There is a growing need for accurate distribution data for both common and rare plant species for conservation planning and ecological research purposes. A database of more than 500 observations for nine tree species with different ecological and geographical distributions and a range of frequencies of occurrence in south-eastern New South Wales (Australia) was used to compare the predictive performance of logistic regression models, generalised additive models (GAMs) and classification tree models (CTMs) using different data restriction regimes and several model-building strategies. Environmental variables (mean annual rainfall, mean summer rainfall, mean winter rainfall, mean annual temperature, mean maximum summer temperature, mean minimum winter temperature, mean daily radiation, mean daily summer radiation, mean daily June radiation, lithology and topography) were used to model the distribution of each of the plant species in the study area. Model predictive performance was measured as the area under the curve of a receiver operating characteristic (ROC) plot. The initial predictive performance of logistic regression models and generalised additive models (GAMs) using unrestricted, temperature restricted, major gradient restricted and climatic domain restricted data gave results that were contrary to current practice in species distribution modelling. Although climatic domain restriction has been used in other studies, it was found to produce models that had the lowest predictive performance. The performance of domain restricted models was significantly (p = 0.007) inferior to the performance of major gradient restricted models when the predictions of the models were confined to the climatic domain of the species. Furthermore, the effect of data restriction on model predictive performance was found to depend on the species as shown by a significant interaction between species and data restriction treatment (p = 0.013). As found in other studies however, the predictive performance of GAM was significantly (p = 0.003) better than that of logistic regression. The superiority of GAM over logistic regression was unaffected by different data restriction regimes and was not significantly different within species. The logistic regression models used in the initial performance comparisons were based on models developed using the forward selection procedure in a rigorous-fitting model-building framework that was designed to produce parsimonious models. The rigorous-fitting modelbuilding framework involved testing for the significant reduction in model deviance (p = 0.05) and significance of the parameter estimates (p = 0.05). The size of the parameter estimates and their standard errors were inspected because large estimates and/or standard errors are an indication of model degradation from overfilling or effecls such as mullicollinearily. For additional variables to be included in a model, they had to contribule significantly (p = 0.025) to the model prediclive performance. An attempt to improve the performance of species distribution models using logistic regression models in a rigorousfitting model-building framework, the backward elimination procedure was employed for model selection, bul it yielded models with reduced performance. A liberal-filling model-building framework that used significant model deviance reduction at p = 0.05 (low significance models) and 0.00001 (high significance models) levels as the major criterion for variable selection was employed for the development of logistic regression models using the forward selection and backward elimination procedures. Liberal filling yielded models that had a significantly greater predictive performance than the rigorous-fitting logistic regression models (p = 0.0006). The predictive performance of the former models was comparable to that of GAM and classification tree models (CTMs). The low significance liberal-filling models had a much larger number of variables than the high significance liberal-fitting models, but with no significant increase in predictive performance. To develop liberal-filling CTMs, the tree shrinking program in S-PLUS was used to produce a number of trees of differenl sizes (subtrees) by optimally reducing the size of a full CTM for a given species. The 10-fold cross-validated model deviance for the subtrees was plotted against the size of the subtree as a means of selecting an appropriate tree size. In contrast to liberal-fitting logistic regression, liberal-fitting CTMs had poor predictive performance. Species geographical range and species prevalence within the study area were used to categorise the tree species into different distributional forms. These were then used, to compare the effect of plant species rarity on the predictive performance of logistic regression models, GAMs and CTMs. The distributional forms included restricted and rare (RR) species (Eucalyptus paliformis and Eucalyptus kybeanensis), restricted and common (RC) species (Eucalyptus delegatensis, Eucryphia moorei and Eucalyptus fraxinoides), widespread and rare (WR) species (Eucalyptus data) and widespread and common (WC) species (Eucalyptus sieberi, Eucalyptus pauciflora and Eucalyptus fastigata). There were significant differences (p = 0.076) in predictive performance among the distributional forms for the logistic regression and GAM. The predictive performance for the WR distributional form was significantly lower than the performance for the other plant species distributional forms. The predictive performance for the RC and RR distributional forms was significantly greater than the performance for the WC distributional form. The trend in model predictive performance among plant species distributional forms was similar for CTMs except that the CTMs had poor predictive performance for the RR distributional form. This study shows the importance of data restriction to model predictive performance with major gradient data restriction being recommended for consistently high performance. Given the appropriate model selection strategy, logistic regression, GAM and CTM have similar predictive performance. Logistic regression requires a high significance liberal-fitting strategy to both maximise its predictive performance and to select a relatively small model that could be useful for framing future ecological hypotheses about the distribution of individual plant species. The results for the modelling of plant species for conservation purposes were encouraging since logistic regression and GAM performed well for the restricted and rare species, which are usually of greater conservation concern.

<p>Electrospray ionization (ESI) mass spectrometry (MS) in combination with liquid chromatography (LC) is an excellent tool for the identification of drug metabolites. Utilizing this hyphenated technique in combination with proper sample pretreatment, the metabolic pathways of the analgesic drug ketobemidone were investigated in human urine and rat microdialysate from blood and brain. Two novel phase I metabolites (ketobemidone N-oxide and meta-hydroxymethoxyketobemidone) and three novel phase II metabolites (glucuronic acid conjugates of ketobemidone, norketobemidone and hydroxymethoxyketobemidone) were identified in human urine. Further, norketobemidone and ketobemidone N-oxide were identified in rat microdialysate from brain after regional distribution of ketobemidone in striatum. This indicates that the brain itself has the possibility to metabolize ketobemidone. </p><p>Synthetic ketobemidone metabolites were used for comparison of retention times and tandem MS spectra with the possible metabolites recovered from the biological samples. The conjugated metabolites were identified by accurate mass measurements and tandem MS spectra of the aglycones. The accuracy of the estimated masses was better than 2.1 ppm for two out of three conjugates in presence of internal standard.</p><p>On-line micro-SPE was successfully used for trapping and desalting of the microdialysates. The small SPE pre-column made it possible to inject approximately 100 times more sample on the analytical column compared to injection without pre-column. Selective trapping was demonstrated for the polar catechol amine metabolite, dihydroxyketobemidone, which forms covalent complexes with phenylboronic acid (PBA). A fluorinated silica type stationary phase was the only column out of several tested that was able to separate ketobemidone and all relevant phase I metabolites. </p><p>Liquid chromatography and mass spectrometry are independently valuable tools in the field of analytical pharmaceutical chemistry. The present study showed that the combination of LC-MS, with its excellent selectivity and sensitivity, offers an outstanding tool in the qualitative analysis of drugs and metabolites in biological fluids. </p>

Electrospray ionization (ESI) mass spectrometry (MS) in combination with liquid chromatography (LC) is an excellent tool for the identification of drug metabolites. Utilizing this hyphenated technique in combination with proper sample pretreatment, the metabolic pathways of the analgesic drug ketobemidone were investigated in human urine and rat microdialysate from blood and brain. Two novel phase I metabolites (ketobemidone N-oxide and meta-hydroxymethoxyketobemidone) and three novel phase II metabolites (glucuronic acid conjugates of ketobemidone, norketobemidone and hydroxymethoxyketobemidone) were identified in human urine. Further, norketobemidone and ketobemidone N-oxide were identified in rat microdialysate from brain after regional distribution of ketobemidone in striatum. This indicates that the brain itself has the possibility to metabolize ketobemidone. Synthetic ketobemidone metabolites were used for comparison of retention times and tandem MS spectra with the possible metabolites recovered from the biological samples. The conjugated metabolites were identified by accurate mass measurements and tandem MS spectra of the aglycones. The accuracy of the estimated masses was better than 2.1 ppm for two out of three conjugates in presence of internal standard. On-line micro-SPE was successfully used for trapping and desalting of the microdialysates. The small SPE pre-column made it possible to inject approximately 100 times more sample on the analytical column compared to injection without pre-column. Selective trapping was demonstrated for the polar catechol amine metabolite, dihydroxyketobemidone, which forms covalent complexes with phenylboronic acid (PBA). A fluorinated silica type stationary phase was the only column out of several tested that was able to separate ketobemidone and all relevant phase I metabolites. Liquid chromatography and mass spectrometry are independently valuable tools in the field of analytical pharmaceutical chemistry. The present study showed that the combination of LC-MS, with its excellent selectivity and sensitivity, offers an outstanding tool in the qualitative analysis of drugs and metabolites in biological fluids.

A numerical method (SIMPLE DIRK Method) for unsteady incompressible viscous flow simulation is presented. The proposed method can be used to achieve arbitrarily high order of accuracy in time-discretization which is otherwise limited to second order in majority of the currently used simulation techniques. A special class of implicit Runge-Kutta methods is used for time discretization in conjunction with finite volume based SIMPLE algorithm. The algorithm was tested by solving for velocity field in a lid-driven square cavity. In the test case calculations, power law scheme was used in spatial discretization and time discretization was performed using a second-order implicit Runge-Kutta method. Time evolution of velocity profile along the cavity centerline was obtained from the proposed method and compared with that obtained from a commercial computational fluid dynamics software program, FLUENT 6.2.16. Also, steady state solution from the present method was compared with the numerical solution of Ghia, Ghia, and Shin and that of Erturk, Corke, and Goökçöl. Good agreement of the solution of the proposed method with the solutions of FLUENT; Ghia, Ghia, and Shin; and Erturk, Corke, and Goökçöl establishes the feasibility of the proposed method.

A numerical method (SIMPLE DIRK Method) for unsteady incompressible viscous flow simulation is presented. The proposed method can be used to achieve arbitrarily high order of accuracy in time-discretization which is otherwise limited to second order in majority of the currently used simulation techniques. A special class of implicit Runge-Kutta methods is used for time discretization in conjunction with finite volume based SIMPLE algorithm. The algorithm was tested by solving for velocity field in a lid-driven square cavity. In the test case calculations, power law scheme was used in spatial discretization and time discretization was performed using a second-order implicit Runge-Kutta method. Time evolution of velocity profile along the cavity centerline was obtained from the proposed method and compared with that obtained from a commercial computational fluid dynamics software program, FLUENT 6.2.16. Also, steady state solution from the present method was compared with the numerical solution of Ghia, Ghia, and Shin and that of Erturk, Corke, and Goökçöl. Good agreement of the solution of the proposed method with the solutions of FLUENT; Ghia, Ghia, and Shin; and Erturk, Corke, and Goökçöl establishes the feasibility of the proposed method.

Tight gas and shale oil play an important role in energy security and in meeting an increasing energy demand. Hydraulic fracturing is a widely used technology for recovering these resources. The design and evaluation of hydraulic fracture operation is critical for efficient production from tight gas and shale plays. The efficiency of fracturing jobs depends on the interaction between hydraulic (induced) and naturally occurring discrete fractures. In this work, a coupled reservoir-fracture flow model is described which accounts for varying reservoir geometries and complexities including non-planar fractures. Different flow models such as Darcy flow and Reynold's lubrication equation for fractures and reservoir, respectively are utilized to capture flow physics accurately. Furthermore, the geomechanics effects have been included by considering a multiphase Biot's model. An accurate modeling of solid deformations necessitates a better estimation of fluid pressure inside the fracture. The fractures and reservoir are modeled explicitly allowing accurate representation of contrasting physical descriptions associated with each of the two. The approach presented here is in contrast with existing averaging approaches such as dual and discrete-dual porosity models where the effects of fractures are averaged out. A fracture connected to an injection well shows significant width variations as compared to natural fractures where these changes are negligible. The capillary pressure contrast between the fracture and the reservoir is accounted for by utilizing different capillary pressure curves for the two features. Additionally, a quantitative assessment of hydraulic fracturing jobs relies upon accurate predictions of fracture growth during slick water injection for single and multistage fracturing scenarios. It is also important to consistently model the underlying physical processes from hydraulic fracturing to long-term production. A recently introduced thermodynamically consistent phase-field approach for pressurized fractures in porous medium is utilized which captures several characteristic features of crack propagation such as joining, branching and non-planar propagation in heterogeneous porous media. The phase-field approach captures both the fracture-width evolution and the fracture-length propagation. In this work, the phase-field fracture propagation model is briefly discussed followed by a technique for coupling this to a fractured poroelastic reservoir simulator. We also present a general compositional formulation using multipoint flux mixed finite element (MFMFE) method on general hexahedral grids with a future prospect of treating energized fractures. The mixed finite element framework allows for local mass conservation, accurate flux approximation and a more general treatment of boundary conditions. The multipoint flux inherent in MFMFE scheme allows the usage of a full permeability tensor. An accurate treatment of diffusive/dispersive fluxes owing to additional velocity degrees of freedom is also presented. The applications areas of interest include gas flooding, CO₂ sequestration, contaminant removal and groundwater remediation. / text

Tyrimo objektas – pilnoji ir ABC išlaidų apskaitos sistemos. Darbo tikslas – atsižvelgiant į išlaidų apskaitos sistemos pasirinkimą sąlygojančius veiksnius pagrįsti ABC sistemos taikymo tikslingumą siekiant tiksliau apskaičiuoti produkcijos savikainą. Uždaviniai: • išanalizuoti išlaidų apskaitos sistemos esmę; • nustatyti pagrindinių veiksnių įtaką išlaidų apskaitos sistemų pasirinkimui; • išanalizuoti pilnosios ir ABC išlaidų apskaitos sistemų esmę, privalumus ir trūkumus; • naudojantis atliktos anketinės apklausos duomenimis, išanalizuoti išlaidų apskaitos sistemų taikymo Lietuvos įmonėse patirtį ir problemas; • pasirinktos įmonės pavyzdžiu pagrįsti ABC sistemos tinkamumą norint tiksliau paskirstyti netiesiogines išlaidas. Tyrimo metodai – nagrinėjant išlaidų apskaitos sistemos esmę, jos pasirinkimą lemiančius veiksnius naudojamasi literatūros šaltinių analizės, palyginimo metodais. Analizuojant pilnąją ir ABC išlaidų apskaitos sistemas dar panaudoti sintezės, anketavimo, grafiniai ir apibendrinimo metodai. Išanalizavus mokslinę literatūrą, atskleista išlaidų apskaitos sistemos esmė, nustatytas išlaidų apskaitos sistemų ir jų pasirinkimą lemiančių veiksnių ryšys. Atlikus literatūros šaltinių analizę ir anketinį tyrimą nustatyti pilnosios ir ABC išlaidų apskaitos sistemų privalumai, trūkumai ir jų taikymo tinkamumas norint paskirstyti netiesiogines išlaidas. / The object of research – absorption and ABC cost systems. The goal of research - in consideration of factors which influence costs accounting system to argue ABC system usefulness on purpose to calculate more accurate production cost. The tasks are as follows: • to display meaning of cost accounting system; • to estimate the link between factors which influence costs accounting systems; • to analyze absorption and ABC cost systems, their limitations, advantages; • to identify cost accounting systems in practice and problems in Lithuanian companies using questionarable data; • to check ABC system suitability for more accurate indirect cost assigning in chosen company. Methods of research: displaying meaning of cost accounting system and factors which influence costs accounting systems were used literature analysis, comparison. Analyzing absorption and ABC cost accounting systems were used also synthesis, questionairing, graphic and generalization. After scientific literatures have been analyzed it comes clear cost system meaning, the link between factors which influence costs accounting systems and cost accounting systems. After questionairing analysis have been identified advantages and disadvantages of absorption and ABC cost accounting systems, their suitability for more accurate indirect cost assigning.

Complex 3D digital objects are used in many domains such as animation films, scientific visualization, medical imaging and computer vision. These objects are usually represented by triangular meshes with many triangles. The simplification of those objects in order to keep them as close as possible to the original has received a lot of attention in the recent years. In this context, we propose a simplification algorithm which is focused on the accuracy of the simplifications. The mesh simplification uses edges collapses with vertex relocation by minimizing an error metric. Accuracy is obtained with the two error metrics we use: the Accurate Measure of Quadratic Error (AMQE) and the Symmetric Measure of Quadratic Error (SMQE). AMQE is computed as the weighted sum of squared distances between the simplified mesh and the original one. Accuracy of the measure of the geometric deviation introduced in the mesh by an edge collapse is given by the distances between surfaces. The distances are computed in between sample points of the simplified mesh and the faces of the original one. SMQE is similar to the AMQE method but computed in the both, direct and reverse directions, i.e. simplified to original and original to simplified meshes. The SMQE approach is computationnaly more expensive than the AMQE but the advantage of computing the AMQE in a reverse fashion results in the preservation of boundaries, sharp features and isolated regions of the mesh. For both measures we obtain better results than methods proposed in the literature.

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This essay investigates how the first person narrative of Mark Haddon’s neurodiverse protagonist in The Curious Incident of the Dog in the Night-Time raises awareness for the complexity of neurodiversity in relation to a neurotypical society. This has been done by applying the critical lens of Disability Studies and Disability Studies in Education to explain how disability is a concept of social and cultural construct. As the Swedish school has failed to provide neurodiverse students with the inclusive environment they need, the importance of fostering students who are accepting towards cognitive disabilities is greater than ever. This essay therefore argues that an inclusion of Haddon’s novel in the EFL classroom could be used to provide the students with understanding for neurodiversity as well as strategies that could help them to navigate in a socially demanding society.