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TaPT: Temperature-Aware Dynamic Cache Optimization for Embedded Systems(MDPI, 2018-03)Embedded systems have stringent design constraints, which has necessitated much prior research focus on optimizing energy consumption and/or performance. Since embedded systems typically have fewer cooling options, rising temperature, and thus temperature optimization, is an emergent concern. Most embedded systems only dissipate heat by passive convection, due to the absence of dedicated thermal management hardware mechanisms. The embedded system's temperature not only affects the system's reliability, but can also affect the performance, power, and cost. Thus, embedded systems require efficient thermal management techniques. However, thermal management can conflict with other optimization objectives, such as execution time and energy consumption. In this paper, we focus on managing the temperature using a synergy of cache optimization and dynamic frequency scaling, while also optimizing the execution time and energy consumption. This paper provides new insights on the impact of cache parameters on efficient temperature-aware cache tuning heuristics. In addition, we present temperature-aware phase-based tuning, TaPT, which determines Pareto optimal clock frequency and cache configurations for fine-grained execution time, energy, and temperature tradeoffs. TaPT enables autonomous system optimization and also allows designers to specify temperature constraints and optimization priorities. Experiments show that TaPT can effectively reduce execution time, energy, and temperature, while imposing minimal hardware overhead.
Analysis and visualization of vanadium mineral diversity and distribution(MINERALOGICAL SOC AMER, 2018-07)We employ large mineralogical data resources to investigate the diversity and spatial distribution of vanadium minerals. Data for 219 approved species (http://http://rruff.info/ima, as of April 15, 2016), representing 5437 mineral species-locality pairs (http://http://mindat.org and other sources, as of April 15, 2016), facilitate statistical evaluation and network analysis of these vanadium minerals. V minerals form a sparse, moderately centralized and transitive network, and they cluster into at least seven groups, each of which indicates distinct paragenetic process. In addition, we construct the V mineral-locality bipartite network to reveal mineral diversity at each locality. It shows that only a few V minerals occur at more than three localities, while most minerals occur at one or two localities, conforming to a Large Number of Rare Events (LNRE) distribution. We apply the LNRE model to predict that at least 307 +/- 30 (1 sigma) vanadium minerals exist in Earth's crust today, indicating that at least 88 species have yet to be discovered-a minimum estimate because it assumes that new minerals will be found only using the same methods as in the past. Numerous additional vanadium minerals likely await discovery using micro-analytical methods. By applying LNRE models to subsets of V minerals, we speculate that most new vanadium minerals are to be discovered in sedimentary or hydrothermal non-U-V ore deposits other than igneous or metamorphic rocks/ore deposits.
What Defines the Effective Hydraulic Conductivity of a Heterogeneous Medium?(The University of Arizona., 2018)Geologic processes produce heterogeneous porous materials that are complex systems to analyze. This research is focused on the bulk behavior of these heterogeneous media, specifically, the effective hydraulic conductivity (Keff). Specifically, I studied media comprised of two block materials with different K values to understand how the percent composition of the materials and their spatial distribution affect Keff. Two approaches are taken. First, I examine an exponential mixing law, that describes Keff as falling between two end members when the materials are distributed parallel to (arithmetic) and perpendicular to (harmonic) the flow direction. The results, based on examining steady state flow through 990,000 grids with MODFLOW linked with MATLAB, indicate a linear increase in the exponent describing K mixing as a function of the fraction of the high K material included, leading to an expression that estimates Keff with an R2 of 0.982. Second, I show that an approach based on energy dissipation weighting, while difficult to infer visually, returns a perfect explanation of K weighting.
Genome-wide association study of habitual physical activity in over 377,000 UK Biobank participants identifies multiple variants including CADM2 and APOE(NATURE PUBLISHING GROUP, 2018-06)Background/objectives Physical activity (PA) protects against a wide range of diseases. Habitual PA appears to be heritable, motivating the search for specific genetic variants that may inform efforts to promote PA and target the best type of PA for each individual. Subjects/methods We used data from the UK Biobank to perform the largest genome-wide association study of PA to date, using three measures based on self-report (n(max) = 377,234) and two measures based on wrist-worn accelerometry data (nmax = 91,084). We examined genetic correlations of PA with other traits and diseases, as well as tissue-specific gene expression patterns. With data from the Atherosclerosis Risk in Communities (ARIC; n = 8,556) study, we performed a meta-analysis of our top hits for moderate-to-vigorous PA (MVPA). Results We identified ten loci across all PA measures that were significant in both a basic and a fully adjusted model (p < 5 x 10(-9)). Upon meta-analysis of the nine top hits for MVPA with results from ARIC, eight were genome-wide significant. Interestingly, among these, the rs429358 variant in the APOE gene was the most strongly associated with MVPA, whereby the allele associated with higher Alzheimer's risk was associated with greater MVPA. However, we were not able to rule out possible selection bias underlying this result. Variants in CADM2, a gene previously implicated in obesity, risk-taking behavior and other traits, were found to be associated with habitual PA. We also identified three loci consistently associated (p < 5 x 10(-5)) with PA across both self-report and accelerometry, including CADM2. We found genetic correlations of PA with educational attainment, chronotype, psychiatric traits, and obesity-related traits. Tissue enrichment analyses implicate the brain and pituitary gland as locations where PA-associated loci may exert their actions. Conclusions These results provide new insight into the genetic basis of habitual PA, and the genetic links connecting PA with other traits and diseases.
Effect of cardiometabolic risk factors on the relationship between adiposity and bone mass in girls(NATURE PUBLISHING GROUP, 2018-06)Background/objective Childhood obesity has been separately associated with cardiometabolic risk factors (CMRs) and increased risk of fracture. However, both augmented and compromised bone mass have been reported among overweight/obese children. Metabolic dysfunction, often co-existing with obesity, may explain the discrepancy in previous studies. The aim of this study was to examine whether the relationship between adiposity and dual-energy X-ray absorptiometry (DXA) derived bone mass differed in young girls with and without CMR(s). Subjects/methods Whole-body bone and body composition measures by DXA and measures of CMR (fasting glucose, high-density lipoprotein cholesterol (HDL-C), triglyceride (TG), systolic and diastolic blood pressure, waist circumference (WC)) were obtained from 307, 9-to 12-year-old girls. Girls with 1 or >= 2 CMR(s) were considered to be at risk (vs. no CMR). Multiple linear regression was used to test the relationship of total fat mass with total body bone mineral content (BMC) after controlling for height, lean mass, CMR risk, and other potential confounders. Results There was a significant interaction between CMR risk and total body fat mass. When girls were stratified by CMR group, all groups had a significant positive relationship between fat mass and BMC (p < 0.05), however, girls with >= 2 CMRs had a lower BMC for a given level of body fat. Total body fat was not significantly related to bone mineral density (p > 0.05). Conclusion Fat mass has a positive relationship with BMC even after controlling for lean mass. However, the positive relationship of fat mass with BMC may be attenuated if multiple CMRs are present.