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Open Access Publications from the University of California

Scholarly Works (485 results)

  • Article
  • Peer Reviewed
Lawrence Berkeley National Laboratory (2013)
    Cover page: Probabilistic analysis of fracture reactivation associated with deep underground CO2 injection
    • Article
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    UC San Diego Previously Published Works (2018)
    The following article deals with the role of compressibility in regularizing the well-known μ(I) model, i.e., eliminating the short-wavelength (Hadamard) instability revealed by Barker et al. [“Well-posed and ill-posed behaviour of the μ(I)-rheology for granular flow,” J. Fluid Mech. 779, 794–818 (2015)]. In particular, we discuss the compressible-flow models proposed in the recent papers by Heyman et al. [“Compressibility regularizes the μ(I)-rheology for dense granular flows,” J. Fluid Mech. 830, 553–568 (2017)] and Barker et al. [“Well-posed continuum equations for granular flow with compressibility and μ(I)-rheology,” Proc. R. Soc. A 473(2201), 20160846 (2017)]. In addition to a critique of certain aspects of their proposed constitutive models, we show that the main effect of their regularizations is to add viscous effects to the shear response in a way that appears unfortunately to eliminate quasi-static yield stress. Another goal of the present work is to show how the development and analysis of visco-plastic constitutive relations are facilitated by dissipation potentials and the dissipative analog of elastic potentials. We illustrate their utility in Sec. IV of this article, where it is shown that a constant non-zero yield stress leads to loss of convexity that can only be restored by substituting viscous effects or else by adding spatial-gradient effects proposed previously by the present authors [Goddard, J. and Lee, J., “On the stability of the μ(I) rheology for granular flow,” J. Fluid Mech. 833, 302–331 (2017)].
      Cover page: Regularization by compressibility of the μ(I) model of dense granular flow
      • Article
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      UCLA Previously Published Works (2016)
        Cover page: Earnings and employment benefits of adult higher education in comparative perspective: evidence based on the OECD Survey of Adult Skills (PIAAC)
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        International Organization of Citrus Virologists Conference Proceedings (1957-2010), Volume 11, Issue 11 (1991)
          Cover page: An Evaluation of Types of Citrus Tristeza Virus in Selected Sweet Orange Groves in Southern California
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          • Peer Reviewed
          Technology Innovations in Statistics Education, Volume 3, Issue 2 (2009)

          In this paper we provide a glimpse of the iterations of design, research and theorizing of a probability simulation tool, Probability Explorer, that have occurred over the past decade. We provide a brief description of the key features of the technology designed to allow young students opportunities to explore probabilistic situations. This is followed by details about several research observations made in multiple investigations of student explorations with this probability micro-world software package. We then explicate how research results suggest that a focus on a bidirectional interplay between theoretical distribution and empirical data can promote reasoning about probabilistic phenomena, and offer implications for instruction. The paper concludes with a discussion of a next generation innovation in the software for representing a theoretical distribution that we believe may promote better students reasoning about the bidirectional connection between theoretical distributions and empirical data.

            Cover page: Reasoning about Probabilistic Phenomena: Lessons Learned and Applied in Software Design
            • Article
            Hydraulic Engineering Laboratory Reports (1970)

            The following work is part of a continuing study of the sediments and sedimentary processes of the continental shelf of central Califor nia done in cooperation between the University of California, Berkeley, and the Coastal Engineering Research Center, U. S. Army Corps of Engineers. Sediment analyses of the samples were done at the Univer sity of California, Berkeley, utilizing the facilities of the Depart ments of Civil Engineering and Geology and the Institute of Marine Resources. The results of this study will be presented in three separate reports:

            Part A Introduction and Grain Size Data (this volume) Part B Mineralogical Data Part C Interpretation and Summary of Results

            The first two reports, Parts A and B, will be presented with little or no interpretation. In Part C the authors' interpretation of the data plus background information and previous work in the study area will be given.

            The area covered by this report extends from Pigeon Point in the north to Sand Hill Point in the south. With the completion of this report a complete section of the continental shelf of California from Russian River to Monterey Bay will have been studied. The methods of sediment analysis employed in the overall study are grain size analysis followed by heavy mineral analysis and interpretation.

              Cover page: Recent Sediments of the Central California Continental Shelf, Pigeon Point to Sand Hills Bluff: Part A -- Introduction and Grain Size Analysis
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              • Peer Reviewed
              UC San Diego Previously Published Works (2011)
              Background: CNS injury including stroke, infection, and tumor growth lead to astrogliosis, a process that involves upregulation of glial fibrillary acidic protein (GFAP) in astrocytes. However, the kinetics of astrogliosis that is related to these insults (i.e. tumor) is largely unknown.Results: Using transgenic mice expressing firefly luciferase under the regulation of the GFAP promoter (GFAP-luc), we developed a model system to monitor astrogliosis upon tumor growth in a rapid, non-invasive manner. A biphasic induction of astrogliosis was observed in our xenograft model in which an early phase of activation of GFAP was associated with inflammatory response followed by a secondary, long-term upregulation of GFAP. These animals reveal GFAP activation with kinetics that is in parallel with tumor growth. Furthermore, a strong correlation between astrogliosis and tumor size was observed.Conclusions: Our results suggest that non-invasive, quantitative bioluminescent imaging using GFAP-luc reporter animal is a useful tool to monitor temporal-spatial kinetics of host-mediated astrogliosis that is associated with glioma and metastatic brain tumor growth. © 2011 Lee et al; licensee BioMed Central Ltd.
                Cover page: Non-invasive quantification of brain tumor-induced astrogliosis
                • Article
                • Peer Reviewed
                International Organization of Citrus Virologists Conference Proceedings (1957-2010), Volume 11, Issue 11 (1991)
                  Cover page: Additional Factors Affecting dsRNA Analysis of Citrus Tristeza Virus
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                  Faculty (2013)
                  This paper studies systems of polynomial equations that provide information about orientability of matroids. First, we study systems of linear equations over GF(2), originally alluded to by Bland and Jensen in their seminal paper on weak orientability. The Bland-Jensen linear equations for a matroid M have a solution if and only if M is weakly orientable. We use the Bland-Jensen system to determine weak orientability for all matroids on at most nine elements and all matroids between ten and twelve elements having rank three. Our experiments indicate that for small rank, about half the time, when a simple matroid is not orientable, it is already non-weakly orientable. Thus, about half of the small simple non-orientable matroids of rank three are not representable over fields having order congruent to three modulo four. For binary matroids, the Bland-Jensen linear systems provide a practical way to check orientability. Second, we present two extensions of the Bland-Jensen equations to slightly larger systems of non-linear polynomial equations. Our systems of polynomial equations have a solution if and only if the associated matroid M is orientable. The systems come in two versions, one directly extending the Bland-Jensen system for GF(2), and a different system working over other fields. We study some basic algebraic properties of these systems. Finally, we present an infinite family of non-weakly-orientable matroids, with growing rank and co-rank. We conjecture that these matroids are minor-minimal non-weakly-orientable matroids.
                    • Article
                    • Peer Reviewed
                    UC San Francisco Previously Published Works (2019)

                    Objective

                    We aim to study to what extent conventional and deep-learning-based T2 relaxometry patterns are able to distinguish between knees with and without radiographic osteoarthritis (OA).

                    Methods

                    T2 relaxation time maps were analyzed for 4,384 subjects from the baseline Osteoarthritis Initiative (OAI) Dataset. Voxel Based Relaxometry (VBR) was used for automatic quantification and voxel-based analysis of the differences in T2 between subjects with and without radiographic OA. A Densely Connected Convolutional Neural Network (DenseNet) was trained to diagnose OA from T2 data. For comparison, more classical feature extraction techniques and shallow classifiers were used to benchmark the performance of our algorithm's results. Deep and shallow models were evaluated with and without the inclusion of risk factors. Sensitivity and Specificity values and McNemar test were used to compare the performance of the different classifiers.

                    Results

                    The best shallow model was obtained when the first ten Principal Components, demographics and pain score were included as features (AUC = 77.77%, Sensitivity = 67.01%, Specificity = 71.79%). In comparison, DenseNet trained on raw T2 data obtained AUC = 83.44%, Sensitivity = 76.99%, Specificity = 77.94%. McNemar test on two misclassified proportions form the shallow and deep model showed that the boost in performance was statistically significant (McNemar's chi-squared = 10.33, degree of freedom (DF) = 1, P-value = 0.0013).

                    Conclusion

                    In this study, we presented a Magnetic Resonance Imaging (MRI)-based data-driven platform using T2 measurements to characterize radiographic OA. Our results showed that feature learning from T2 maps has potential in uncovering information that can potentially better diagnose OA than simple averages or linear patterns decomposition.
                      Cover page: Diagnosing osteoarthritis from T2 maps using deep learning: an analysis of the entire Osteoarthritis Initiative baseline cohort
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