Welcome to the UA Campus Repository, a service of the University of Arizona Libraries. The repository shares, archives and preserves unique digital materials from faculty, staff, students and affiliated contributors. Contact us at email@example.com with any questions.
- Dissertations from the Indigenous Peoples Law and Policy Program are now available in the repository.
- The latest volume of Desert Plants, a special issue called Thirty-Seven Years on a Mountain Trail: Vascular Flora and Flowering Phenology of the Finger Rock Canyon Watershed, Santa Catalina Mountains, Arizona.
- New geologic maps and data from the Arizona Geological Survey Document Repository.
- A report on the Research Practices of Indigenous Studies Scholars at the University of Arizona.
- Honors College Theses from Fall 2018 graduates.
- Proceedings from the 2018 Critical Librarianship and Pedagogy Symposium.
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Improved spectral comparisons of paleoclimate models and observations via proxy system modeling: Implications for multi-decadal variability(ELSEVIER SCIENCE BV, 2017-10-15)The spectral characteristics of paleoclimate observations spanning the last millennium suggest the presence of significant low-frequency (multi-decadal to centennial scale) variability in the climate system. Since this low-frequency climate variability is critical for climate predictions on societally-relevant scales, it is essential to establish whether General Circulation models (GCMs) are able to simulate it faithfully. Recent studies find large discrepancies between models and paleoclimate data at low frequencies, prompting concerns surrounding the ability of GCMs to predict long-term, high-magnitude variability under greenhouse forcing (Laepple and Huybers, 2014a, 2014b). However, efforts to ground climate model simulations directly in paleoclimate observations are impeded by fundamental differences between models and the proxy data: proxy systems often record a multivariate and/or nonlinear response to climate, precluding a direct comparison to GCM output. In this paper we bridge this gap via a forward proxy modeling approach, coupled to an isotope-enabled GCM. This allows us to disentangle the various contributions to signals embedded in ice cores, speleothem calcite, coral aragonite, tree-ring width, and tree-ring cellulose. The paper addresses the following questions: (1) do forward-modeled “pseudoproxies” exhibit variability comparable to proxy data? (2) if not, which processes alter the shape of the spectrum of simulated climate variability, and are these processes broadly distinguishable from climate? We apply our method to representative case studies, and broaden these insights with an analysis of the PAGES2k database (PAGES2K Consortium, 2013). We find that current proxy system models (PSMs) can help resolve model-data discrepancies on interannual to decadal timescales, but cannot account for the mismatch in variance on multi-decadal to centennial timescales. We conclude that, specific to this set of PSMs and isotope-enabled model, the paleoclimate record may exhibit larger low-frequency variability than GCMs currently simulate, indicative of incomplete physics and/or forcings.
Diagnosing Abnormal Electrocardiogram (ECG) via Deep Learning(INTECHOPEN, 2019-04-03)In this chapter, we investigate the most recent automatic detecting algorithms on abnormal electrocardiogram (ECG) in a variety of cardiac arrhythmias. We present typical examples of a medical case study and technical applications related to diagnosing ECG, which include (i) a recently patented data classifier on the basis of deep learning model, (ii) a deep neural network scheme to diagnose variable types of arrhythmia through wearable ECG monitoring devices, and (iii) implementation of the health cloud platform, which consists of automatic detection, data mining, and classifying via the Android terminal module. Our work establishes a cross-area study, which relates artificial intelligence (AI), deep learning, cloud computing on huge amount of data to minishape ECG monitoring devices, and portable interaction platforms. Experimental results display the technical advantages such as saving cost, better reliability, and higher accuracy of deep learning-based models in contrast to conventional schemes on cardiac diagnosis.
Dental evidence for wild tuber processing among Titicaca Basin foragers 7000 ybp(Wiley, 2017-09)Objectives: The objective of this work is to characterize dental wear in a skeletal sample dating to the Middle/Late Archaic period transition (8,000-6,700 cal. B.P.) from the Lake Titicaca Basin, Peru to better define subsistence behaviors of foragers prior to incipient sedentism and food production. Materials and Methods: The dental sample consists of 251 teeth from 11 individuals recovered from the site of Soro Mik'aya Patjxa (SMP), the earliest securely dated burial assemblage in the Lake Titicaca Basin and the only burial assemblage in the region from an unequivocal forager context. Occlusal surface wear was quantified according to Smith (1984) and Scott (1979a) to characterize diversity within the site and to facilitate comparison with other foraging groups worldwide. General linear modeling was used to assess observation error and principal axis analysis was used to compare molar wear rates and angles. Teeth were also examined for caries and specialized wear. Results: Occlusal surface attrition is generally heavy across the dental arcade and tends to be flat among posterior teeth. Only one carious lesion was observed. Five of the 11 individuals exhibit lingual surface attrition of the maxillary anterior teeth (LSAMAT). Discussion: Tooth wear rates, molar wear plane, and caries rates are consistent with terrestrial foraging and a diverse diet. The presence of LSAMAT indicates tuber processing. The results therefore contribute critical new data toward our understanding of forager diet in the Altiplano prior to plant and animal domestication in the south-central Andes.
Assessing the national trends in colon cancer among Native Americans: A 12 year SEER database study(EXCERPTA MEDICA INC-ELSEVIER SCIENCE INC, 2017-08-01)Introduction: Native Americans (NA) form a unique cohort of colon cancer (CC) patients among whom the variability in demographics and cancer characteristics remains unclear. Methods: We abstracted the national estimates for NA with CC using the Surveillance, Epidemiology, and End Result (SEER) database. Trend analysis of incidence, variation in location and patient demographic analysis were performed. Results: A total number of 26,674 NA with CC were reported during the 12-year study period. While the overall incidence of CC decreased by 12% during the study period, incidence increased by 38% in NA. Incidence of CC was more prevalent and higher increase (42%) seen in NA females than males (p = 0.02; 34%). Stage III tumors represented 29% of all CC, sigmoid colon the most common site location (38%) with 72% of all tumors being moderately differentiated. 55% tumors were localized in left, 36% in right and 9% in transverse colon. 92% of the NA were insured. Conclusion: Incidence of CC continues to rise in NA with majority of CC presented at higher stage and moderate differentiation. Published by Elsevier Inc.
Differential susceptibility of human peripheral blood T cells to suppression by environmental levels of sodium arsenite and monomethylarsonous acid(PUBLIC LIBRARY SCIENCE, 2014-10-01)Human exposure to arsenic in drinking water is known to contribute to many different health outcomes such as cancer, diabetes, and cardiopulmonary disease. Several epidemiological studies suggest that T cell function is also altered by drinking water arsenic exposure. However, it is unclear how individual responses differ to various levels of exposure to arsenic. Our laboratory has recently identified differential responses of human peripheral blood mononuclear cell (HPMBC) T cells as measured by polyclonal T cell activation by mitogens during sodium arsenite exposure. T cells from certain healthy individuals exposed to various concentrations (1–100 nM) of arsenite in vitro showed a dose-dependent suppression at these extremely low concentrations (∼0.1–10 ppb) of arsenite, whereas other individuals were not suppressed at low concentrations. In a series of more than 30 normal donors, two individuals were found to be sensitive to low concentration (10 nM equivalent ∼1 ppb drinking water exposure) to sodium arsenite-induced inhibition of T cell proliferation produced by phytohemagglutinin (PHA) and anti-CD3/anti-CD28. In an arsenite-susceptible individual, arsenite suppressed the activation of Th1 (Tbet) cells, and decreased the percentage of cells in the double positive Th17 (RORγt) and Treg (FoxP3) population. While the majority of normal blood donors tested were not susceptible to inhibition of proliferation at the 1–100 nM concentrations of As+3, it was found that all donors were sensitive to suppression by 100 nM monomethylarsonous acid (MMA+3), a key metabolite of arsenite. Thus, our studies demonstrate for the first time that low ppb-equivalent concentrations of As+3 are immunosuppressive to HPBMC T cells in some individuals, but that most donor HPBMC are sensitive to suppression by MMA+3 at environmentally relevant exposure levels.