Direct and gradient-based average strain estimation by using weighted nearest neighbor cross-correlation peaks

In this paper, two novel approaches, gradientbased and direct strain estimation techniques, are proposed for high-quality average strain imaging incorporating a cost function maximization. Stiffness typically is a continuous function. Consequently, stiffness of proximal tissues is very close to that of the tissue corresponding to a given data window. Hence, a cost function is defined from exponentially weighted neighboring pre- and post-compression RF echo normalized cross-correlation peaks in the lateral (for displacement estimation) or in both the axial and the lateral (for direct strain estimation) directions. This enforces a controlled continuity in displacement/strain and average displacement/strain is calculated from the corresponding maximized cost function. Axial stress causes lateral shift in the tissue. Therefore, a 1-D post-compression echo segment is selected by incorporating Poisson's ratio. Two stretching factors are considered simultaneously in gradient-based strain estimation that allow imaging the lesions properly. The proposed time-domain gradient-based and direct-strain-estimation-based algorithms demonstrate significantly better performance in terms of elastographic signal-to-noise ratio (SNRe), elastographic contrast-to-noise ratio (CNRe), peak signal-to-noise ratio (PSNR), and mean structural similarity (MSSIM) than the other reported time-domain gradientbased and direct-strain-estimation techniques in finite element modeling (FEM) simulation and phantom experiments. For example, in FEM simulation, it has been found that the proposed direct strain estimation method can improve up to approximately 2.49 to 8.71, 2.2 to 6.63, 1.5 to 5, and 1.59 to 2.45 dB in the SNRe, CNRe, PSNR, and MSSIM compared with the traditional direct strain estimation method, respectively, and the proposed gradient-based algorithm demonstrates 2.99 to 16.26, 18.74 to 23.88, 3 to 9.5, and 0.6 to 5.36 dB improvement in the SNRe, CNRe, PSNR, and MSSIM, respectively, compared with a recently reported time-domain gradient-based technique. The range of improvement as noted above is for low to high applied strains. In addition, the comparative results using the in vivo breast data (including malignant or benign masses) also show that the lesion size is better defined by the proposed gradient-based average strain estimation technique.     

Progress of key strategies in development of electrospun scaffolds: bone tissue

There has been unprecedented development in tissue engineering (TE) over the last few years owing to its potential applications, particularly in bone reconstruction or regeneration. In this article, we illustrate several advantages and disadvantages of different approaches to the design of electrospun TE scaffolds. We also review the major benefits of electrospun fibers for three-dimensional scaffolds in hard connective TE applications and identify the key strategies that can improve the mechanical properties of scaffolds for bone TE applications. A few interesting results of recent investigations have been explained for future trends in TE scaffold research.     

Influence of nanofluids on mixed convective heat transfer over a horizontal backward‐facing step

Predictions are reported for laminar mixed convection using various types of nanofluids over a horizontal backward‐facing step in a duct, in which the upstream wall and the step are considered adiabatic surfaces, while the downstream wall from the step is heated to a uniform temperature that is higher than the inlet fluid temperature. The straight wall that forms the other side of the duct is maintained at constant temperature equivalent to the inlet fluid temperature. Eight different types of nanoparticles, Au, Ag, Al₂O₃, Cu, CuO, diamond, SiO₂, and TiO₂, with 5% volume fraction are used. The conservation equations along with the boundary conditions are solved using the finite volume method. Results presented in this paper are for a step height of 4.9 mm and an expansion ratio of 1.942, while the total length in the downstream of the step is 0.5 m. The Reynolds number is in the range of 75 ≤ Re ≤ 225. The downstream wall was fixed at a uniform wall temperature in the range of 0 ≤ ΔT ≤ 30 °C which is higher than the inlet flow temperature. Results reveal that there is a primary recirculation region for all nanofluids behind the step. It is noticed that nanofluids without secondary recirculation region have a higher Nusselt number and it increases with Prandtl number decrement. On the other hand, nanofluids with secondary recirculation regions are found to have a lower Nusselt number. Diamond nanofluid has the highest Nusselt number in the primary recirculation region, while SiO₂ nanofluid has the highest Nusselt number downstream of the primary recirculation region. The skin friction coefficient increases as the temperature difference increases and the Reynolds number decreases. © 2011 Wiley Periodicals, Inc. Heat Trans Asian Res; Published online in Wiley Online Library ( wileyonlinelibrary.com/journal/htj ). DOI 10.1002/htj.20344     

Statistical Analysis on the Cost and Duration of Public Building Projects

A probabilistic model is proposed to predict the risk effects on time and cost of public building projects. The research goal is to utilize a real history data in estimating project cost and duration. The model results can be used to adjust floats and budgets of the planning schedule before project commencement. Statistical regression models and sample tests are developed using real data of 113 public projects. The model outputs can be used by project managers in the planning phase to validate the schedule critical path time and project budget. The comparison of means analysis for project cost and time performance indicated that the sample projects tend to finish over budget and almost on schedule. Regression models were developed to model project cost and time. The regression analysis showed that the project budgeted cost and planned project duration provide a good basis for estimating the cost and duration. The regression model results were validated by estimating the prediction error in percent and through conducting out-of-sample tests. In conclusion, the models were validated at a probability of 95%, at which the proposed models predict the project cost and duration at an error margin of ±0.035% of the actual cost and time.     

Computational applications of a coupled plasticity-damage constitutive model for simulating plain concrete fracture

A coupled plasticity-damage model for plain concrete is presented in this paper. Based on continuum damage mechanics (CDM), an isotropic and anisotropic damage model coupled with a plasticity model is proposed in order to effectively predict and simulate plain concrete fracture. Two different damage evolution laws for both tension and compression are formulated for a more accurate prediction of the plain concrete behavior. In order to derive the constitutive equations and for the easiness in the numerical implementation, in the CDM framework the strain equivalence hypothesis is adopted such that the strain in the effective (undamaged) configuration is equivalent to the strain in the nominal (damaged) configuration. The proposed constitutive model has been shown to satisfy the thermodynamics requirements. Detailed numerical algorithms are developed for the finite element implementation of the proposed coupled plasticity-damage model. The numerical algorithm is coded using the user subroutine UMAT and then implemented in the commercial finite element analysis program Abaqus. Special emphasis is placed on identifying the plasticity and damage model material parameters from loading-unloading uniaxial test results. The overall performance of the proposed model is verified by comparing the model predictions to various experimental data, such as monotonic uniaxial tension and compression tests, monotonic biaxial compression test, loading-unloading uniaxial tensile and compressive tests, and mixed-mode fracture tests.     

Changes in rumen bacterial and archaeal communities over the transition period in primiparous Holstein dairy cows

In the present study, we hypothesized that the rumen bacterial and archaeal communities would change significantly over the transition period of dairy cows, mainly as an adaptation to the classical use of low-grain prepartum and high-grain postpartum diets. Bacterial 16S rRNA gene amplicon sequencing of rumen samples from 10 primiparous Holstein dairy cows revealed no changes over the transition period in relative abundance of genera such as Ruminococcus, Butyrivibrio, Clostridium, Coprococcus, and Pseudobutyrivibrio. However, other dominant genus-level taxa, such as Prevotella, unclassified Ruminococcaceae, and unclassified Succinivibrionaceae, showed distinct changes in relative abundance from the prepartum to the postpartum period. Overall, we observed individual fluctuation patterns over the transition period for a range of bacterial taxa that, in some cases, were correlated with observed changes in the rumen short-chain fatty acids profile. Combined results from clone library and terminal-restriction fragment length polymorphism (T-RFLP) analyses, targeting the methyl-coenzyme M reductase α-subunit (mcrA) gene, revealed a methanogenic archaeal community dominated by the Methanobacteriales and Methanomassiliicoccales orders, particularly the genera Methanobrevibacter, Methanosphaera, and Methanomassiliicoccus. As observed for the bacterial community, the T-RFLP patterns showed significant shifts in methanogenic community composition over the transition period. Together, the composition of the rumen bacterial and archaeal communities exhibited changes in response to particularly the dietary changes of dairy cows over the transition period.     

Effect of Different Drying Treatments and Solvent Ratios on Phytochemical Constituents of Ipomoea aquatica and Correlation with α-Glucosidase Inhibitory Activity

Ipomoea aquatica is an aquatic plant that is widely consumed in Southeast Asia as a vegetable. In this study, the influence of various ethanol ratios (0, 20, 50, 80, and 100%) as an extraction solvent and different drying methods including air drying, sun drying, and oven drying on phytochemical constituents of I. aquatica was investigated using a proton nuclear magnetic resonance-based metabolomics approach. The effect on α-glucosidase inhibitory activity and total phenolic content was also examined. Clear discrimination was observed between different ethanol ratios and different drying processes by principal component analysis. The highest α-glucosidase inhibitory activity was observed for absolute ethanol extract from the oven drying method with IC₅₀ value of 204.0 ± 59.0 µg/mL and total phenolic content value of 22.0 ± 0.7 µg gallic acid equivalent/mg extract. Correlation between the α-glucosidase inhibitory activity and the metabolite were analyzed using a partial least square analysis. The metabolites that are responsible for the activity were quercetin derivatives, chlorogenic acid derivatives, sucrose, and fructose. This study highlights the basis for future investigations of I. aquatica as a source of food that has the potential for nutraceutical enhancement and as ingredient in medicinal preparation.     

Hydrogen sensing using gold nanoclusters supported on tungsten trioxide thin films

Controlled amounts of chemically synthesised gold (Au) nanoclusters were deposited onto tungsten trioxide (WO₃) nanostructured thin films as sensors for hydrogen. The Au/WO₃ thin films were characterised by XPS, XRD, SEM and TEM. Performance of Au/WO₃ films was tested at operating temperatures varying from room temperature to 450 °C. It was demonstrated that Au metal loading plays an important role in defining enhancement of the sensor response towards hydrogen. “Less is more” principle applies to the reported here sensors as materials made using lower concentration of Au nanoclusters demonstrated significantly better response. HRTEM images of the Au/WO₃ thin films provide evidence that the more active sensors are enriched with smaller Au nanoparticles (≤5 nm). Fast response towards H₂ within a wide range of industrially relevant concentrations, excellent baseline stability and signal reproducibility at optimized operating temperature demonstrate feasibility of this novel approach toward fabrication of sensors.