Almost all logging in Sweden is carried out by the Cut-To-Length method. The method is carried out by two machines, a harvester and a forwarder. The forwarder transports the cut logs from the forest to a landing area for further transportation. Due to the uneven ground, the operators are subjected to high amplitude vibrations and the vehicle damages the ground soil when the pressure is unevenly distributed between the vehicles wheels. In an endeavor to decrease soil damage and increase the comfort for the operator, Skogforsk in collaboration with eXtractor is developing a pendulum arm suspended forwarder, named XT28. The benefit with such a forwarder is that each pendulum arm and wheel can be controlled individually. In this project a scale model (1:5) of the XT28 was developed and realized in order to enable implementation and development of a control system for its active pendulum arm suspension. A scaled model is much easier to handle and manage when tests is going to be performed. Additionally it is much more cost efficient than working with a full-scaled model. The focus point for this project will be the pendulum arm suspension and as a final test the function of this type of suspension will be tested and examined. Apart from a few design changes the downscaled model is a good representation of the XT28 and can be used in the development of a control system. After testing, it can be said that the downscaled prototype represents the full-scaled forwarder well when it comes to test the function of the pendulum arms. / Skogsavverkningen i Sverige utförs nästan uteslutande genom cut-to-length-metoden. Metoden utförs av två maskiner, en skördare och en skotare. Skotaren transporterar fällda träd från skogen till en lastplats för vidare transport. På grund av det ojämna underlaget utsätts operatören för vibrationer med hög amplitud och fordonet skadar underlaget när marktrycket är ojämnt fördelat mellan hjulen. I ett försök att minska markskador och öka komforten för operatören utvecklar Skogforsk i sammarbete med eXtractor en skotare med pendelarmsdämpning, där hjulen kan styras individuellt. Skotaren heter XT28. I detta projekt utvecklades och framställdes en skalmodell (1:5) av XT28 med syftet att möjliggöra förverkligandet och utvecklandet av ett kontrollsystem till den aktiva dämpningen i pendelarmarna. En skalmodell är mycket enklare att hantera när tester skall utföras. Dessutom är det mer kostnadseffektivt jämfört med att arbeta med fullskalemodellen. Detta projekts fokus kommer att ligga på pendelarmarna och som ett slutgiltigt test kommer funktionen av denna dämpning att testas och undersökas. Med undantag av några konstruktionsändringar representerar den nedskalade modellen skotaren XT28 väl och kan användas i utvecklandet av ett kontrollsystem. Efter utförda tester kan det konstateras att den nedskalade prototypen representerar den fullskaliga skotaren väl när det kommer till att testa funktionen av pendelarmsdämpningen.

The aim of the present study is to develop subgrid-scale models that are relevant for complex flows and combustion. A stochastic model based on a stochastic Smagorinsky constant with adjustable variance and time scale is proposed. The stochastic model is shown to provide for backscatter of both kinetic energy and scalar variance without causing numerical instabilities. A new subgrid-scale scalar flux model is developed using the same kind of methodology that leads to the explicit algebraic scalar flux model, EASFM, for RANS. The new model predicts the anisotropy of the subgrid-scales in a more realistic way than the eddy diffusion model. Both new models were tested in rotating homogeneous shear flow with a passive scalar. Rogallo’s method of moving the frame with the mean flow to enable periodic boundary conditions was used to simulate homogeneous shear flow. / QC 20101119

Heart failure occurs when the heart is not capable to pump blood at a sufficient rate to meet the demands of the body. Depending on the health of the heart, doctors may recommend a heart transplant, but finding a suitable donor is often a long duration process and the patient might be at an advance condition or the patient is not adequate for a heart transplant. In such cases Ventricular assist devices (VAD) are implemented. The purpose of a VAD is to aid the heart to pump the correct amount of blood, by doing so it relives the load that is put on the heart while giving the patient a chance for recovery. This study focuses on observing the hemodynamic effects of implementing a left ventricular assist device (LVAD) along the aortic arch and main arteries. Thrombi creation and transportation is other subject included in the study, due to the fact that thrombi can obstruct blood flow to critical arteries, manly carotid and vertebral. Occlusion of these can lead to a stroke with devastating effects on the neurocognitive functions and even death. A multi-scale CFD analysis a patient specific geometry model is used as well as a lumped system which provides the correct conditions in order to simulate the whole cardiovascular system. The main goal of the study is to understand the difference in flow behavior created by the unsteady pulsatile boundary conditions. The model described in this work has a total cardiac output of 7.0 Liters/ minute, this for a healthy heart. Two cardiac output splits are used to simulate heart failure conditions. The first split consists of 5 Liters/minute flowing through the LVAD cannula and 2 Liters/minute via the aortic root. The second scenario is when heart iv failure is critical, meaning that zero flow is being output by the left ventricle, thus a split of 7 Liter/minute trough the LVAD cannula and 0 Liters/minute traveling through the aortic root. A statistical analysis for the thrombi motion throughout the patient aortic arch was performed in order to quantify the influence that pulsatile flow has on the particles being track. Spherical particles of 2mm, 4mm and 5mm were released and accounted in the statistical analysis for each of the two split configurations. The study focuses on particles that escaped on the outlet boundaries of the upper arteries (Right Carotid, Left Carotid, and Vertebral). Results exhibit the statistical comparison of means for each particle diameter as well as for the overall probability for the steady and unsteady flow condition.

Cryogenic air separation units (ASUs) are the most widely used technology for industrialscale production of large amounts of high-purity air components. These are highly energyintensive processes, which have motivated the development of demand response strategies to adapt their operation in response to the increased volatility of the energy market. The startup of ASUs warrants particular consideration within this context. ASUs are tightly integrated, thermally and materially, and have slow dynamics. These result in startup times on the order of hours to a day, during which electricity is consumed with limited revenue generation. In the current environment of electricity price deregulation, it may be economically advantageous for ASUs to shut down during periods of high electricity pricing, increasing the occurrences of startups. This presents a promising research opportunity, especially because ASU startup has received relatively little attention in the literature. This thesis investigates the optimal startup of ASUs using dynamic optimization. First, this thesis focuses on startup model development for the multiproduct ASU. Startup model development requires accounting for discontinuities present at startup. Four main discontinuities are considered: stage liquid flow discontinuity, stage vapor flow discontinuities, flow liquid out of sumps and reboilers, and opening and closing valves. Other types of discontinuities accounted for include the change in the number of phases of streams. These discontinuities are approximated with smoothing formulations, using mostly hyperbolic tangent functions, to allow application of gradient-based optimization. The modeling approach was assessed through three case studies: dynamic simulation of a successful startup, dynamic simulation of a failed startup, and dynamic optimization using a least-squares minimization formulation. Following startup model development, this thesis investigates the development of a framework for optimizing ASU startups using readily interpretable metrics of time and economics. For economics, cumulative profit over the startup horizon is considered. Two events are tracked for the definition of time metrics: time taken to obtain product purities and time to obtain steady-state product flows. Novel approaches are proposed for quantifying these time metrics, which are used as objective functions and in formulating constraints. The / Thesis / Doctor of Philosophy (PhD)

Yes / In nearshore regions, bidirectional tidal flow is the main hydrodynamic factor, which induces local scour around submarine pipelines. So far, most studies on scour around submarine pipelines only consider the action of unidirectional, steady currents and little attention has been paid to the situation of bidirectional tidal currents. To deeply understand scour characteristics and produce a more accurate prediction method in bidirectional tidal currents for engineering application, a series of laboratory scale experiments were conducted in a bidirectional current flume. The experiments were carried out at a length scale of 1:20 and the tidal currents were scaled with field measurements from Cezhen pipeline in Hangzhou Bay, China. The experimental results showed that under bidirectional tidal currents, the scour depth increased significantly during the first half of the tidal cycle and it only increased slightly when the flow of the tidal velocity was near maximum flood or ebb in the following tidal cycle. Compared with scour under a unidirectional steady current, the scour profile under a bidirectional tidal current was more symmetrical, and the scour depth in a bidirectional tidal current was on average 80% of that under a unidirectional, steady current based on maximum peak velocity. Based on previous research and the present experimental data, a more accurate fitted equation to predict the tidally induced live-bed scour depth around submarine pipelines was proposed and has been verified using field data from the Cezhen pipeline.

Computational biology enabled us to manage vast amount of experimental data and make inferences on observations that we had not made. Among the many methods, predicting metabolic functions with genome-scale models had shown promising results in the recent years. Using sophisticated algorithms, such as flux balance analysis, OptKnock, and OptForce, we can predict flux distributions and design metabolic engineering strategies at a greater efficiency. The caveat of these current methods is the accuracy of the predictions. We proposed using flux balance analysis with flux ratios as a possible solution to improving the accuracy of the conventional methods. To examine the accuracy of our approach, we implemented flux balance analyses with flux ratios in five publicly available genome-scale models of five different organisms, including Arabidopsis thaliana, yeast, cyanobacteria, Escherichia coli, and Clostridium acetobutylicum, using published metabolic engineering strategies for improving product yields in these organisms. We examined the limitations of the published strategies, searched for possible improvements, and evaluated the impact of these strategies on growth and product yields. The flux balance analysis with flux ratio method requires a prior knowledge on the critical regions of the metabolic network where altering flux ratios can have significant impact on flux redistribution. Thus, we further developed the reverse flux balance analysis with flux ratio algorithm as a possible solution to automatically identify these critical regions and suggest metabolic engineering strategies. We examined the accuracy of this algorithm using an Arabidopsis genome-scale model and found consistency in the prediction with our experimental data. / Master of Science

Tesis por compendio / [ES] Saccharomyces cerevisiae, además de ser un importante organismo modelo en biología, es indiscutiblemente la especie de levadura más utilizada en procesos fermentativos industriales, incluyendo el sector enológico. Su capacidad de fermentar en concentraciones elevadas de azúcares, tolerar concentraciones altas de etanol y soportar la adición de sulfitos, son algunos de los factores que explican su éxito en fermentaciones vínicas. El metabolismo fermentativo de S. cerevisiae en condiciones enológicas se conoce bien gracias a una amplia bibliografía científica. En cambio, aún se sabe poco sobre el metabolismo de las especies de Saccharomyces criotolerantes, S. uvarum y S. kudriavzevii, quienes han suscitado recientemente el interés del sector vitivinícola por sus buenas propiedades fermentativas a bajas temperaturas, tales como la producción de vinos con mayor contenido en glicerol y alta complejidad aromática, llegando a veces a reducir su contenido en etanol. En este contexto, esta tesis pretende ampliar nuestros conocimientos sobre el metabolismo fermentativo de S. uvarum y S. kudriavzevii en condiciones enológicas, profundizando en el entendimiento de las diferencias existentes con el de S. cerevisiae, así como entre cepas de S. cerevisiae de distintos orígenes. Para ello, hemos utilizado varias técnicas ómicas para analizar la dinámica de los metabolomas (intra- y extracelulares) y/o transcriptomas de cepas representativas de S. cerevisiae, S. uvarum y S. kudriavzevii a alta (25 °C) y baja (12 °C) temperatura de fermentación. También, hemos desarrollado un modelo metabólico a escala de genoma que, junto a un análisis de balance de flujos, es capaz de cuantificar los flujos a través del metabolismo del carbono y del nitrógeno de levaduras en cultivo de tipo batch. Así, el conjunto de estos trabajos nos ha permitido identificar rasgos metabólicos y/o transcriptómicos relevantes para el sector enológico en estas especies. También se aporta nueva información sobre las especificidades de redistribución de flujos en la red metabólica de levaduras del género Saccharomyces acorde a la especie y las fluctuaciones ambientales que ocurren durante una fermentación vínica. / [CAT] Saccharomyces cerevisiae, a més de ser un important organisme model en biologia, és indiscutiblement l'espècie de llevat més utilitzat en processos fermentatius industrials, incloent el sector enològic. La seua capacitat de fermentar grans concentracions de sucres, tolerar concentracions altes d'etanol i suportar l'addició de sulfits, són alguns dels factors que expliquen el seu èxit en fermentacions víniques. D'aquesta manera, el metabolisme fermentatiu de S. cerevisiae en condicions enològiques està ben descrit i es beneficia d'una àmplia bibliografia científica. En canvi, poc se sap encara sobre el metabolisme de les espècies de Saccharomyces criotolerants, S. uvarum i S. kudriavzevii, els qui han recentment suscitat l'interés del sector vitivinícola per les seues bones propietats fermentatives a baixes temperatures, com ara la producció de vins amb major contingut en glicerol, alta complexitat aromàtica i arribant a vegades a reduir el seu contingut en etanol. En aquest context, aquesta tesi pretén ampliar els nostres coneixements sobre el metabolisme fermentatiu de S. uvarum i S. kudriavzevii en condicions enològiques, aprofundint en l'enteniment de les diferències existents amb el de S. cerevisiae, així també com entre ceps de S. cerevisiae de diferents orígens. Per a això, hem utilitzat diverses tècniques omiques per a analitzar la dinàmica dels metabolomes (intra- i extracelul·lars) i/o transcriptomes de ceps representatius de S. cerevisiae, S. uvarum i S. kudriavzevii a alta (25 °C) i baixa (12 °C) temperatures de fermentació. També, hem desenvolupat un model metabòlic a escala del genoma que, al costat d'una anàlisi de balanç de fluxos, és capaç de quantificar els fluxos a través del metabolisme carbonat i nitrogenat de llevats en cultius de tipus batch. Així, el conjunt d'aquests treballs ens ha permés identificar trets metabòlics i/o transcriptómics rellevants per al sector enològic en aquestes espècies. També aporta nova informació sobre les especificitats de redistribució de fluxos en la xarxa metabòlica de llevats del gènere Saccharomyces concorde a l'espècie i les fluctuacions ambientals ocorrent durant una fermentació vínica. / [EN] Saccharomyces cerevisiae, besides being an important model organism in biology, is undoubtedly the most widely used yeast species in industrial fermentation processes, including the winemaking sector. Its ability to ferment at high levels of sugars, tolerate high ethanol concentrations and withstand the addition of sulfites are some of the factors explaining its success in wine fermentation. Accordingly, the fermentative metabolism of S. cerevisiae under oenological conditions is well described and benefits from a large scientific literature. In contrast, little is known about the metabolism of the cryotolerant Saccharomyces species, S. uvarum and S. kudriavzevii, which have recently attracted the interest of the wine industry for their good fermentative properties at low temperatures, such as the production of wines with higher glycerol content, high aromatic complexity and sometimes even reduced ethanol content. In this context, this thesis aims to expand our knowledge on the fermentative metabolism of S. uvarum and S. kudriavzevii under oenological conditions, deepening our understanding of the existing differences with that of S. cerevisiae, as well as between S. cerevisiae strains of different origins. For this purpose, we have used several omics techniques to analyze the dynamics of the (intra- and extracellular) metabolomes and/or transcriptomes of representative strains of S. cerevisiae, S. uvarum and S. kudriavzevii at high (25 °C) and low (12 °C) fermentation temperatures. Also, we have developed a genome-scale metabolic model that, together with a flux balance analysis, is able to quantify fluxes through carbon and nitrogen metabolism of yeast in batch culture. Taken together, this work has allowed us to identify metabolic and/or transcriptomic traits relevant to the oenological sector in these species. It also provides new information on the specificities of flux redistribution in the metabolic network of Saccharomyces yeasts according to the species and environmental fluctuations occurring during wine fermentation. / The present work has been carried out at the Department of Food Biotechnology of the IATA (CSIC). Romain Minebois was funded by a FPI grant (REF: BES-2016-078202) and supported by projects AGL2015-67504-C3-1R and RTI2018-093744-BC31 of the Ministerio de Ciencia e Inovación awarded to Amparo Querol. / Minebois, RCM. (2021). Study of the differences in the fermentative metabolism of S. cerevisiae, S. uvarum and S. kudriavzevii species [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/176018 / Compendio

Advances in bioinformatics and computational biology have enabled integration of an enormous amount of known biological interactions. This has enabled researchers to use models and data to design experiments and guide new discovery as well as test for consistency. One such computational method is constraint-based metabolic flux modeling. This is performed using genome-scale metabolic models (GEMs) that are a collection of biochemical reactions, derived from a genome's annotation. This type of flux modeling enables prediction of net metabolite conversion rates (metabolic fluxes) to help understand metabolic activities under specific environmental conditions. It can also be used to derive metabolic engineering strategies that involve genetic manipulations. Over the past decade, GEMs have been constructed for several different microbes, plants, and animal species. Researchers have also developed advanced algorithms to use GEMs to predict genetic modifications for the overproduction of biofuel and valuable commodity chemicals. Many of the predictive algorithms for microbes were validated with experimental results and some have been applied industrially. However, there is much room for improvement. For example, many algorithms lack straight-forward predictions that truly help non-computationally oriented researchers understand the predicted necessary metabolic modifications. Other algorithms are limited to simple genetic manipulations due to computational demands. Utilization of GEMs and flux-based modeling to predict in vivo characteristics of multicellular organisms has also proven to be challenging. Many researchers have created unique frameworks to use plant GEMs to hypothesize complex cellular interactions, such as metabolic adjustments in rice under variable light intensity and in developing tomato fruit. However, few quantitative predictions have been validated experimentally in plants. This research demonstrates the utility of GEMs and flux-based modeling in both metabolic engineering and analysis by tackling the challenges addressed previously with alternative approaches. Here, a novel predictive algorithm, Node-Reward Optimization (NR-Opt) toolbox, was developed. It delivers concise and accurate metabolic engineering designs (i.e. genetic modifications) that can truly improve the efficiency of strain development. As a proof-of-concept, the algorithm was deployed on GEMs of E. coli and Arabidopsis thaliana, and the predicted metabolic engineering strategies were compared with results of well-accepted algorithms and validated with published experimental data. To demonstrate the utility of GEMs and flux-based modeling in analyzing plant metabolism, specifically its response to changes in the signaling pathway, a novel modeling framework and analytical pipeline were developed to simulate changes of growth and starch metabolism in Arabidopsis over multiple stages of development. This novel framework was validated through simulation of growth and starch metabolism of Arabidopsis plants overexpressing sucrose non-fermenting related kinase 1.1 (SnRK1.1). Previous studies suggest that SnRK1.1 may play a critical signaling role in plant development and starch level (a critical carbon source for plant night growth). It has been shown that overexpressing of SnRK1.1 in Arabidopsis can delay vegetative-to-reproductive transition. Many studies on plant development have correlated the delay in developmental transition to reduction in starch turnover at night. To determine whether starch played a role in the delayed developmental transition in SnRK1.1 overexpressor plants, starch turnover was simulated at multiple developmental stages. Simulations predicted no reduction in starch turnover prior to developmental transition. Predicted results were experimentally validated, and the predictions were in close agreement with experimental data. This result further supports previous data that SnRK1.1 may regulate developmental transition in Arabidopsis. This study further validates the utility of GEMs and flux-based modeling in guiding future metabolic research. / Ph. D. / Recent advances in genetic and biochemical studies revealed the incredible complexity of cells, which generated interests in using computers to aid whole cell analyses and design cell engineering strategies to overproduce valuable commodity chemicals, such as biofuel, medicines, polymers, and many industrial materials. In order to use computers to study cells, current knowledge of cellular machinery is converted into mathematical models, such as genome-scale metabolic models. Genome-scale metabolic models are used to simulate the rates of chemical events in cells, which helps researchers predict cellular outputs of interest, such as growth rate and chemical synthesis rates. Combining genome-scale metabolic models with sophisticated computer algorithms, researchers can simulate numerous cell engineering experiments and select a few candidates to test physically, which can reduce cost and research time significantly. This computational technique has been well validated in microorganisms, such as E. coli and yeast; however, the ability to simulate cellular chemistry accurately in plants remains a challenge, which was a goal in my research. In addition, my research also aimed to reduce the inefficiencies in previous cell engineering design algorithms. I was able to develop a novel genome-scale model framework that enabled accurate simulation of plant growth and changes of starch content over time. I also developed a new computer algorithm that could significantly improve the efficiency in designing cell engineering strategies.

Mangotes de transferência têm sido utilizados em grande quantidade em operações de descarga de óleo, principalmente em águas profundas, onde existem cargas estáticas e cíclicas variáveis devido ao ambiente de trabalho. Apesar da grande demanda dessas estruturas, seu comportamento é pouco conhecido e discutido na literatura devido a sua complexidade. Além disso, os materiais utilizados nesse equipamento podem ocasionar um elevado número de falhas, sendo muitas vezes superestimados, deixando o mangote com peso excessivo. Este trabalho objetiva o desenvolvimento de uma metodologia de análise de materiais poliméricos avançados, especificamente fibras de poliaramida e materiais compósitos à base de fibra de carbono, em substituição a materiais tradicionais, utilizando modelos numéricos capazes de prever o comportamento da pressão de ruptura das carcaças e resistência a compressão radial do mangote, além da avaliação em fadiga dos cordonéis à base de poliaramida dessas novas estruturas. Modelos em meso-escala foram desenvolvidos utilizando conceitos de hiperelasticidade e de critérios de falha de materiais compósitos para previsão das tensões e deformações locais em regiões críticas do mangote. Análises numéricas foram realizadas via elementos finitos com o software comercial para auxiliar a elaboração dos modelos e a realização dos cálculos numéricos. Foram realizados ensaios experimentais para validação desses modelos numéricos, bem como para a previsão do comportamento estático e em fadiga dos materiais envolvidos. Foram desenvolvidos dois modelos. Em um modelo foi aplicado pressão interna no mangote para previsão de ruptura das carcaças no qual tem o objetivo de avaliar o desempenho dos novos reforços de poliaramida. No outro modelo foi aplicada uma carga radial na seção central do mangote para prever a resistência ao esmagamento, no qual tem o objetivo de avaliar o desempenho do componente de sustentação em material compósito de fibra de carbono. Os resultados dos modelos numéricos apresentaram boa concordância com os resultados experimentais em grande parte das análises. Também se observou que os novos materiais apresentam um grande potencial de substituição dos materiais tradicionais, bem como um excelente comportamento frente a carregamentos estáticos e dinâmicos envolvidos na aplicação, sendo verificada diminuição significativa de peso e aumento do desempenho. / Offloading hoses have been extensively used at offloading oil operations, especially in deep water, where there are variable static and cyclic loads due to the working environment. Despite the great demand for these structures, their behavior is little known and discussed in the literature due to the complexity. In addition, the materials used in this equipment may lead to a high number of failures, being often overestimated, leading to excessive weight. This work aims to develop a methodology for analysis of advanced polymeric materials, specifically polyaramide fibers and carbon fiber composite materials, in the substitution of traditional materials, using numerical models able to predict the static behavior of the burst pressure of the carcasses and radial compression strength of the hose. In addition, fatigue tests were performed to evaluate the polyaramide cords of these new structures. Meso-scale models were developed using advanced hyperplastic and composite failure criteria concepts to predict local stresses and strains in critical regions of the hose. Numerical analyses were performed using finite elements with commercial software to aid the development of models and to carry out numerical calculations. Several experimental tests were performed to validate numerical models, as well as to forecast the static and fatigue behavior of the materials used. Two models were developed. A model is used to predict the burst pressure of the hose in order to evaluate the performance of the new polyaramide reinforcements cords. In the other model, a radial load was applied in the central section of the hose to predict the crushing strength, in which it has the aim of evaluating the performance of the load-bearing component made with carbon fiber composite material. The results of the computer models showed good agreement with the experimental results in most analyses. It was also found that the studied materials offered considerable potential for the substitution of traditional materials, as well as an excellent behavior under static and dynamic loads related to this application, with a significant weight reduction and increased performance of the new configurations over traditional hoses.

A new ESSA indicator of school quality and student success provides flexibility to broaden a states’ definition of school and student success. Educational research has found school success is in part determined by a school’s climate and should be considered in improvement/reform strategies (Cohen et al., 2009; Thapa et al., 2013). Yet, school climate research is often difficult and time consuming, and employs a variety of conflicting definitions and dimensions, instruments, and empirical approaches to determining school climate. Given these significant limitations with current measures, the purpose of this study was to validate an instrument measuring school climate based on the four most commonly accepted dimensions of school climate, using items adapted from a well-regarded and established theoretical framework to provide an effective measure for educators and researchers. The sample selected for this study was a portion of teachers who indicated teaching 3rd or 8th grade as their primary teaching assignment (n=500) from the larger study sample (n=4974). A Rasch Rating Scale Model was used to evaluate unidimensionality, item fit and difficulty, reliability, and potential differential item functioning on a 23-item school climate survey. Results of the study showed the instrument was not unidimensional and was split into two subdimensions: student-centered and teacher/school support. All items were retained and displayed appropriate fit. Significant differential item functioning (DIF) was found between 3rd and 8th grade teachers on both subdimensions, further suggesting multidimensionality in the scale. Study findings suggest researchers should be mindful of any school climate instrument not validated at the item level for unidimensionality, and that an instrument may perform differently for teachers at different grade levels.