Multiple-indicators multiple-causes (MIMIC) modeling is often employed for measurement invariance testing under the structural equation modeling framework. This Monte Carlo study explored the behaviors of MIMIC as a measurement invariance testing method in different research situations. First, the performance of MIMIC under the factor loading noninvariance conditions was investigated through model fit evaluations and likelihood ratio tests. This study demonstrated that the violation of factor loading invariance was not detected by any of the typically reported model fit indices. Consistently, the likelihood ratio tests for MIMIC models exhibited poor performance in identifying noninvariance in factor loadings. That is, MIMIC was insensitive to the presence of factor loading noninvariance, which implies that factor loading invariance should be examined through other measurement invariance testing techniques. To control Type I error inflation in detecting the noninvariance of intercepts or thresholds, this simulation study with both continuous and categorical variables employed the likelihood ratio test with two critical value adjustment strategies, Oort adjustment and Bonferroni correction. The simulation results showed that the likelihood ratio test with Oort adjustment not only controlled Type I error rates below the basal Type I error rates but also maintained high power across study conditions. However, it was observed that power to detect the noninvariant variables slightly attenuated with multiple (i.e., two) noninvariant variables in a model. Given that the modification index is the chi-square difference after relaxing one parameter for estimation, this study investigated modification indices under four research scenarios based on a combination of the cutoffs of modification indices and the procedures of model modification: (a) the noniterative method (i.e., modification indices at the initial stage of model modification) using the conventional critical value, (b) the noniterative method using the Oort adjusted critical value, (c) the iterative procedure of model modification using the conventional critical value, and (d) the iterative procedure using the Oort adjustment. The iterative model search procedure using modification indices showed high performance in detecting noninvariant variables even without critical value adjustment, which indicates that iterative model search specification does not require critical value adjustment in identifying the noninvariance correctly. On the other hand, when the noniterative procedure was used, the Oort adjustment yielded adequate results.

The development of novel, peptide based structures for tissue engineering materials has been widely researched, and its popularity can be attributed to advancements in technological analysis methods. Using principles based on protein structure and organization, this work describes the novel self-assembly of depsipeptides, which incorporate alternating esters within a native peptide backbone. Chapter 1 introduces and reviews peptide mimics for their utility for tissue engineering applications. Chapter 2 describes the methodology in synthesizing and characterization a depsipeptide library using both solution and solid phase methods. Chapter 3 discusses the effects of depsipeptide length, concentration, and sequence within a range of ionic concentrations and pH ranges on the self-assembly of depsipeptides into spherical nanostructures, fibers, or hydrogels. Chapter 4 describes proposed methods to increase the rate of gelation, followed by discussions of biocompatibility studies from other self-assembling peptide and modified-peptide systems in vitro and in vivo. The work described in this dissertation demonstrates that the synthesis and self-assembly of a depsipeptide family which alternates esters into a native peptide backbone does not disrupt the formation of higher order structures. This study illustrates the potential to synthesize a wide range of depsipeptides with variable side chains and hydrophobic character, as understanding these effects on self-assembly is imperative to the development of biomimetic materials for tissue engineering applications. / text

VEIGA, Fernando Cavalcante. Modelagem da Economia Paralela na América Latina / Fernando Cavalcante Veiga. - 2017. 53 f. Dissertação (mestrado profissional). - Universidade Federal do Ceará, Programa de Pós Graduação em Economia, CAEN, Fortaleza, 2017. / Submitted by Mônica Correia Aquino (monicacorreiaaquino@gmail.com) on 2017-09-19T21:29:42Z No. of bitstreams: 1 2017_dis_fcveiga.pdf: 1495809 bytes, checksum: 95d236b7f9aaf13d0845e4b19446bb31 (MD5) / Approved for entry into archive by Mônica Correia Aquino (monicacorreiaaquino@gmail.com) on 2017-09-20T17:51:31Z (GMT) No. of bitstreams: 1 2017_dis_fcveiga.pdf: 1495809 bytes, checksum: 95d236b7f9aaf13d0845e4b19446bb31 (MD5) / Made available in DSpace on 2017-09-20T17:51:32Z (GMT). No. of bitstreams: 1 2017_dis_fcveiga.pdf: 1495809 bytes, checksum: 95d236b7f9aaf13d0845e4b19446bb31 (MD5) Previous issue date: 2017 / This dissertation estimates the size and evolution of the shadow economy in 18 Latin American countries, from 1990 to 2013, using the Multiple Indicators and Multiple Causes (MIMIC) model. It is noted that increases in regulatory intensity, opening of the economy, money supply and GDP per capita lead to grow the shadow economy, while investment growth tends to decrease it. The results obtained point to an average shadow economy of 35.6% of the official GDP in Latin America, with a tendency of growth during the studied period, a behavior that is also verified when fuzzy logic based estimation is used. With percentages below 28%, countries such as Chile, Argentina and Costa Rica contribute in a way to reduce the average of the region. Panama, Bolivia and Honduras, countries with the highest levels of informality, raise the average. The only Latin American country to register a decline in the shadow economy over the analyzed period is Venezuela. / Esta dissertação estima o tamanho e a evolução da economia paralela em 18 países latino-americanos, no período de 1990 a 2013, usando o modelo de múltiplos indicadores e múltiplas causas (MIMIC). Observa-se que aumentos da intensidade regulatória, da abertura da economia, da oferta monetária e do PIB per capita levam a incrementos na economia paralela, enquanto o crescimento dos investimentos tende a diminuí-la. Os resultados obtidos apontam para uma economia paralela média de 35,6% do PIB oficial da América Latina, com tendência de crescimento durante o período estudado, comportamento esse também verificado quando se utiliza estimação baseada na lógica fuzzy (difusa). Com percentuais abaixo de 28%, países como Chile, Argentina e Costa Rica contribuem de forma a diminuir a média da região. Já Panamá, Bolívia e Honduras, países com os maiores níveis de informalidade, elevam aquela média. O único país latino-americano a registrar diminuição da economia paralela, ao longo do período analisado, é a Venezuela.

The Tissue Engineering Research Lab at California Polytechnic State University, San Luis Obispo focuses on creating tissue-engineered blood vessel mimics (BVMs) for use in preclinical testing of vascular devices. These BVMs are composed of electrospun scaffolds made of an assortment of polymers that are seeded with different cell types. This integration of polymers with cells leads to the need for biocompatibility testing of the polymer scaffolds. Many of the lab’s newest scaffolds have not been fully characterized for biologic interactions. Therefore, the first aim of this thesis developed methods for in vitro cytotoxicity testing of polymers used in the fabrication of BVMs. This included cytotoxicity testing using direct contact and elution-based methods, along with fluorescent staining to visualize the scaffold effects on cells. The second aim of this thesis implemented the newly developed cytotoxicity protocols to evaluate the biocompatibility of existing polymers, ePTFE and PLGA, used in the tissue engineering lab. The results demonstrated that ePTFE and PLGA were noncytotoxic to cells. The third aim of this thesis evaluated the biocompatibility of novel polymers used to fabricate BVMs: PLGA with salt, PLLA, and PCL. Elution-based methods concluded that PLGA with salt, PLLA, and PCL were noncytotoxic to cells; however, the direct contact method illustrated PLGA with salt and PCL were mildly cytotoxic at 24 and 48 hours. Potential causes of this variability include the addition of salt to PLGA, dissolving PCL in dichloromethane, inadequate sample sizing, and the inherent differences between the test methods. Overall, this thesis developed and implemented methods to evaluate the biocompatibility of polymer scaffolds used in the BVM model, and found that ePTFE, PLGA, and PLLA scaffold materials were biocompatible and could be implemented in future BVM setups without concerns. Meanwhile, PLGA with salt and PCL’s toxicity was mild enough to urge future cytotoxicity testing on PLGA with salt and PCL before further use in the lab.

To prevent clotting during dialysis, heparin is used to line the tubing which blood flows through. Unfortunately, many side effects arise from taking heparin, especially when it is used for an extended period of time. As such, long-term exposure for individuals undergoing dialysis every day is unavoidable. To prevent the solubilized heparin from entering the bloodstream, a polymer-based natural material is being investigated. This materials properties include reduction of coagulation and elimination of the long-term effects of heparin such as heparin induced thrombocytopenia and osteoporosis. Cellulose nanocrystals (CNCs) contain the same 1,4 linked pyranose backbone structure as heparin along with desirable mechanical properties, like high stiffness and anisotropic shape. By altering the functionalization on the surface of CNCs to closely mirror that of heparin, it should be possible to make a biomimetic material that counteracts blood clotting, while not introducing soluble small molecule anti-coagulants into the body. Through blood assays and platelet fixing analysis, we have been able to show that this change in functionalization does reduce coagulation. Surface chemistry of CNCs were modified from 'plain' CNCs (70 mmol SO3-/kg residual from hydrolysis) to 500 mmol COO-/kg (TEMPO oxidized) and 330 mmol SO3-/kg CNC (sulfonated CNCs). We will show that by utilizing CNCs reactive functional groups and incredible mechanical properties we are able to create a material that reduces clotting while maintaining the tubing's mechanical strength as well as eliminating heparin's side effects associated with it being a soluble anticoagulant. / MS / To prevent clotting during dialysis, heparin is used to line the tubing which blood flows through. Heparin, an anticoagulant, is more commonly known as a ‘blood thinner’ which is a misnomer because it does not actually thin blood. Heparin works by inhibiting clotting factors in the coagulation cascade pathway which in turn limit the formation of blood clots and create the ‘thinning’ effect mentioned earlier. When dialysis is performed the interaction between blood and the dialyzer tubing initiates the formation of a blood clot. This is where heparin use comes in. Unfortunately, many side effects arise from taking heparin, especially when it is used for an extended period of time. As such, long-term exposure for individuals undergoing dialysis every day is unavoidable. To prevent heparin or its mimics from entering the bloodstream, a polymer-based natural material is being investigated. The properties of this material will include reduction of coagulation and elimination of the long-term effects of heparin. The polymer-based natural material being investigated is cellulose nanocrystals (CNCs). CNCs contain the same ring structure and chemical linkage sites as heparin along with desirable mechanical properties. By altering the surface chemistry on the CNCs to closely mirror that of heparin, it should be possible to make a biomimetic material that counteracts blood clotting, while not introducing a solution based small molecule anticoagulant to the body. Through blood assays and platelet fixing analysis, we have been able to show that this change in functionalization does reduce coagulation. The ‘plain’ CNCs used contained an initial charge density of 70 mmol SO₃⁻ /kg. This residual charge density was a result from the acid hydrolysis performed to acquire CNCs from cellulose. Chemically modified CNCs contained many more negatively charged functional groups with TEMPO oxidized and sulfated CNCs having 500 mmol COO⁻/kg and 330 mmol SO₃⁻ /kg, respectively. We will show that by utilizing CNCs reactive functional groups and incredible mechanical properties we are able to create a material that reduces clotting while maintaining the tubing’s mechanical strength as well as eliminating heparin’s side effects associated with it being a soluble anti-coagulant.

We report the design and assembly of three-dimensional (3D) multi-cellular liver models comprised of primary rat hepatocytes, liver sinusoidal endothelial cells (LSECs), and Kupffer cells (KCs). LSECs and KCs in the liver model were separated from hepatocytes by a nanoscale, detachable, optically transparent chitosan and hyaluronic acid (HA) polyelectrolyte multilayer (PEM) film. The properties of the PEM were tuned to mimic the Space of Disse found in liver. The thickness of the detachable PEM was 650 to 1000 nm under hydrated conditions. The Young's modulus of the PEM was approximately 42 kPa, well within the range of modulus values reported for bulk liver. The 3D liver models comprised of all three cell types and a detachable PEM exhibited stable urea production and increased albumin secretion over a 12 day culture period. Additionally, the 3D liver model maintained the phenotype of both LSECs and KCs over the 12 day culture period, verified by CD32b and CD163 staining, respectively. Additionally, CYP1A1 enzyme activity increased significantly in the 3D liver models. The number of hepatocytes in the 3D liver model increased by approximately 60% on day 16 of culture compared to day 4 indicating. Furthermore, only the 3D hepatic model maintained cellular compositions virtually identical to those found in vivo. DNA microarray measurements were conducted on the hepatocyte fractions of the 3D liver mimic to obtain insights into hepatic processes. Gene sets up-regulated in the 3D liver model were related to proliferation, migration, and deposition of extracellular matrix, all functions observed in regenerating hepatocytes. Taken together, these results suggest that inter-cellular signaling between the different cell types in the 3D liver model led to increased hepatic functions. To the best of our knowledge, this is the first study where three of the major hepatic cell types have been incorporated into a model that closely mimics the structure of the sinusoid. These studies demonstrate that the multi-cellular liver models are physiologically relevant. Such models are very promising to conduct detailed investigations into hepatic inter-cellular signaling. / Ph. D.

Šešėlinę ekonomiką daug kas supranta kaip nelegalų verslą ar kontrabandą. Tai nėra tik vogtų daiktų realizavimas, prostitucija ar narkotikai, kuriuos privalo kontroliuoti policija ir kitos valstybės institucijos. Tačiau ir legalus verslas taip pat tampa šešėlinės ekonomikos dalimi, kai jos veiklos rezultatai falsifikuojami siekiant išvengti mokesčių. Tai neteisėti sandoriai, nerealios jų vertės ir panašiai. Iš tiesų, tai sudėtingas reiškinys, iškreipiantis oficialiąją statistiką, stabdantis ekonomikos augimą. Šio darbo tikslas nustatyti ekonominius faktorius, reikšmingai įtakoja Lietuvos šešėlinę ekonomiką. Darbo eigoje apibrėžiama šešėlinė ekonomika, jos sudedamosios dalys bei vertinimo metodikos. Tyrimo metu sudaromas Lietuvos šešėlinės ekonomikos MIMIC (Multiple Indicator Multiple Causal) modelis. Tikrinamas jo suderinamumas su turimais statistiniais duomenimis. Taip pat pateikiamos trys skirtingos MIMIC modelio specifikacijos, remiantis statistiniais kriterijais jos palyginamos ir randama priimtiniausia. / There is considerable agreement internationally about the factors that determine the relative size of the underground economy and that evidence of underground activity will be captured in several economic indicators. Until recently, however, the methods that have been employed to measure the underground economy focused on only a few causal factors, one indicator, and only produced an estimate for one particular point in time. This paper presents the modeling technique that threats the underground economy as an unobservable or latent variable and incorporates multiple indicator and multiple causal variables – MIMIC model. Moreover this technique allows us to estimate the significance of each causal variable as well as each indicator. First of all the theoretical definition of the shadow economy is proposed. Further the MIMIC modeling technique is described and the emphasis is laid on the most common variables used for latter method. Subsequently, the model is defined and the corresponding economical variables of Lithuanian are chosen. Whereupon the model is estimated and respecified while nonsignificant variables and relations been removed. Finally the conclusions about the most suitable model and statistically significant variables are maid.

Using multi-group confirmatory factor analysis (MCFA) and multiple-indicator-multiple-cause (MIMIC) to investigate group difference in the context of the second-order factor model with either the unparceled or parceled data had never been thoroughly examined. The present study investigated (1) the difference of MCFA and MIMIC in terms of Type I error rate and power when testing the mean difference of the higher-order latent factor (delta kappa) in a second-order confirmatory factor analysis (CFA) model; and (2) the impact of data parceling on the test of (delta kappa) between groups by using the two approaches. The methods were introduced, including the design of the models, the design of Monte Carlo simulation, the calculation of empirical Type I Error and empirical power, the two parceling strategies, and the adjustment of the random error variance. The results suggested that MCFA should be favored when the compared groups were when the different group sizes were paired with the different generalized variances, and MIMIC should be favored when the groups were balanced (i.e., have equal group sizes) in social science and education disciplines. This study also provided the evidence that parceling could improve the power for both MCFA and MIMIC when the factor loadings were low without bringing bias into the solution when the first-order factors were collapsed. However, parceling strategies might not be necessary when the factor loadings were high. The results also indicated that the two approaches were equally favored when domain representative parceling strategy was applied.

The chemistry of the enzyme glutathione peroxidase and synthetic organoselenium enzyme mimics has been a significant research interest for more than three decades. In this work, the results of a computational study employing modern electronic structure methods to model the reactions of a synthetic glutathione peroxidase mimic are presented. The ability of nine density-functional theory methods and thirteen basis sets to predict both molecular geometries and bond dissociation energies in organoselenium compounds is examined. This is used to determine the best methodology to employ for the study of glutathione peroxidase mimics. The key reactions in the catalytic mechanism of the organoselenium antioxidant N,N-dimethyl-benzylamine-2-selenol are the focus of the remainder of the document. This is a three-step mechanism which includes many of the organic forms adopted by selenium compounds, including selenol, oxoacids, and selenylsulfides. In the first step of the cycle, the well-studied reduction of hydrogen peroxide by a selenol and a diselenide is modelled. The second step modelled is a substitution reaction at the selenium centre of a selenenic acid with a thiol. The final step discussed is the reduction of the selenium centre in a selenylsulfide, regenerating the selenol and forming a disulfide species. Each mechanism is evaluated by discussing both molecular geometries and reaction energetics. To close the document, the peroxide reduction reaction is revisited to determine the effects of substitution on the phenyl ring of the synthetic antioxidant. This serves as a preliminary attempt to improve the antioxidant efficiency of this compound. In addition to a discussion of the changes in reaction energetics predicted, the topology of the electron density is studied using the quantum theory of atoms in molecules to better understand how the distribution of electron density is affected by substituents.

In multilevel MIMIC models, covariates at the between level and at the within level can be modeled simultaneously. Covariates interaction effect occurs when the effect of one covariate on the latent factor varies depending on the level of the other covariate. The two covariates can be both at the between level, both at the within level, and one at the between level and the other one at the within level. And they can create between level covariates interaction, within level covariates interaction, and cross level covariates interaction. Study One purports to examine the performance of multilevel MIMIC models in estimating the covariates interaction described above. Type I error of falsely detecting covariates interaction when there is no covariates interaction effect in the population model, and the power of correctly detecting the covariates interaction effect, bias of the estimate of interaction effect, and RMSE are examined. The design factors include the location of the covariates interaction effect, cluster number, cluster size, intra-class correlation (ICC) level, and magnitude of the interaction effect. The results showed that ML MIMIC performed well in detecting the covariates interaction effect when the covariates interaction effect was at the within level or cross level. However, when the covariates interaction effect was at the between level, the performance of ML MIMIC depended on the magnitude of the interaction effect, ICC, and sample size, especially cluster size. In Study Two, the impact of omitting covariates interaction effect on the estimate of other parameters is investigated when the covariates interaction effect is present in the population model. Parameter estimates of factor loadings, intercepts, main effects of the covariates, and residual variances produced by the correct model in Study One are compared to those produced by the misspecified model to check the impact. Moreover, the sensitivity of fit indices, such as chi-square, CFI, RMSEA, SRMR-B (between), and SRM-W (within) are also examined. Results indicated that none of the fit indices was sensitive to the omission of the covariates interaction effect. The biased parameter estimates included the two covariates main effect and the between-level factor mean.