Bolt Bearing Behavior of Engineered Wood Composites

The goal of this research was to gain a better understanding of the bolt bearing behavior of engineered wood composites made from yellow poplar lumber. Lumber specimens included in this study were laminated veneer lumber, strandbased lumber, yellow poplar lumber, and Douglas-fir larch lumber. Testing followed the half-hole and full-hole configuration as set forth in ASTM Standard D5764 (1998). In a previous study by Wilkinson (1991), a strong correlation was shown between bearing strength perpendicular to grain and bolt diameter. This study supports Wilkinson\u27s finding for bearing strength perpendicular-to-grain based on the half hole test configuration. Other findings in this study indicate there may be a correlation between bolt diameter and bearing strength parallel-to-grain for the half-hole test configuration as well as a correlation between bolt diameter and bearing strength both perpendicular- and parallel-to-grain for the full-hole test configuration. In general, half-hole tests resulted in a greater dowel-bearing strength than full-hole tests, especially for 12.7mm (1/2 in) diameter bolts. Also, engineered wood composites generally provided equivalent or greater dowel-bearing strength in the half-hole configuration and greater dowel-bearing strength in the full-hole configuration when compared to lumber from the same species

C4: The New Hampshire Spherulitic Rhyolites: Rocks of Importance to Prehistoric Native Americans

Guidebook for field trips in Western Maine and Northern New Hampshire: New England Intercollegiate Geological Conference, p. 305-316

Development of quantum perspectives in modern physics

Introductory undergraduate courses in classical physics stress a perspective that can be characterized as realist; from this perspective, all physical properties of a classical system can be simultaneously specified and thus determined at all future times. Such a perspective can be problematic for introductory quantum physics students, who must develop new perspectives in order to properly interpret what it means to have knowledge of quantum systems. We document this evolution in student thinking in part through pre- and post-instruction evaluations using the Colorado Learning Attitudes about Science Survey. We further characterize variations in student epistemic and ontological commitments by examining responses to two essay questions, coupled with responses to supplemental quantum attitude statements. We find that, after instruction in modern physics, many students are still exhibiting a realist perspective in contexts where a quantum-mechanical perspective is needed. We further find that this effect can be significantly influenced by instruction, where we observe variations for courses with differing learning goals. We also note that students generally do not employ either a realist or a quantum perspective in a consistent manner.Comment: 18 pages, plus references; 3 figures; 9 tables. PACS: 01.40.Fk, 03.65._

Application of a single-objective, hybrid genetic algorithm approach to pharmacokinetic model building.

A limitation in traditional stepwise population pharmacokinetic model building is the difficulty in handling interactions between model components. To address this issue, a method was previously introduced which couples NONMEM parameter estimation and model fitness evaluation to a single-objective, hybrid genetic algorithm for global optimization of the model structure. In this study, the generalizability of this approach for pharmacokinetic model building is evaluated by comparing (1) correct and spurious covariate relationships in a simulated dataset resulting from automated stepwise covariate modeling, Lasso methods, and single-objective hybrid genetic algorithm approaches to covariate identification and (2) information criteria values, model structures, convergence, and model parameter values resulting from manual stepwise versus single-objective, hybrid genetic algorithm approaches to model building for seven compounds. Both manual stepwise and single-objective, hybrid genetic algorithm approaches to model building were applied, blinded to the results of the other approach, for selection of the compartment structure as well as inclusion and model form of inter-individual and inter-occasion variability, residual error, and covariates from a common set of model options. For the simulated dataset, stepwise covariate modeling identified three of four true covariates and two spurious covariates; Lasso identified two of four true and 0 spurious covariates; and the single-objective, hybrid genetic algorithm identified three of four true covariates and one spurious covariate. For the clinical datasets, the Akaike information criterion was a median of 22.3 points lower (range of 470.5 point decrease to 0.1 point decrease) for the best single-objective hybrid genetic-algorithm candidate model versus the final manual stepwise model: the Akaike information criterion was lower by greater than 10 points for four compounds and differed by less than 10 points for three compounds. The root mean squared error and absolute mean prediction error of the best single-objective hybrid genetic algorithm candidates were a median of 0.2 points higher (range of 38.9 point decrease to 27.3 point increase) and 0.02 points lower (range of 0.98 point decrease to 0.74 point increase), respectively, than that of the final stepwise models. In addition, the best single-objective, hybrid genetic algorithm candidate models had successful convergence and covariance steps for each compound, used the same compartment structure as the manual stepwise approach for 6 of 7 (86 %) compounds, and identified 54 % (7 of 13) of covariates included by the manual stepwise approach and 16 covariate relationships not included by manual stepwise models. The model parameter values between the final manual stepwise and best single-objective, hybrid genetic algorithm models differed by a median of 26.7 % (q₁ = 4.9 % and q₃ = 57.1 %). Finally, the single-objective, hybrid genetic algorithm approach was able to identify models capable of estimating absorption rate parameters for four compounds that the manual stepwise approach did not identify. The single-objective, hybrid genetic algorithm represents a general pharmacokinetic model building methodology whose ability to rapidly search the feasible solution space leads to nearly equivalent or superior model fits to pharmacokinetic data

Observations on the statistical nature of terrestrial irradiation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/24505/1/0000782.pd

The probability distribution of terrestrial irradiation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/24562/1/0000843.pd

Electrophilic PPARγ Ligands Attenuate IL-1β and Silica-Induced Inflammatory Mediator Production in Human Lung Fibroblasts via a PPARγ-Independent Mechanism

Acute and chronic lung inflammation is associated with numerous important disease pathologies including asthma, chronic obstructive pulmonary disease and silicosis. Lung fibroblasts are a novel and important target of anti-inflammatory therapy, as they orchestrate, respond to, and amplify inflammatory cascades and are the key cell in the pathogenesis of lung fibrosis. Peroxisome proliferator-activated receptor gamma (PPARγ) ligands are small molecules that induce anti-inflammatory responses in a variety of tissues. Here, we report for the first time that PPARγ ligands have potent anti-inflammatory effects on human lung fibroblasts. 2-cyano-3, 12-dioxoolean-1, 9-dien-28-oic acid (CDDO) and 15-deoxy-Δ12,14-prostaglandin J2 (15d-PGJ2) inhibit production of the inflammatory mediators interleukin-6 (IL-6), monocyte chemoattractant protein-1 (MCP-1), COX-2, and prostaglandin (PG)E2 in primary human lung fibroblasts stimulated with either IL-1β or silica. The anti-inflammatory properties of these molecules are not blocked by the PPARγ antagonist GW9662 and thus are largely PPARγ independent. However, they are dependent on the presence of an electrophilic carbon. CDDO and 15d-PGJ2, but not rosiglitazone, inhibited NF-κB activity. These results demonstrate that CDDO and 15d-PGJ2 are potent attenuators of proinflammatory responses in lung fibroblasts and suggest that these molecules should be explored as the basis for novel, targeted anti-inflammatory therapies in the lung and other organs

A Novel Anti-Inflammatory and Pro-Resolving Role for Resolvin D1 in Acute Cigarette Smoke-Induced Lung Inflammation

Introduction: Cigarette smoke is a profound pro-inflammatory stimulus that contributes to acute lung injuries and to chronic lung disease including COPD (emphysema and chronic bronchitis). Until recently, it was assumed that resolution of inflammation was a passive process that occurred once the inflammatory stimulus was removed. It is now recognized that resolution of inflammation is a bioactive process, mediated by specialized lipid mediators, and that normal homeostasis is maintained by a balance between pro-inflammatory and pro-resolving pathways. These novel small lipid mediators, including the resolvins, protectins and maresins, are bioactive products mainly derived from dietary omega-3 and omega-6 polyunsaturated fatty acids (PUFA). We hypothesize that resolvin D1 (RvD1) has potent anti-inflammatory and pro-resolving effects in a model of cigarette smoke-induced lung inflammation. Methods: Primary human lung fibroblasts, small airway epithelial cells and blood monocytes were treated with IL-1β or cigarette smoke extract in combination with RvD1 in vitro, production of pro-inflammatory mediators was measured. Mice were exposed to dilute mainstream cigarette smoke and treated with RvD1 either concurrently with smoke or after smoking cessation. The effects on lung inflammation and lung macrophage populations were assessed. Results: RvD1 suppressed production of pro-inflammatory mediators by primary human cells in a dose-dependent manner. Treatment of mice with RvD1 concurrently with cigarette smoke exposure significantly reduced neutrophilic lung inflammation and production of pro-inflammatory cytokines, while upregulating the anti-inflammatory cytokine IL-10. RvD1 promoted differentiation of alternatively activated (M2) macrophages and neutrophil efferocytosis. RvD1 also accelerated the resolution of lung inflammation when given after the final smoke exposure. Conclusions: RvD1 has potent anti-inflammatory and pro-resolving effects in cells and mice exposed to cigarette smoke. Resolvins have strong potential as a novel therapeutic approach to resolve lung injury caused by smoke and pulmonary toxicants