Infinity and Beyond

This paper attempts to explore the concept of infinity regarding the nature of God, by responding to several criticisms regarding the concept of an infinite being. Andrew Lavin, in his article The Theological use of Infinity explains that the concept of an infinite God is inconsistent, and suggests that a finite God would be more conceivable. This paper analyzes each of Lavin\u27s objections and his reasoning behind them as well as his understanding of the concept of infinity in itself

National Collaborative Research on How Students Learn Integration: Final Report

A relational attachment model of how students learn integration at Rosemead and Fuller was replicated with clinical psychology doctoral students at George Fox University and Wheaton College (Illinois). Struc- tural equation modeling of multitrait-multimethod matrices tested how well faculty members could recognize what students readily identify in professors as most useful to students’ integration, and Latent Semantic Anal- ysis interpreted what students found most important

Graduate Students\u27 Perceptions of Formative Faculty Characteristics: A Look At What Facilitates Integrative Development in a Christian Psychology Program

Little has been done to assess how students learn integration except by grading them on how well they memorize and echo back their professors\u27 views. The present study sought to ask students what they find helpful from professors, rather than presuming that faculty already know what is best. Following the research protocol of Sorenson (1995), the present study measured graduate students\u27 perceptions of what faculty characteristics are helpful in their integrative pursuit at George Fox College\u27s Graduate School of Clinical Psychology. This research sought to (a) determine if students at George Fox College employ particular latent dimensions for evaluating faculty on integration, (b) identify faculty characteristics students at George Fox perceive as formative for integrative development, and (c) replicate Sorenson\u27s (1995) findings from Rosemead School of Psychology with George Fox College to see if any results are generalizable across these different populations. Forty-eight clinical psychology doctoral students rated the perceived similarity of all faculty. Students\u27 card sorts of faculty members were analyzed using multidimensional scaling to measure students\u27 perceptions of similarities and dissimilarities of faculty members. Three dimensions were identified using multidimensional scaling. The resulting dimensions were correlated with a pooled dependent variable on how helpful and exemplary in integration various faculty members were for students-from the students\u27 point of view. The dimensions were interpreted via canonical correlation with criterion variables. Results suggest that graduate students at George Fox College do tacitly evaluate faculty along two latent dimensions in ways that relate to integration ( sense of humor and personal spirituality ), and that these dimensions are similar to those from Rosemead School of Psychology. Implications of these findings are that (a) integrative programs select faculty with relationship and mentoring skills, (b) members of faculty give evidence of a personal relationship with God, and ( c) faculty development encourage personal spiritual growth and foster personal contact

Modern coatings in high performance cutting applications

Modern, state-of-the-art, PVD coatings are required to fulfill a variety of different applications. Each metal cutting operation requires an optimal combination of various film parameters to achieve a high end cutting performance. Especially, Al-based coatings such as AlTiN- and AlCrN-coatings show very good results in high performance metal cutting applications. Wear resistance, thermal stability such as oxidation resistance and hardness at elevated temperatures are key issues within these cutting operations. In this paper the influence of these properties on Al-based nitride coatings in relation to metal cutting tests such as milling and drilling will be discussed

Importance Sampling and Stratification for Copula Models

An importance sampling approach for sampling from copula models is introduced. The proposed algorithm improves Monte Carlo estimators when the functional of interest depends mainly on the behaviour of the underlying random vector when at least one of its components is large. Such problems often arise from dependence models in finance and insurance. The importance sampling framework we propose is particularly easy to implement for Archimedean copulas. We also show how the proposal distribution of our algorithm can be optimized by making a connection with stratified sampling. In a case study inspired by a typical insurance application, we obtain variance reduction factors sometimes larger than 1000 in comparison to standard Monte Carlo estimators when both importance sampling and quasi-Monte Carlo methods are used.NSERC, Grant 238959 NSERC, Grant 501

Interpretation of Brain Morphology in Association to Alzheimer's Disease Dementia Classification Using Graph Convolutional Networks on Triangulated Meshes

We propose a mesh-based technique to aid in the classification of Alzheimer's disease dementia (ADD) using mesh representations of the cortex and subcortical structures. Deep learning methods for classification tasks that utilize structural neuroimaging often require extensive learning parameters to optimize. Frequently, these approaches for automated medical diagnosis also lack visual interpretability for areas in the brain involved in making a diagnosis. This work: (a) analyzes brain shape using surface information of the cortex and subcortical structures, (b) proposes a residual learning framework for state-of-the-art graph convolutional networks which offer a significant reduction in learnable parameters, and (c) offers visual interpretability of the network via class-specific gradient information that localizes important regions of interest in our inputs. With our proposed method leveraging the use of cortical and subcortical surface information, we outperform other machine learning methods with a 96.35% testing accuracy for the ADD vs. healthy control problem. We confirm the validity of our model by observing its performance in a 25-trial Monte Carlo cross-validation. The generated visualization maps in our study show correspondences with current knowledge regarding the structural localization of pathological changes in the brain associated to dementia of the Alzheimer's type.Comment: Accepted for the Shape in Medical Imaging (ShapeMI) workshop at MICCAI International Conference 202

NABS: non-local automatic brain hemisphere segmentation

"NOTICE: this is the author’s version of a work that was accepted for publication in Magnetic Resonance Imaging. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Magnetic Resonance Imaging, [Volume 33, Issue 4, May 2015, Pages 474–484] DOI 10.1016/j.mri.2015.02.005In this paper, we propose an automatic method to segment the five main brain sub-regions (i.e. left/right hemispheres, left/right cerebellum and brainstem) from magnetic resonance images. The proposed method uses a library of pre-labeled brain images in a stereotactic space in combination with a non-local label fusion scheme for segmentation. The main novelty of the proposed method is the use of a multi-label block-wise label fusion strategy specifically designed to deal with the classification of main brain sub-volumes that process only specific parts of the brain images significantly reducing the computational burden. The proposed method has been quantitatively evaluated against manual segmentations. The evaluation showed that the proposed method was faster while producing more accurate segmentations than a current state-of-the-art method. We also present evidences suggesting that the proposed method was more robust against brain pathologies than the compared method. Finally, we demonstrate the clinical value of our method compared to the state-of-the-art approach in terms of the asymmetry quantification in Alzheimer's disease.We want to thank the OASIS (P50 AG05681, P01 AG03991, R01 AG021910, P50 MH071616, U24 RR021382, R01 MH56584) and IXI - Information eXtraction from Images (EPSRC GR/S21533/02) datasets promoters for making available this valuable resource to the scientific community which surely will boost the research in brain imaging. This work has been supported by the Spanish grant TIN2011-26727 from Ministerio de Ciencia e Innovacion. J. Tohka's work was supported by the Academy of Finland grant 130275. This study has been carried out with financial support from the French State, managed by the French National Research Agency (ANR) in the frame of the Investments for the Future Programme IdEx Bordeaux (ANR-10-IDEX-03-02), Cluster of Excellence CPU and TRAIL (HR-DTI ANR-10-LABX-57).Romero Gómez, JE.; Manjón Herrera, JV.; Tohka, J.; Coupé, P.; Robles Viejo, M. (2015). NABS: non-local automatic brain hemisphere segmentation. Magnetic Resonance Imaging. 33(4):474-484. https://doi.org/10.1016/j.mri.2015.02.005S47448433