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Title: A comparison of forecasting accuracy of several quantitative forecasting methods : application to lodging sales tax and use tax collections in Michigan
Creator: Kim, Jong Ho
Date: 1994
Collection: Electronic Theses & Dissertations

Title: A computerized sensitivity analysis of selected assumptions in an annual econometric model of the U.S. economy : the electric Klein-Goldberger
Creator: Havenner, Arthur Melvin, 1943-
Date: 1973
Collection: Electronic Theses & Dissertations

Title: A constitutive equation for collagen fibers
Creator: Haut, Roger Carl, 1944-
Date: 1971
Collection: Electronic Theses & Dissertations

Title: A container-attachable inertial sensor for real-time hydration tracking
Creator: Griffith, Henry
Date: 2019
Collection: Electronic Theses & Dissertations
Description: The underconsumption of fluid is associated with multiple adverse health outcomes, including reduced cognitive function, obesity, and cancer. To aid individuals in maintaining adequate hydration, numerous sensing architectures for tracking fluid intake have been proposed. Amongst the various approaches considered, container-attachable inertial sensors offer a non-wearable solution capable of estimating aggregate consumption across multiple drinking containers. The research described herein...
Show moreThe underconsumption of fluid is associated with multiple adverse health outcomes, including reduced cognitive function, obesity, and cancer. To aid individuals in maintaining adequate hydration, numerous sensing architectures for tracking fluid intake have been proposed. Amongst the various approaches considered, container-attachable inertial sensors offer a non-wearable solution capable of estimating aggregate consumption across multiple drinking containers. The research described herein demonstrates techniques for improving the performance of these devices.A novel sip detection algorithm designed to accommodate the variable duration and sparse occurrence of drinking events is presented at the beginning of this dissertation. The proposed technique identifies drinks using a two-stage segmentation and classification framework. Segmentation is performed using a dynamic partitioning algorithm which spots the characteristic inclination pattern of the container during drinking. Candidate drinks are then distinguished from handling activities with similar motion patterns using a support vector machine classifier. The algorithm is demonstrated to improve true positive detection rate from 75.1% to 98.8% versus a benchmark approach employing static segmentation. Multiple strategies for improving drink volume estimation performance are demonstrated in the latter portion of this dissertation. Proposed techniques are verified through a large-scale data collection consisting of 1,908 drinks consumed by 84 individuals over 159 trials. Support vector machine regression models are shown to improve per-drink estimation accuracy versus the prior state-of-the-art for a single inertial sensor, with mean absolute percentage error reduced by 11.1%. Aggregate consumption accuracy is also improved versus previously reported results for a container-attachable device.An approach for computing aggregate consumption using fill level estimates is also demonstrated. Fill level estimates are shown to exhibit superior accuracy with reduced inter-subject variance versus volume models. A heuristic fusion technique for further improving these estimates is also introduced herein. Heuristic fusion is shown to reduce root mean square error versus direct estimates by over 30%. The dissertation concludes by demonstrating the ability of the sensor to operate across multiple containers.
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Title: A cybernetic model of the U.S. defense expenditure policy-making process
Creator: Marra, Robin Frank
Date: 1984
Collection: Electronic Theses & Dissertations

Title: A fictitious domain solver for computation of the effective properties of material distributions generated by iterated affine maps
Creator: Brennan, Edward M.
Date: 2000
Collection: Electronic Theses & Dissertations

Title: A mathematical model for predicting optimal micro-perforated packaging
Creator: Zhang, Jin (Graduate of Michigan State University)
Date: 2015
Collection: Electronic Theses & Dissertations
Description: Micro-perforated packaging has been known to maintain the quality of fresh produceby increasing gas exchange volume through polymer films. Even though by far severalmathematical models have been proposed to predict gas exchange process of micro perforated films, to the best of author's knowledge, there are no statistical methods usedto analyze the models themselves. Therefore, the aim of this research was to employinverse problem technique (ordinary least square, sequential and bootstrap...
Show moreMicro-perforated packaging has been known to maintain the quality of fresh produceby increasing gas exchange volume through polymer films. Even though by far severalmathematical models have been proposed to predict gas exchange process of micro perforated films, to the best of author's knowledge, there are no statistical methods usedto analyze the models themselves. Therefore, the aim of this research was to employinverse problem technique (ordinary least square, sequential and bootstrap methods) tomodel gas exchange process of micro-perforated packaging based on a different approach, and to assess the validity of the prediction. The prediction model involved hydrodynamic flow (minor head loss theory) and diffusion flow (total pressure gradient ≠0). To better predict hydrodynamic flow, the entrance shape of micro perforations was analyzed under SEM. To test the prediction model, experimental data sets were evaluated together with a published data set. The predicted results had high agreement with both data groups, and all the predicted values fell within the asymptotic and bootstrap confidence and prediction bands showing the reliability of the model. Besides, the condition number (cond(J) =1) and bootstrap residual analysis further verified the validity of the model. Due to the slight difference from the reference boundary values, parameters in the model were also accurately estimated by inverse problem technique.
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Title: A novel algorithm of solvation free energy calculation : the KECSA-movable type implicit solvation model (KMTISM)
Creator: Wang, Ting (M.S. in Chemistry)
Date: 2015
Collection: Electronic Theses & Dissertations
Description: A number of theoretical methods have been developed for calculating solvation free energies for biological and chemical processes. In this paper an implicit solvation model, KECSA-Movable Type Implicit Solvation Model (KMTISM) is created by utilizing an energy sampling approach termed the “Movable Type” (MT) method, and a statistical energy function for solvation modeling, “Knowledge-based and Empirical Combined Scoring Algorithm” (KECSA). The solvation free energies can be obtained from the...
Show moreA number of theoretical methods have been developed for calculating solvation free energies for biological and chemical processes. In this paper an implicit solvation model, KECSA-Movable Type Implicit Solvation Model (KMTISM) is created by utilizing an energy sampling approach termed the “Movable Type” (MT) method, and a statistical energy function for solvation modeling, “Knowledge-based and Empirical Combined Scoring Algorithm” (KECSA). The solvation free energies can be obtained from the NVT ensemble partition function generated by the MT method within the implicit solvent model approximation. Several subsets from the Minnesota Solvation Database v2012 are selected to use as validation sets. The solvation free energies getting from KMTISM are compared with several solvation free energy calculation methods, including MM-GBSA and MM-PBSA. Comparison against a quantum mechanics-based polarizable continuum model is also discussed (Cramer and Truhlar’s Solvation Model 12).
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Title: A stochastic multi-scale model of stream-groundwater interaction in strongly heterogeneous porous medium and its application in southern Branch County, Michigan
Creator: Xinyu, Ye
Date: 2014
Collection: Electronic Theses & Dissertations
Description: In this paper, stream depletion is assessed by the approach of multi-scale geostatistics in stressed watershed, South Branch County, Michigan. The watershed is currently under large water demand and representative of the general failure to pass the online Water Withdrawal Assessment Tool. Due to the heterogeneity of porous medium and the high variability of hydrogeological parameters and scale, there is a deviation between field observations and simulated groundwater flow in those areas. The...
Show moreIn this paper, stream depletion is assessed by the approach of multi-scale geostatistics in stressed watershed, South Branch County, Michigan. The watershed is currently under large water demand and representative of the general failure to pass the online Water Withdrawal Assessment Tool. Due to the heterogeneity of porous medium and the high variability of hydrogeological parameters and scale, there is a deviation between field observations and simulated groundwater flow in those areas. The approach of multi-scale geostatistics model based on detailed lithological data and its application in numerical groundwater simulation can be used in stream depletion assessment. Specifically, the multi-scale transition probability geostatistics approach, supplemented with a 10m Digital Elevation Model, allows for a more realistic integration of heterogeneous medium into the development of correlated spatial variability of hydrogeological parameters at each spatial scale. This approach enables accurate simulation of complex hydrogeology, including vertical shift structural variation and aquifer thickness variations. Systematic hydrology models at the regional, local and site scale allows for simulations of integrated water budget analysis. These simulations are necessary to evaluate the water depletions of targeted streams and the surrounded protected area. The hydrology system is calibrated with the steady state water levels from 732 monitoring wells.The stability of transition probability geostatistics model depends on the distributions, the heterogeneity of simulated area and other factors. The results show that transition probability geostatistics model provides a reasonable distribution of materials in aquifer medium, improving numerical groundwater modeling in assessing water depletion in streams and venerable area.
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Title: A theory model : an analysis and integration of the factors and forces influencing curricular decisions
Creator: Coleman, Paul Robert, 1926-
Date: 1974
Collection: Electronic Theses & Dissertations

Title: Ab initio molecular dynamics : applications to defective silicon nanocrystals and developments toward dense manifold systems
Creator: Peng, Wei-Tao
Date: 2019
Collection: Electronic Theses & Dissertations
Description: Ab initio molecular dynamics (AIMD) methods consider the nuclear motions under the potential generated by electronic wavefunctions which are determined from ab initio quantum mechanical calculations on-the-fly. AIMD methods allow researchers to investigate chemical processes without prior knowledge or assumptions about the shape of the potential energy surface (PES). In this thesis, we applied AIMD methods to study silicon nanocrystals with dangling bond defects (DB-SiNCs). DB defects on...
Show moreAb initio molecular dynamics (AIMD) methods consider the nuclear motions under the potential generated by electronic wavefunctions which are determined from ab initio quantum mechanical calculations on-the-fly. AIMD methods allow researchers to investigate chemical processes without prior knowledge or assumptions about the shape of the potential energy surface (PES). In this thesis, we applied AIMD methods to study silicon nanocrystals with dangling bond defects (DB-SiNCs). DB defects on SiNCs have been known as nonradiative (NR) decay centers. However, the atomistic mechanism for the decay process is unclear. Previously, researchers considered a pyramidalization mode surrounding the DB site involved in the process. Based on our AIMD calculations on the first excited state and the static analysis of the PESs of SiNC systems, we discovered that asymmetrical Si-Si bond stretching modes surrounding DB sites are important, in addition to pyramidalization. Most importantly, we found a low-lying defect-induced conical intersection (DICI) in the neutral DB system. The minimum energy conical intersection (MECI) is estimated to be 1.74 eV above the ground state minimum energy geometry by application of multi-state complete active space second-order perturbation theory (MS-CASPT2) to a small cluster model system. In addition, the roles of charged DBs on NR decay process are investigated. We found DICIs for both positively and negatively charged DB systems. The MECI energies are 2.10 eV and 2.65 eV respectively. The rationalization of the existence of conical intersections and detailed dynamics after excitation of these systems are discussed in the thesis. Additionally, to study the possible defect-defect interactions during the NR recombination process, we considered slab models with two DB defects at short (4 0303A) and long (100303 A) separations. According to our simulations, the NR recombination process is localized on a single DB site, regardless the defect-defect distances. However, energy transfer between defect sites with short separations is possible.For the defective SiNC systems, we demonstrated the power of the AIMD method to investigate the dynamics after excitations. However, the applications of AIMD to high-lying states are much more challenging, due to the dense manifold of states that cause immense computational effort. In the thesis, we developed several methods toward the application to such systems. First, we developed a time-dependent configuration interaction (TD-CI) method that can simulate the electron dynamics under a strong field efficiently. The method is based on the direct scheme to form the vector, , which can be accelerated by a graphical processing unit. A TD-CI calculation with 853776 determinants requires only 20.1 hours to propagate to 100 fs with 1 attosecond (10-18 second) time steps. On the other hand, when the field is strong enough, the electrons can be driven to the boundary of the basis set, which would cause unphysical effects such as reflection. To account for this, we developed an analytical expression for a molecule-centered complex absorbing potential which can be evaluated efficiently to remove the unwanted effects. Finally, for the nuclear dynamics, we developed an Ehrenfest dynamics method based on the TD-CI wavefunction. In this approach, the nuclear motions are propagated under the averaged potential generated by TD-CI wave function, thus the approach is promising for application to systems with dense manifolds of states.
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Title: Addition and removal energies via the in-medium similarity renormalization group method
Creator: Yuan, Fei (Software engineer)
Date: 2018
Collection: Electronic Theses & Dissertations
Description: "The in-medium similarity renormalization group (IM-SRG) is an ab initio many-body method suitable for systems with moderate numbers of particles due to its polynomial scaling in computational cost. The formalism is highly flexible and admits a variety of modifications that extend its utility beyond the original goal of computing ground state energies of closed-shell systems. In this work, we present an extension of IM-SRG through quasidegenerate perturbation theory (QDPT) to compute...
Show more"The in-medium similarity renormalization group (IM-SRG) is an ab initio many-body method suitable for systems with moderate numbers of particles due to its polynomial scaling in computational cost. The formalism is highly flexible and admits a variety of modifications that extend its utility beyond the original goal of computing ground state energies of closed-shell systems. In this work, we present an extension of IM-SRG through quasidegenerate perturbation theory (QDPT) to compute addition and removal energies (single particle energies) near the Fermi level at low computational cost. This expands the range of systems that can be studied from closed-shell ones to nearby systems that differ by one particle. The method is applied to circular quantum dot systems and nuclei, and compared against other methods including equations-of-motion (EOM) IM-SRG and EOM coupled-cluster (CC) theory. The results are in good agreement for most cases. As part of this work, we present an open-source implementation of our flexible and easy-to-use J-scheme framework as well as the HF, IM-SRG, and QDPT codes built upon this framework. We include an overview of the overall structure, the implementation details, and strategies for maintaining high code quality and efficiency. Lastly, we also present a graphical application for manipulation of angular momentum coupling coefficients through a diagrammatic notation for angular momenta (Jucys diagrams). The tool enables rapid derivations of equations involving angular momentum coupling - such as in J-scheme - and significantly reduces the risk of human errors."--Page ii.
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Title: Advances in metal ion modeling
Creator: Li, Pengfei (Chemist)
Date: 2016
Collection: Electronic Theses & Dissertations
Description: Metal ions play fundamental roles in geochemistry, biochemistry and materials science.With the tremendous increasing power of the computational resources and largelyinventions of the computational tools, computational chemistry became a more and moreimportant tool to study various chemical processes. Force field modeling strategy, whichis built on physical background, offered a fast way to study chemical systems at atomiclevel. It could offer considerable accuracy when combined with the Monte...
Show moreMetal ions play fundamental roles in geochemistry, biochemistry and materials science.With the tremendous increasing power of the computational resources and largelyinventions of the computational tools, computational chemistry became a more and moreimportant tool to study various chemical processes. Force field modeling strategy, whichis built on physical background, offered a fast way to study chemical systems at atomiclevel. It could offer considerable accuracy when combined with the Monte Carlo orMolecular Dynamics simulation protocol. However, there are various metal ions and it isstill challenging to model them using available force field models. Generally there areseveral models available for modeling metal ions using the force field approach such asthe nonbonded model, the bonded model, the cationic dummy atom model, the combinedmodel, and the polarizable models. Our work concentrated on the nonbonded and bondedmodels, which are widely used nowadays. Firstly, we focused on filling in the blanks ofthis field. We proposed a noble gas curve, which was used to describe the relationshipbetween the van der Waals radius and well depth parameters in the 12-6 Lennard-Jonespotential. By using the noble gas curve and multiple target values (the hydration freeenergy, ion-oxygen distance, coordination number values), we have consistentlyparameterized the 12-6 Lennard-Jones nonbonded model for 63 different ions (including11 monovalent cations, 4 monovalent anions, 24 divalent cations, 18 trivalent cations,and 6 tetravalent cations) combined with three widely used water models (TIP3P, SPC/E, and TIP4PEW). Secondly, we found there is limited accuracy of the 12-6 model, whichmakes it hard to simulate different properties simultaneously for ions with formal chargeequal or larger than +2. By considering the physical origins of the 12-6 model, weproposed a new nonbonded model, named the 12-6-4 LJ-type nonbonded model. Wehave systematically parameterized the 12-6-4 model for 55 different ions (including 11monovalent cations, 4 monovalent anions, 16 divalent cations, 18 trivalent cations, and 6tetravalent cations) in the three water models. It was shown that the 12-6-4 model couldreproduce several properties at the same time, showing remarkable improvement over the12-6 model. Meanwhile, through the usage of a proposed combining rule, the 12-6-4model showed excellent transferability to mixed systems. Thirdly, we have developed theMCPB.py program to facilitate building of the bonded model for metal ion containingsystems, which can largely reduce human efforts. Finally, an application case of ametallochaperone - CusF was shown, and based on the simulations we hypothesized anion transfer mechanism.
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Title: An analysis of the risk and risk reduction of influenza virus infection through use of antimicrobial products
Creator: Chabrelie, Alexandre
Date: 2019
Collection: Electronic Theses & Dissertations
Description: Influenza is a pathogen of major concern, causing up to 79,000 deaths, 960,000 hospitalizations, and 49 million people sick per year in the US. One of the major route of transmission for influenza is by expelling viruses from coughing/sneezing onto surfaces, followed by transfer of viruses from surfaces to hands, and subsequently to facial mucous membranes.Therefore, routine cleaning and disinfection of surfaces is an important part of the environmental management of influenza A. While the...
Show moreInfluenza is a pathogen of major concern, causing up to 79,000 deaths, 960,000 hospitalizations, and 49 million people sick per year in the US. One of the major route of transmission for influenza is by expelling viruses from coughing/sneezing onto surfaces, followed by transfer of viruses from surfaces to hands, and subsequently to facial mucous membranes.Therefore, routine cleaning and disinfection of surfaces is an important part of the environmental management of influenza A. While the emphasis is generally on spraying hard surfaces and laundering cloth and linens with high temperature machine drying, not all surfaces can be treated in this manner. The quantitative microbial risk assessment (QMRA) approach was used to develop a stochastic risk model for estimating the risk of infection from indirect contact with porous surfaces, with and without surface pre-treatment with an antimicrobial spray product. The data collected from laboratory combined with the risk model show that the risk of influenza A infection can be lowered by four logs when using an antimicrobial spray on a porous surface. Median risk associated with a single touch to a contaminated fabric was estimated to be 1.25 x10-4 for the untreated surface, and 3.6 x10-8 for the treated surface. This single touch scenario was used to develop a generalizable model, allowing to estimate risks by comparing different cases related to more realistic 15 to 30 minutes exposure scenarios associated with multiple surface/face touches. The results of this study demonstrate the effective risk reduction associated with treating porous surfaces that cannot be laundered at high temperatures.
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Title: Analysis and design of resonant frequency control systems with applications
Creator: Smith, Daniel
Date: 2007
Collection: Electronic Theses & Dissertations

Title: Analysis of cooperative transcription factor binding at the sequence level
Creator: Clifford, Jacob
Date: 2015
Collection: Electronic Theses & Dissertations
Description: Transcription Factor binding to DNA binding sites is one of the primary causes of generegulation. A common representation of transcription factor binding sites is at the DNAsequence level, partly due to reoccurring patterns at the sequence level that occur throughoutthe genome for a given factor. The first chapter of this dissertation introduces gene regulationfrom the perspective of development. In addition the mathematical-physics foundation forperforming calculations and for...
Show moreTranscription Factor binding to DNA binding sites is one of the primary causes of generegulation. A common representation of transcription factor binding sites is at the DNAsequence level, partly due to reoccurring patterns at the sequence level that occur throughoutthe genome for a given factor. The first chapter of this dissertation introduces gene regulationfrom the perspective of development. In addition the mathematical-physics foundation forperforming calculations and for representations of the transcription factor binding sites atthe sequence level is discussed in Chapter 1. In Chapter 2 I explore the possibility thattwo distinct sub-types of binding sites may co-exist within a population of functional sites.This leads to a model that can be used for prediction of transcription factor binding sites.In Chapter 3 I explore modelling of Dorsal Ventral early development Gene RegulatoryNetwork, using the tools built up in Chapter 1 and 2, namely 'Position Weight Matrices'that allow for prediction of binding energies for genomic segments of DNA.
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Title: Analyzing economic multipliers for the wood products industry
Creator: Beckley, Paul R.
Date: 2002
Collection: Electronic Theses & Dissertations

Title: Brain connectivity analysis using information theory and statistical signal processing
Creator: Wang, Zhe (Software engineer)
Date: 2017
Collection: Electronic Theses & Dissertations
Description: Connectivity between different brain regions generates our minds. Existing work on brain network analysis has mainly been focused on the characterization of connections between the regions in terms of connectivity and causality. Connectivity measures the dependence between regional brain activities, and causality analysis aims to determine the directionality of information flow among the functionally connected brain regions, and find the relationship between causes and effects.Traditionally,...
Show moreConnectivity between different brain regions generates our minds. Existing work on brain network analysis has mainly been focused on the characterization of connections between the regions in terms of connectivity and causality. Connectivity measures the dependence between regional brain activities, and causality analysis aims to determine the directionality of information flow among the functionally connected brain regions, and find the relationship between causes and effects.Traditionally, the study on connectivity and causality has largely been limited to linear relationships. In this dissertation, as an effort to achieve more accurate characterization of connections between brain regions, we aim to go beyond the linear model, and develop innovative techniques for both non-directional and directional connectivity analysis. Note that due to variability in the brain connectivity of each individual, the connectivity between two brain regions alone may not be sufficient for brain function analysis, in this research, we also conduct network connectivity pattern analysis, so as to reveal more in-depth information.First, we characterize non-directional connectivity using mutual information (MI). In recent years, MI has gradually appeared as an alternative metric for brain connectivity, since it measures both linear and non-linear dependence between two brain regions, while the traditional Pearson correlation only measures the linear dependence. We develop an innovative approach to estimate the MI between two functionally connected brain regions and apply it to brain functional magnetic resonance imaging (fMRI) data. It is shown that: on average, cognitively normal subjects show larger mutual information between critical regions than Alzheimer's disease (AD) patients.Second, we develop new methodologies for brain causality analysis based on directed information (DI). Traditionally, brain causality is based on the well-known Granger Causality (GC) analysis. The validity of GC has been widely recognized. However, it has also been noticed that GC relies heavily on the linear prediction method. When there exists strong nonlinear interactions between two regions, GC analysis may lead to invalid results. In this research, (i) we develop an innovative framework for causality analysis based on directed information (DI), which reflects the information flow from one region to another, and has no modeling constraints on the data. It is shown that DI based causality analysis is effective in capturing both linear and non-linear causal relationships. (ii) We show the conditional equivalence between the DI Framework and Friston's dynamic causal modeling (DCM), and reveal the relationship between directional information transfer and cognitive state change within the brain. Finally, based on brain network connectivity pattern analysis, we develop a robust method for the AD, mild cognitive impairment (MCI) and normal control (NC) subject classification under size limited fMRI data samples. First, we calculate the Pearson correlation coefficients between all possible ROI pairs in the selected sub-network and use them to form a feature vector for each subject. Second, we develop a regularized linear discriminant analysis (LDA) approach to reduce the noise effect. The feature vectors are then projected onto a subspace using the proposed regularized LDA, where the differences between AD, MCI and NC subjects are maximized. Finally, a multi-class AdaBoost Classifier is applied to carry out the classification task. Numerical analysis demonstrates that the combination of regularized LDA and the AdaBoost classifier can increase the classification accuracy significantly.
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Title: Case studies of high school students using physical models to study mathematical systems
Creator: Burke, Gerald Clayton, 1932-
Date: 1973
Collection: Electronic Theses & Dissertations

Title: Changing hearts and minds : imagined intergroup contact's effect on warmth and competence stereotypes
Creator: O'Connor, Rachel C.
Date: 2015
Collection: Electronic Theses & Dissertations
Description: Imagined intergroup contact was introduced as an easy and efficient method of improving the quality of intergroup interactions allowing better prejudice reduction. It has proven effective at improving many intergroup outcomes, however some previous research points to limitations of the method and suggest that perhaps imagined intergroup contact is more effective at reducing certain types of prejudice than others. The Stereotype Content Model posits distinct types of prejudice directed at...
Show moreImagined intergroup contact was introduced as an easy and efficient method of improving the quality of intergroup interactions allowing better prejudice reduction. It has proven effective at improving many intergroup outcomes, however some previous research points to limitations of the method and suggest that perhaps imagined intergroup contact is more effective at reducing certain types of prejudice than others. The Stereotype Content Model posits distinct types of prejudice directed at different social groups based on perceptions of the group members’ warmth and competence. In the current study, I sought to investigate whether imagined intergroup contact works equally well for groups that experience different types of prejudice based on their differences on the dimensions of warmth and competence. Additionally, I examined the duration of the effects of intergroup contact by comparing outcomes both immediately after and one week later. Results indicated that imagined intergroup contact was not successful at creating more positive stereotype perceptions for any groups, regardless of their previous standing on warmth and competence. Unsurprisingly, patterns for intergroup emotions and behavioral tendencies predicated on these stereotype differences were not observed either. However, select behavioral tendencies were higher following imagined interactions with some social groups, indicating that part of intergroup contact’s influence on behavior is independent of its influence on stereotypes and emotions. Furthermore, many intergroup outcomes deteriorated over the period of a week, especially in the control condition. Results are discussed in terms of their implications for the theories of both imagined intergroup contact and the Stereotype Content Model.
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