114 research outputs found
An introduction to project N
The thesis is a theoretical introduction and technical documentation of my ongoing project, “N”.
N is a themed collection of both textual writings and visual artworks. Divided into three chapters, Nothingness, Ubiquitous and Enigma, N draws upon diverse content from science, philosophy, psychology, theology, anthropology and literature. N seeks potential correlations between drastically different paradigms and fields. On a broader scale, N serves as an incentive to creative thinkers to initiate conversations between long isolated and self-privileged disciplines, mediating between them to collaboratively generate new insights into our fundamental questions.
The thesis covers the personal and theoretical backgrounds of N, the symbolic arrangements of its content, its post-structuralist style of writing and the metaphorical implications of its artistic praxis. The thesis also contains fragmented texts excerpted from N, as well as detailed descriptions of some selected artworks
ANALYSIS OF INNOVATIVE TEACHING REFORM OF ACCOUNTING EDUCATION IN COLLEGES AND UNIVERSITIES FROM THE PERSPECTIVE OF EDUCATIONAL PSYCHOLOGY
RESEARCH ON COLLEGE ENGLISH TRANSLATION TEACHING THEORY AND TRANSLATION SKILLS FROM THE PERSPECTIVE OF EDUCATIONAL PSYCHOLOGY
RESEARCH ON COLLEGE ENGLISH TRANSLATION TEACHING THEORY AND TRANSLATION SKILLS FROM THE PERSPECTIVE OF EDUCATIONAL PSYCHOLOGY
ANALYSIS OF INNOVATIVE TEACHING REFORM OF ACCOUNTING EDUCATION IN COLLEGES AND UNIVERSITIES FROM THE PERSPECTIVE OF EDUCATIONAL PSYCHOLOGY
The Effects of Lead Exposure at Different Stages of Life on Neurobehavioral and Metabolic Outcomes.
Lead exposure remains an enormous public health problem worldwide. In this dissertation, I investigated the effect of exposure to lead in terms of windows of exposures. With the methodological advantages of longitudinal study designs and the use of biomarkers for cumulative as well as short-term lead exposures, I aimed to establish the relationship between timing of exposure to lead and a variety of health outcomes.
In the first project, I investigated the timing of perinatal and early childhood exposure to lead in relation to the psychobehavioral development in children aged from 6 to 13 years. The results did not show statistically significant associations between lead exposures in early life and the majority of behavioral outcomes. However, the findings suggested that exposure to lead in utero and during the first two years of life have strong impacts on inattention and hyperactivity behaviors in children.
The goal of the second project was to understand the potential impact of lifetime exposure to lead on Parkinson’s disease development in subjects with genetic polymorphisms of the SNCA gene. Three loci were found strongly predicted Parkinson’s disease. Lead increased the odds of PD only among subjects who were genetically relatively resistant to the disease. This result implies that lead exposure and genetic predisposition in SNCA gene does not have a synergistic effect on PD development.
The last project aimed to discover the relationship between lifetime lead exposure and risk of type 2 diabetes. It provided novel evidence that exposure to lead could result in type 2 diabetes. A significant finding was observed that increase in patella bone lead level was associated with higher risk of type 2 diabetes. A discrepancy between tibia lead and patella lead effects on development of type 2 diabetes was also observed. Our findings suggested that cumulative exposure to lead increases the risk of DM2 with a ceiling effect.
The studies in this thesis provide a landscape of lead effects on human health across the life span with consideration of the timing of the exposures, and interactions with genetic vulnerabilities.PHDEnvironmental Health SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/97980/1/syhuang_1.pd
Stabilization and current-induced motion of antiskyrmion in the presence of anisotropic Dzyaloshinskii-Moriya interaction
Topological defects in magnetism have attracted great attention due to
fundamental research interests and potential novel spintronics applications.
Rich examples of topological defects can be found in nanoscale non-uniform spin
textures, such as monopoles, domain walls, vortices, and skyrmions. Recently,
skyrmions stabilized by the Dzyaloshinskii-Moriya interaction have been studied
extensively. However, the stabilization of antiskyrmions is less
straightforward. Here, using numerical simulations we demonstrate that
antiskyrmions can be a stable spin configuration in the presence of anisotropic
Dzyaloshinskii-Moriya interaction. We find current-driven antiskyrmion motion
that has a transverse component, namely antiskyrmion Hall effect. The
antiskyrmion gyroconstant is opposite to that for skyrmion, which allows the
current-driven propagation of coupled skyrmion-antiskyrmion pairs without
apparent skyrmion Hall effect. The antiskyrmion Hall angle strongly depends on
the current direction, and a zero antiskyrmion Hall angle can be achieved at a
critic current direction. These results open up possibilities to tailor the
spin topology in nanoscale magnetism, which may be useful in the emerging field
of skyrmionics.Comment: 31 pages, 6 figures, to appear in Physical Review
Dimensionality's blessing: Clustering images by underlying distribution
Many high dimensional vector distances tend to a constant. This is typically
considered a negative "contrast-loss" phenomenon that hinders clustering and
other machine learning techniques. We reinterpret "contrast-loss" as a
blessing. Re-deriving "contrast-loss" using the law of large numbers, we show
it results in a distribution's instances concentrating on a thin "hyper-shell".
The hollow center means apparently chaotically overlapping distributions are
actually intrinsically separable. We use this to develop
distribution-clustering, an elegant algorithm for grouping of data points by
their (unknown) underlying distribution. Distribution-clustering, creates
notably clean clusters from raw unlabeled data, estimates the number of
clusters for itself and is inherently robust to "outliers" which form their own
clusters. This enables trawling for patterns in unorganized data and may be the
key to enabling machine intelligence.Comment: Accepted in CVPR 201
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