Culm Morphological Traits Contributing to Lodging Resistance in First Generation NERICA Cultivars Under Foliar Application of Orthosilicic Acid Fertilizer

Silicon - Lodging resistance in upland rice requires adequate knowledge of the mechanical basis of culm morphological traits (CMTs) with potential for improved structural integrity under...     

Characterization of the structure and properties of processed alumina-graphene and alumina-zirconia composites

The onset of hybrid alumina-based composites, which combines two or more nano-particles within the alumina matrix has already shown promising improvements in the matrix material. However, variations in mechanical properties including the optimum compositions that give improved properties faced with the development of alumina-based composites require further studies to understand the underlying mechanisms and synergistic effects of the nano-particle additions on the alumina matrix. In the current study, the structure and properties of Al?O?-graphene (0.5 wt%) and Al?O?–ZrO? (4 wt% and 10 wt%) composites fabricated via hot-pressing was studied as a baseline for multiple combinations. Even though the addition of 10 wt%ZrO? resulted in a 23% reduction in the grain size of the alumina matrix, the 4 wt%ZrO? addition resulted in a 14% increase in grain size as compared to the parent alumina matrix. X-ray diffraction analysis revealed that there was approximately 85% monoclinic (m-ZrO₂) vs. 15% tetragonal (t-ZrO₂) crystal structures in the A4ZrO? sample whilst the A₁₀ZrO? had approximately 93% m-ZrO₂ vs. 7% t-ZrO₂. The high-volume fraction of the monoclinic crystal structures in the A₁₀ZrO? accounts for the induced microcracks in the sample since the transition from the ductile-tetragonal to brittle-monoclinic is associated with the exertion of compressive stresses on the alumina matrix by the associated elastic volume expansion of m-ZrO₂. Also, the addition of 0.5 wt%graphene resulted in about 37% reduction in the grain size of the alumina matrix, and approximately 10% increase in hardness as a result of the distribution of graphene along the grain boundaries of the parent alumina matrix, which restricts grain coalescence and growth during processing. Furthermore, an increase up to 115% and 164% were observed in the fracture toughness (K_IC) with the inclusion of 0.5 wt%graphene and 10 wt%ZrO? respectively, which was primarily ascribed to the fine-grained microstructures and toughening mechanisms of the intergranular graphene and ZrO? particles.     

A fuzzy Bayesian belief network for safety assessment of oil and gas pipelines

Safety assessment of oil and gas (O&G) pipelines is necessary to prevent unwanted events that may cause catastrophic accidents and heavy financial losses. This study develops a safety assessment model for O&G pipeline failure by incorporating fuzzy logic into Bayesian belief network. Proposed fuzzy Bayesian belief network (FBBN) model explicitly represents dependencies of events, updating probabilities and representation of uncertain knowledge (such as randomness, vagueness and ignorance). The study highlights the utility of FBBN in safety analysis of O&G pipeline because of its flexible structure, allowing it to fit a wide variety of accident scenarios. The sensitivity analysis of the proposed model indicates that construction defect, overload, mechanical damage, bad installation and quality of worker are the most significant causes for the O&G pipeline failures. The research results can help owners of transmission and distribution pipeline companies and professionals to prepare preventive safety measures and allocate proper resources.     

On the Issue of Incomplete and Missing Water-Quality Data in Mine Site Databases: Comparing Three Imputation Methods

Large water-quality databases are valuable for predicting mine drainage chemistry, identifying optimal measures for mitigation and remediation, and refuting/refining models and theories. However, such databases often have missing values due to periodic lack of sampling and analysis or input errors. These missing values lead to problems in machine learning and statistical analysis of water-quality data from mine sites. Using water-quality data collected from 1971 to 1994 from many locations at a copper-molybdenum-gold-silver-rhenium mine site, we compared three imputation methods to estimate missing water-quality data: iterative robust model-based imputation (IRMI), multiple imputations of incomplete multivariate data (AMELIA), and sequential imputation for missing values (IMPSEQ). These methods were evaluated based on mean absolute error, relative absolute error, and percent bias techniques. The results showed that IMPSEQ and IRMI are suitable to impute missing values in water-quality databases at mine sites, whereas AMELIA is not.     

Effect of two different rubbers as secondary binders on the friction and wear characteristics of non-asbestos organic (NAO) brake friction materials

Binder provides structural integrity by holding all ingredients in the composition of a brake friction material. The modified binders have played a major role in improving the frictional performance and thermal resistance of the friction material. The present research work evaluates the influence of secondary binders (Nitrile Butadiene rubber (NBR) and Styrene Butadiene rubber (SBR)) on the tribological performance of the friction material using a full-scale inertia brake dynamometer as per JASO C406 standard. Three brake pads were developed by varying the type and composition of secondary rubber binder (5%NBR, 5%SBR and 2.5%NBR + 2.5%SBR) with rest of the ingredients kept unaltered. It was found that the quantity of SBR rubber powder present as secondary binder improved dry and wet recovery. Friction coefficient (μ) exhibited better stability during the fade with the inclusion of both the rubber powders. The friction material with the inclusion of both the NBR and SBR rubber powders exhibited overall better performance than compared to the inclusion of only one secondary binder rubber in the composition. The worn-out surface of the developed friction materials and the counter discs were characterised using FESEM.     

3D Virtual Pome Fruit Tissue Generation Based on Cell Growth Modeling

A 3D virtual fruit tissue generator is presented that can distinctly define the microstructural components of a fruit tissue and that can be used to model important physical processes such as gas transport during controlled atmosphere storage. The model is based on the biomechanics of plant cells in tissues. The main merit of this algorithm is that it can account for typical differences in intercellular air space networks and in cell size and shape found between different fruit species and tissues. The cell is considered as a closed thin walled structure, maintained in tension by turgor pressure. The cell walls of adjacent cells are modeled as parallel, linear elastic elements which obey Hooke's law. A 3D Voronoi tessellation is used to generate the initial topology of the cells. Intercellular air spaces of schizogenous origin are generated by separating the Voronoi cells along the edges where three Voronoi cells are in contact; while intercellular air spaces of lysigenous origin are generated by deleting (killing) some of the Voronoi cells randomly. Cell expansion then results from turgor pressure acting on the yielding cell wall material. To find the sequence of positions of each vertex and thus the shape of the tissue with time, a system of differential equations for the positions and velocities of each vertex is established and solved using a Matlab ordinary differential equation solver. Statistical comparison with synchrotron tomography images of fruit tissue is excellent. The virtual tissues can be used to study tissue mechanics and exchange processes of important metabolites.     

Metastatic cancer cell attachment to endothelium is promoted by endothelial glycocalyx sialic acid degradation

While it is known that cancer cell interactions with vascular endothelial cells (ECs) drive metastatic cancer cell extravasation from blood vessels into secondary tumor sites, the mechanisms of action are still poorly understood. Here, we tested the hypothesis that neuraminidase-induced degradation of EC surface glycocalyx (GCX), particularly the sialic acid (SA) residue components of the GCX, will substantially increase metastatic cancer cell attachment to ECs. To our knowledge, our study is the first to isolate the role of GCX SA residues in cancer cell attachment to the endothelium, which were found to be differentially affected by the presence of neuraminidase and to indeed regulate metastatic cancer cell homing to ECs. We hope that this work will eventually translate to identification of EC GCX-based cancer markers that can be therapeutically targeted to hinder the progression of metastasis.     

The influence of steam injection for Enhanced Oil Recovery (EOR) on the quality of crude oil

Currently, due to reduction of oil reservoirs and the increasing need for oil as the main source for world energy, the need for production of heavy oil reservoirs is inevitable. The main purpose of this study is to determine the effectiveness of some operational and reservoir parameters and their impact on thermal and productive efficiency of thermal process of steam injection and quality of crude oil. In order to model the process, Eclipse-300 simulator was employed. Detection of these parameters, in addition to determining the best production scenario, can lead to the use of this method with better economic conditions. Hence, the results obtained from this study show that the optimal values obtained for operational parameters of stream injection such as steam quality, steam injection pressure, injection rate and well completion injection depth. The simulation results show that the use of optimal values of steam injection parameters can enhance efficiency of steam injection method and can make this method considered as third EOR method in heavy oil reservoirs than previously known in the petroleum industry.