Rheological performance evaluation of asphalt modified with bio-based polymers

Fuel-based polymers, used as modifiers and additives in asphalt cement binders, improve the rheological performance of the base asphalt binders, therefore increase the resistance to pavement distresses. However, demand for polymers that are biodegradable, environmentally friendly, and cost effective is increasing. Soybean oil used as an alternative in place of soft and rubbery elastomers polybutadiene derived from crude oil was synthesized to bio-based polymers via chemical synthesis methods reversible addition-fragmentation chain transfer (RAFT) and atom transfer radical polymerization (ATRP). In this study, bio-based polymers (PS-PAESO and PS-PAESO-Cl) with different styrene parameters were blended at a dosage of 3% by weight to a base asphalt binder by the solvent blending approach and three different shear blending methods. The objective of this study was to characterize the rheological properties of bio-based polymer modified asphalt blends by conducting dynamic shear rheometer (DSR), rolling thin film oven (RTFO), pressurized aging vessel (PAV), and bending beam rheometer (BBR) based on the Superpave performance graded asphalt binder specifications. The complex modulus (G*), phase angle (δ), mass losses, creep stiffness were determined to evaluate the rheological properties of the modified blends. Statistical analysis was conducted to evaluate the related factors that may influence the test results and to develop statistical modeling for predicting the bio-based polymers with appropriate styrene parameters that would optimize the rheological performance of the modified blends. Results from high temperature performance tests show that the addition of bio-based polymer (PS-PAESO and PS-PAESO-PS) used in this study increase the critical high temperature of the base binder that indicate an improvement on the resistance of rutting at high temperature. The similar results are observed from the master curves and the black diagrams which both exhibit stiffer behavior of the base asphalt at higher temperatures after modification, which indicates a rubber-elastic network establishment within the blends. Whereas, these bio-based polymers do not substantially improve the resistance to low temperature thermal cracking based on the critical low temperature results. Another finding is the use of bio-based polymers generally widened the continuous performance grade range of the base asphalt binder, which indicates that the bio-based polymers reduce the temperature susceptibility of the base asphalt binder. Furthermore, the statistical analysis on laboratory test results show no statistically significant difference between the three shear blending methods used in this study and no statistically significant difference between the polymer synthesis reaction durations. However, further statistical analysis by using block design on the shear blending methods and the polymer reaction durations shows there is statistically significant difference between the short and long reaction durations but no statistically significant difference between the shear blending methods. The finalized prediction models based on the response surface modeling present the same predicated styrene parameters in polymer to the test result analysis, which indicates that bio-based polymer with styrene parameters as lower molecular weight and lower styrene content are recommended for achieving higher critical high temperatures

3D RECONSTRUCTION USING MULTI-VIEW IMAGING SYSTEM

This thesis presents a new system that reconstructs the 3D representation of dental casts. To maintain the integrity of the 3D representation, a standard model is built to cover the blind spots that the camera cannot reach. The standard model is obtained by scanning a real human mouth model with a laser scanner. Then the model is simplified by an algorithm which is based on iterative contraction of vertex pairs. The simplified standard model uses a local parametrization method to obtain the curvature information. The system uses a digital camera and a square tube mirror in front of the camera to capture multi-view images. The mirror is made of stainless steel in order to avoid double reflections. The reflected areas of the image are considered as images taken by the virtual cameras. Only one camera calibration is needed since the virtual cameras have the same intrinsic parameters as the real camera. Depth is computed by a simple and accurate geometry based method once the corresponding points are identified. Correspondences are selected using a feature point based stereo matching process, including fast normalized cross-correlation and simulated annealing

Surface Evolution Under Curvature Flows

In many areas of computer vision, such as multiscale analysis and shape description, an image or surface is smoothed by a nonlinear parabolic partial differential equation to eliminate noise and to reveal the large global features. An ideal flow, or smoothing process, should not create new features. In this paper we describe in detail the effect of a number of flows on surfaces on the parabolic curves, the ridge curves, and umbilic points. In particular we look at the mean curvature flow and the two principal curvature flows. Our calculations show that two principal curvature flows never create parabolic and ridge curves of the same type as the flow, but no flow is found capable of simultaneously smoothing out all features. In fact, we find that the principal curvature flows in some cases create a highly degenerate type of umbilic. We illustrate the effect of these flows by an example of a 3-D face evolving under principal curvature flows.Mathematic

Selenium status and cardiovascular diseases: meta-analysis of prospective observational studies and randomized controlled trials

Background/Objectives: Selenium was thought to have a role in cardiovascular disease (CVD) owing to its antioxidant properties; however, evidence from observational studies and randomized controlled trials (RCTs) has been inconsistent and controversial. We thus conducted a meta-analysis to assess the discrepancies between observational and randomized trial evidence. Subjects/Methods: We searched MEDLINE and EMBASE for eligible prospective studies regarding the relationship between selenium and CVD up to 15 December 2013 and finally included 16 prospective observational studies and 16 RCTs. Random effects model was used to estimate the pooled relative risk (RR). Generalized least-squares trend test and restricted cubic spline model were performed to assess a linear and a nonlinear dose–response relationship. Results: Our meta-analysis of prospective studies showed a nonlinear relationship of CVD risk with blood selenium concentrations across a range of 30–165 μg/l and a significant benefit of CVD within a narrow selenium range of 55–145 μg/l. Our meta-analyses of RCTs showed that oral selenium supplements (median dose: 200 μg/day) for 2 weeks to 144 months significantly raised the blood selenium concentrations by 56.4 μg/l (95% confidence interval (CI): 40.9, 72.0 μg/l), whereas oral selenium supplements (median: 100 μg/day) for 6 to 114 months caused no effect on CVD (RR=0.91; 95% CI: 0.74, 1.10). Conclusions: Our meta-analysis in prospective studies demonstrated a significant inverse association between selenium status and CVD risk within a narrow selenium range and a null effect of selenium supplementation on CVD was observed in RCTs. These findings indicate the importance of considering selenium status, dose and safety in health assessment and future study design

Deep learning for full-field ultrasonic characterization

This study takes advantage of recent advances in machine learning to establish a physics-based data analytic platform for distributed reconstruction of mechanical properties in layered components from full waveform data. In this vein, two logics, namely the direct inversion and physics-informed neural networks (PINNs), are explored. The direct inversion entails three steps: (i) spectral denoising and differentiation of the full-field data, (ii) building appropriate neural maps to approximate the profile of unknown physical and regularization parameters on their respective domains, and (iii) simultaneous training of the neural networks by minimizing the Tikhonov-regularized PDE loss using data from (i). PINNs furnish efficient surrogate models of complex systems with predictive capabilities via multitask learning where the field variables are modeled by neural maps endowed with (scaler or distributed) auxiliary parameters such as physical unknowns and loss function weights. PINNs are then trained by minimizing a measure of data misfit subject to the underlying physical laws as constraints. In this study, to facilitate learning from ultrasonic data, the PINNs loss adopts (a) wavenumber-dependent Sobolev norms to compute the data misfit, and (b) non-adaptive weights in a specific scaling framework to naturally balance the loss objectives by leveraging the form of PDEs germane to elastic-wave propagation. Both paradigms are examined via synthetic and laboratory test data. In the latter case, the reconstructions are performed at multiple frequencies and the results are verified by a set of complementary experiments highlighting the importance of verification and validation in data-driven modeling

Polyploidy levels of Chinese large-flower chrysanthemum determined by flow cytometry

Flow cytometry was used to determine the ploidy level of 405 Chinese large-flower chrysanthemum (Chrysanthemum morifolium Ramat.) cultivars. Sixty-three cultivars are triploid, 175 cultivars tetraploid, 32 cultivars pentaploid, 46 cultivars hexaploid and 1 cultivar heptaploid. Forty-eight cultivars were then randomly selected for confirmation by chromosome-counting; the results are in agreement with the classification of ploidy level by flow cytometry. Most cultivars are aneuploid. The high percentage of tetraploid and triploid, instead of hexaploid in previous studies, represents the first evidence of low ploidy in large-flower chrysanthemum, which indicated a wider range of ploidy variation in this population. The results also offer further insights to the possible evolution and the regulation of flower size of this large-flower population. Additionally, the combination of flow cytometry and chromosome-counting is proved to be efficient and necessary for large-scale ploidy screening of chrysanthemum.Keywords: Chrysanthemum, ploidy level, flow cytometr

Statistics of shape via principal geodesic analysis on lie groups

Abstrac

Insecticidal Activity of the Soil in the Rhizosphere of Viburnum odoratissimum against Solenopsis invicta (Hymenoptera: Formicidae)

Methyl salicylate produced by Viburnum odoratissimum is known to exert lethal or sublethal effects on insects. Replacing conventional pesticides with insecticidal plants is necessary for environmental protection. We evaluated the behavioral and toxicological responses of the red imported fire ant (RIFA Solenopsis invicta)( Hymenopter: Buren Formicidae) at different soil depths in the rhizosphere of V. odoratissimum. Results of insecticidal activity bioassays indicated that the mortality for minor and major ants in soil at depths of 0-10 cm at days 11 and 12 both ranged from 68.75% to 100.00%, with repellent rates of 83.54%–100.00% and 85.31%–100.00%, respectively. In behavioral ability tests, 85.45%–100.00% of minor ants and 86.74%–94.85% of major ants lost their ability to grasp after nine days, with crawl rates at only 0.00%–29.25% and 0.00%–55.77%, respectively. Therefore, we conclude from the result that the soil under V. odoratissimum at depths of 0-10 cm exhibited excellent insecticidal effect in controlling RIFA.Methyl salicylate produced by Viburnum odoratissimum is known to exert lethal or sublethal effects on insects. Replacing conventional pesticides with insecticidal plants is necessary for environmental protection. We evaluated the behavioral and toxicological responses of the red imported fire ant (RIFA Solenopsis invicta, Buren) (Hymenoptera: Formicidae) at different soil depths in the rhizosphere of V. odoratissimum. Results of insecticidal activity bioassays indicated that the mortality for minor and major ants in soil at depths of 0-10 cm at days 11 and 12 both ranged from 68.75% to 100.00%, with repellency rates of 83.54%-100.00% and 85.31%-100.00%, respectively. In behavioral ability tests, 85.45%-100.00% of minor ants and 86.74%-94.85% of major ants lost their ability to grasp after nine days, with crawling rates at only 0.00%-29.25% and 0.00%-55.77%, respectively. Therefore, we conclude from the result that the soil under V. odoratissimum at depths of 0-10 cm exhibited excellent insecticidal effect in controlling RIFA

Cloning and characterization of maize ZmSPK1, a homologue to nonfermenting1-related protein kinase2

SnRK2s play important roles in plant stresses responses. One full-length cDNA encoding a SnRK2b homologue was isolated from maize by RT-PCR and named as ZmSPK1 (for stress-induced protein kinase). The ZmSPK1 protein has 364 amino acids with an estimated molecular mass of 41.8 KD and an isoelectric point of 5.8. The deduced protein sequence has the closest identities to the members of SnRK2b group. RT-PCR analysis showed that the ZmSPK1 expression was induced by mannitol, salt and abscisic acid (ABA). Furthermore, in different tissues the ZmSPK1 showed different expression patterns and was most abundant in reproductive organs. These results suggested that ZmSPK1 might play multiple roles in abiotic stress resistance pathways, as well as in plant reproductive development.Key words: Zea mays L., SnRK2b, expression pattern, abiotic stres