1,909 research outputs found
Talking with Symbols
Discusses a classroom of seven children with cerebral palsy and the effective communication techniques they learned through the language of symbols
Robust FDI Determinants: Bayesian Model Averaging In The Presence Of Selection Bias
The literature on Foreign Direct Investment (FDI) determinants is remarkably diverse in terms of competing theories and empirical results. We utilize Bayesian Model Averaging (BMA) to resolve the model uncertainty that surrounds the validity of the competing FDI theories. Since the structure of existing FDI data is known to induce selection bias, we extend BMA theory to HeckitBMA to address model uncertainty in the presence of selection bias. We then show that more than half of the previously suggested FDI determinants are no longer robust and highlight theories that receive support from the data. In addition, our selection approach allows us to highlight that the determinants of margins of FDI (intensive and extensive) differ profoundly in the data, while FDI theories do not usually model this aspect explicitly.
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Machine-Learning Aided Diagnosis of Alzheimer's Disease
Alzheimer’s disease is a neurodegenerative disorder characterized by the accumulation of amyloid-beta proteins in the brain, leading to loss of neuronal function and eventual death. Though the incidence of Alzheimer’s has risen in recent years, in no small part due to increasing lifespans, there has been little progress in the diagnosis and prevention of the disease. Diagnosis premortem is possible, but mainly through costly imaging or invasive brain biopsies, the latter of which is not recommended due to the possibility of further brain damage in the AD patient. Furthermore, AD treatments are difficult to study due to the difficulty of identifying patients as well as the diseases’ stubborn progression. Thus, there is an area of opportunity in accurately identifying these patients for both diagnostic and therapeutic purposes. There are many biomarkers correlated with the presence of AD, whether that be noticeable brain damage via scanning, the biomarkers of neuron cell death, or latent biomarkers which may cooccur in the progression of the disease. Given that these are non-linear relationships, computer-aided diagnosis may help in elucidating the diagnosis of AD. Random Forest models, given their ability to generate human-understandable trees and decision surfaces, are primed to assist medical professionals with the diagnosis of AD. This thesis analyzes several such models and evaluates their accuracies, as well as providing an overview of the state of the computer-aided medical diagnostics field.Chemical Engineerin
Henri Temianka Correspondence; (helfman)
This collection contains material pertaining to the life, career, and activities of Henri Temianka, violin virtuoso, conductor, music teacher, and author. Materials include correspondence, concert programs and flyers, music scores, photographs, and books.https://digitalcommons.chapman.edu/temianka_correspondence/3591/thumbnail.jp
Transatlantic Influences on American Corporate Jurisprudence: Theorizing the Corporation in the United States
In interpreting and evaluating the history of the Supreme Court\u27s corporate jurisprudence, legal scholars have deployed three broad theories of corporate legal personality: the aggregate entity theory, the artificial entity theory, and the real entity theory. While these theories are powerful ways of conceptualizing the corporation, this article shows that they have not been as central to the Supreme Court\u27s corporate jurisprudence as recent scholarship suggests. It instead argues that historic transformations in the high court\u27s corporate jurisprudence are best understood in light of contemporary intellectual currents rather than through an expost facto application of the aggregate, artificial, and real entity theories. This article revisits the Supreme Court\u27s early corporate jurisprudence, focusing on the Court\u27s reception of English and continental theories of corporation during the antebellum period. It argues that the Marshall Court\u27s approach to corporate legal personality was deeply reliant on early modern English precedents, which were preoccupied with the nature of the corporation as a locus of political authority bounded by constitutional constraints. It further suggests that the Taney Court\u27s transformative decision in Louisville, Cincinnati & Charleston Railroad v. Letson (1844)-that a corporation is a citizen of the United States-was directly influenced by the writings of the German jurist Friedrich von Savigny. Here, the article bridges a significant gap in the history of American legal thought by illustrating the role that Attorney General Hugh Legaré played in presenting to the court a compelling and novel synthesis of English precedent and contemporary continental theory. The article concludes by considering the long shadow these rulings have cast on recent Supreme Court decisions regarding the rights of corporations as citizens of the United States
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