anti-TNFs induced enhanced growth velocity. Four-year treatment survival was comparable between etanercept and infliximab, and switching from first-line to second-line agent a reasonable therapeutic option. During anti-TNF treatment, one-third with JIA-associated anterior uveitis improved.

Genetic analysis of structural brain connectivity using DICCCOL models of diffusion MRI in 522 twins

Genetic and environmental factors affect white matter connectivity in the normal brain, and they also influence diseases in which brain connectivity is altered. Little is known about genetic influences on brain connectivity, despite wide variations in the brain's neural pathways. Here we applied the 'DICCCOL' framework to analyze structural connectivity, in 261 twin pairs (522 participants, mean age: 21.8 y ± 2.7SD). We encoded connectivity patterns by projecting the white matter (WM) bundles of all 'DICCCOLs' as a tracemap (TM). Next we fitted an A/C/E structural equation model to estimate additive genetic (A), common environmental (C), and unique environmental/error (E) components of the observed variations in brain connectivity. We found 44 'heritable DICCCOLs' whose connectivity was genetically influenced (α2>1%); half of them showed significant heritability (α2>20%). Our analysis of genetic influences on WM structural connectivity suggests high heritability for some WM projection patterns, yielding new targets for genome-wide association studies.

Geant4 Hadronic Cascade Models and CMS Data Analysis : Computational Challenges in the LHC era

This work belongs to the field of computational high-energy physics (HEP). The key methods used in this thesis work to meet the challenges raised by the Large Hadron Collider (LHC) era experiments are object-orientation with software engineering, Monte Carlo simulation, the computer technology of clusters, and artificial neural networks. The first aspect discussed is the development of hadronic cascade models, used for the accurate simulation of medium-energy hadron-nucleus reactions, up to 10 GeV. These models are typically needed in hadronic calorimeter studies and in the estimation of radiation backgrounds. Various applications outside HEP include the medical field (such as hadron treatment simulations), space science (satellite shielding), and nuclear physics (spallation studies). Validation results are presented for several significant improvements released in Geant4 simulation tool, and the significance of the new models for computing in the Large Hadron Collider era is estimated. In particular, we estimate the ability of the Bertini cascade to simulate Compact Muon Solenoid (CMS) hadron calorimeter HCAL. LHC test beam activity has a tightly coupled cycle of simulation-to-data analysis. Typically, a Geant4 computer experiment is used to understand test beam measurements. Thus an another aspect of this thesis is a description of studies related to developing new CMS H2 test beam data analysis tools and performing data analysis on the basis of CMS Monte Carlo events. These events have been simulated in detail using Geant4 physics models, full CMS detector description, and event reconstruction. Using the ROOT data analysis framework we have developed an offline ANN-based approach to tag b-jets associated with heavy neutral Higgs particles, and we show that this kind of NN methodology can be successfully used to separate the Higgs signal from the background in the CMS experiment.

Afatinib versus cisplatin-based chemotherapy for EGFR mutation-positive lung adenocarcinoma (LUX-Lung 3 and LUX-Lung 6): analysis of overall survival data from two randomised, phase 3 trials

Background We aimed to assess the effect of afatinib on overall survival of patients with EGFR mutation-positive lung adenocarcinoma through an analysis of data from two open-label, randomised, phase 3 trials. Methods Previously untreated patients with EGFR mutation-positive stage IIIB or IV lung adenocarcinoma were enrolled in LUX-Lung 3 (n=345) and LUX-Lung 6 (n=364). These patients were randomly assigned in a 2:1 ratio to receive afatinib or chemotherapy (pemetrexed-cisplatin [LUX-Lung 3] or gemcitabine-cisplatin [LUX-Lung 6]), stratified by EGFR mutation (exon 19 deletion [del19], Leu858Arg, or other) and ethnic origin (LUX-Lung 3 only). We planned analyses of mature overall survival data in the intention-to-treat population after 209 (LUX-Lung 3) and 237 (LUX-Lung 6) deaths. These ongoing studies are registered with ClinicalTrials.gov, numbers NCT00949650 and NCT01121393. Findings Median follow-up in LUX-Lung 3 was 41 months (IQR 35–44); 213 (62%) of 345 patients had died. Median follow-up in LUX-Lung 6 was 33 months (IQR 31–37); 246 (68%) of 364 patients had died. In LUX-Lung 3, median overall survival was 28·2 months (95% CI 24·6–33·6) in the afatinib group and 28·2 months (20·7–33·2) in the pemetrexed-cisplatin group (HR 0·88, 95% CI 0·66–1·17, p=0·39). In LUX-Lung 6, median overall survival was 23·1 months (95% CI 20·4–27·3) in the afatinib group and 23·5 months (18·0–25·6) in the gemcitabine-cisplatin group (HR 0·93, 95% CI 0·72–1·22, p=0·61). However, in preplanned analyses, overall survival was significantly longer for patients with del19-positive tumours in the afatinib group than in the chemotherapy group in both trials: in LUX-Lung 3, median overall survival was 33·3 months (95% CI 26·8–41·5) in the afatinib group versus 21·1 months (16·3–30·7) in the chemotherapy group (HR 0·54, 95% CI 0·36–0·79, p=0·0015); in LUX-Lung 6, it was 31·4 months (95% CI 24·2–35·3) versus 18·4 months (14·6–25·6), respectively (HR 0·64, 95% CI 0·44–0·94, p=0·023). By contrast, there were no significant differences by treatment group for patients with EGFR Leu858Arg-positive tumours in either trial: in LUX-Lung 3, median overall survival was 27·6 months (19·8–41·7) in the afatinib group versus 40·3 months (24·3–not estimable) in the chemotherapy group (HR 1·30, 95% CI 0·80–2·11, p=0·29); in LUX-Lung 6, it was 19·6 months (95% CI 17·0–22·1) versus 24·3 months (19·0–27·0), respectively (HR 1·22, 95% CI 0·81–1·83, p=0·34). In both trials, the most common afatinib-related grade 3–4 adverse events were rash or acne (37 [16%] of 229 patients in LUX-Lung 3 and 35 [15%] of 239 patients in LUX-Lung 6), diarrhoea (33 [14%] and 13 [5%]), paronychia (26 [11%] in LUX-Lung 3 only), and stomatitis or mucositis (13 [5%] in LUX-Lung 6 only). In LUX-Lung 3, neutropenia (20 [18%] of 111 patients), fatigue (14 [13%]) and leucopenia (nine [8%]) were the most common chemotherapy-related grade 3–4 adverse events, while in LUX-Lung 6, the most common chemotherapy-related grade 3–4 adverse events were neutropenia (30 [27%] of 113 patients), vomiting (22 [19%]), and leucopenia (17 [15%]). Interpretation Although afatinib did not improve overall survival in the whole population of either trial, overall survival was improved with the drug for patients with del19 EGFR mutations. The absence of an effect in patients with Leu858Arg EGFR mutations suggests that EGFR del19-positive disease might be distinct from Leu858Arg-positive disease and that these subgroups should be analysed separately in future trials.

Construction and use of linear regression models for processor performance analysis

Processor architects have a challenging task of evaluating a large design space consisting of several interacting parameters and optimizations. In order to assist architects in making crucial design decisions, we build linear regression models that relate Processor performance to micro-architecture parameters, using simulation based experiments. We obtain good approximate models using an iterative process in which Akaike's information criteria is used to extract a good linear model from a small set of simulations, and limited further simulation is guided by the model using D-optimal experimental designs. The iterative process is repeated until desired error bounds are achieved. We used this procedure to establish the relationship of the CPI performance response to 26 key micro-architectural parameters using a detailed cycle-by-cycle superscalar processor simulator The resulting models provide a significance ordering on all micro-architectural parameters and their interactions, and explain the performance variations of micro-architectural techniques.

Reliability models for existing structures based on dynamic state estimation and data based asymptotic extreme value analysis

The problem of time variant reliability analysis of existing structures subjected to stationary random dynamic excitations is considered. The study assumes that samples of dynamic response of the structure, under the action of external excitations, have been measured at a set of sparse points on the structure. The utilization of these measurements m in updating reliability models, postulated prior to making any measurements, is considered. This is achieved by using dynamic state estimation methods which combine results from Markov process theory and Bayes' theorem. The uncertainties present in measurements as well as in the postulated model for the structural behaviour are accounted for. The samples of external excitations are taken to emanate from known stochastic models and allowance is made for ability (or lack of it) to measure the applied excitations. The future reliability of the structure is modeled using expected structural response conditioned on all the measurements made. This expected response is shown to have a time varying mean and a random component that can be treated as being weakly stationary. For linear systems, an approximate analytical solution for the problem of reliability model updating is obtained by combining theories of discrete Kalman filter and level crossing statistics. For the case of nonlinear systems, the problem is tackled by combining particle filtering strategies with data based extreme value analysis. In all these studies, the governing stochastic differential equations are discretized using the strong forms of Ito-Taylor's discretization schemes. The possibility of using conditional simulation strategies, when applied external actions are measured, is also considered. The proposed procedures are exemplifiedmby considering the reliability analysis of a few low-dimensional dynamical systems based on synthetically generated measurement data. The performance of the procedures developed is also assessed based on a limited amount of pertinent Monte Carlo simulations. (C) 2010 Elsevier Ltd. All rights reserved.

Transcriptional analysis of persistent Chlamydia pneumoniae infection in vitro

Chlamydia pneumoniae can cause acute respiratory infections including pneumonia. Repeated and persistent Chlamydia infections occur and persistent C. pneumoniae infection may have a role in the pathogenesis of atherosclerosis and coronary heart disease and may also contribute to the development of chronic inflammatory lung diseases like chronic obstructive pulmonary disease (COPD) and asthma. In this thesis in vitro models for persistent C. pneumonia infection were established in epithelial and monocyte/macrophage cell lines. Expression of host cell genes in the persistent C. pneumoniae infection model of epithelial cells was studied by microarray and RT-PCR. In the monocyte/macrophage infection model expression of selected C. pneumoniae genes were studied by RT-PCR and immunofluorescence microscopy. Chlamydia is able to modulate host cell gene expression and apoptosis of host cells, which may assist Chlamydia to evade the host cells' immune responses. This, in turn, may lead to extended survival of the organism inside epithelial cells and promote the development of persistent infection. To simulate persistent C. pneumoniae infection in vivo, we set up a persistent infection model exposing the HL cell cultures to IFN-gamma. When HL cell cultures were treated with moderate concentration of IFN-gamma, the replication of C. pneumoniae DNA was unaffected while differentiation into infectious elementary bodies (EB) was strongly inhibited. By transmission electron microscopy small atypical inclusions were identified in IFN-gamma treated cultures. No second cycle of infection was observed in cells exposed to IFN-gamma , whereas C. pneumoniae was able to undergo a second cycle of infection in unexposed HL cells. Although monocytic cells can naturally restrict chlamydial growth, IFN-gamma further reduced production of infectious C. pneumoniae in Mono Mac 6 cells. Under both studied conditions no second cycle of infection could be detected in monocytic cell line suggesting persistent infection in these cells. As a step toward understanding the role of host genes in the development and pathogenesis of persistent C. pneumoniae infection, modulation of host cell gene expression during IFN-gamma induced persistent infection was examined and compared to that seen during active C. pneumoniae infection or IFN-gamma treatment. Total RNA was collected at 6 to 150 h after infection of an epithelial cell line (HL) and analyzed by a cDNA array (available at that time) representing approximately 4000 human transcripts. In initial analysis 250 of the 4000 genes were identified as differentially expressed upon active and persistent chlamydial infection and IFN-gamma treatment. In persistent infection more potent up-regulation of many genes was observed in IFN-gamma induced persistent infection than in active infection or in IFN-gamma treated cell cultures. Also sustained up-regulation was observed for some genes. In addition, we could identify nine host cell genes whose transcription was specifically altered during the IFN-gamma induced persistent C. pneumoniae infection. Strongest up-regulation in persistent infection in relation to controls was identified for insulin like growth factor binding protein 6, interferon-stimulated protein 15 kDa, cyclin D1 and interleukin 7 receptor. These results suggest that during persistent infection, C. pneumoniae reprograms the host transcriptional machinery regulating a variety of cellular processes including adhesion, cell cycle regulation, growth and inflammatory response, all of which may play important roles in the pathogenesis of persistent C. pneumoniae infection. C. pneumoniae DNA can be detected in peripheral blood mononuclear cells indicating that the bacterium can also infect monocytic cells in vivo and thereby monocytes can assist the spread of infection from the lungs to other anatomical sites. Persistent infection established at these sites could promote inflammation and enhance pathology. Thus, the mononuclear cells are in a strategic position in the development of persistent infection. To investigate the intracellular replication and fate of C. pneumoniae in mononuclear cells we analyzed the transcription of 11 C. pneumoniae genes in Mono Mac 6 cells during infection by real time RT-PCR. Our results suggest that the transcriptional profile of the studied genes in monocytes is different from that seen in epithelial cells and that IFN-gamma has a less significant effect on C. pneumoniae transcription in monocytes. Furthermore, our study shows that type III secretion system (T3SS) related genes are transcribed and that Chlamydia possesses a functional T3SS during infection in monocytes. Since C. pneumoniae infection in monocytes has been implicated to have reduced antibiotic susceptibility, this creates opportunities for novel therapeutics targeting T3SS in the management of chlamydial infection in monocytes.

Modelling initial survival and growth of radiata pine in New Zealand.

A sensitive framework has been developed for modelling young radiata pine survival, its growth and its size class distribution, from time of planting to age 5 or 6 years. The data and analysis refer to the Central North Island region of New Zealand. The survival function is derived from a Weibull probability density function, to reflect diminishing mortality with the passage of time in young stands. An anamorphic family of trends was used, as very little between-tree competition can be expected in young stands. An exponential height function was found to fit best the lower portion of its sigmoid form. The most appropriate basal area/ha exponential function included an allometric adjustment which resulted in compatible mean height and basal area/ha models. Each of these equations successfully represented the effects of several establishment practices by making coefficients linear functions of site factors, management activities and their interactions. Height and diameter distribution modelling techniques that ensured compatibility with stand values were employed to represent the effects of management practices on crop variation. Model parameters for this research were estimated using data from site preparation experiments in the region and were tested with some independent data sets.

Toxicant distributions and impact models in environmental risk analysis of waste sites

Myrkyllisten aineiden jakaumat ja vaikutusmallit jätealueiden ympäristöriskien analyysissä.