Warping of a Stretched Bimetallic Sheet

Strength of Materials - The development of bimetallic materials is one of the modern lines of research. The differences in the properties of components can impart special mechanical characteristics...     

Full scale investigation of GCL damage mechanisms in small earth dam retrofit applications under earthquake loading

This paper reports results of full scale testing to further explore potential GCL damage mechanisms in earth dam retrofit applications in seismically active areas; in particular, to a) investigate whether shear displacements could reduce the magnitude of GCL panel overlap during earthquake shaking; b) explore the influence of gravel particles on GCL thickness at localised point of contact; and c) observe the consequences of an accidental exposure of an uncovered GCL to short duration rainfall in terms of moisture content and effects during subsequent compaction. The results of these experiments indicate that even under severe shaking no movements were detected at the GCL panel overlap. Whereas gravel particles were observed to locally reduce the thickness of the GCL to 2.2 mm, no plowing of the particle into the GCL occurred due to a lack of shear displacement at the interface, resulting in no localised internal erosion through the barrier. Furthermore, hydration of GCL panels during construction due to surface wetting was observed to result in a state of hydration less than its post-construction state. These results indicate that although each of the three GCL damage mechanisms cannot be ruled out to ever be relevant in practice, the performance of the GCL retrofitted earth dam tested was satisfactory under even severe Level 2 earthquake shaking, and suggests that the retrofitting of small earth dams with GCLs is a promising strategy to improve their static and seismic resistance.     

Adsorption of Uranium from Aqueous Solutions by Expanded Perlite

Radiochemistry - The uranium removal from radioactive liquid waste using expanded perlite (EP) was studied. The influence of the contact time, solution pH, initial uranium concentration, sorption...     

Modeling of Slug Velocity and Pressure Drop in Gas‐Liquid‐Liquid Slug Flow

Gas‐liquid‐liquid slug flow in a capillary reactor is a promising new concept that allows one to incorporate gas‐liquid reaction, liquid‐liquid extraction, and facile catalyst separation in a single unit. In order to assess the performance of a gas‐liquid‐liquid slug flow reactor, it is necessary to predict the slug velocity and pressure drop to ascertain residence times and reaction rates. New empirical models for velocity and pressure drop were developed based on existing models for two‐phase gas‐liquid and liquid‐liquid slug flows, and these were validated experimentally.     

Field‐based robotic phenotyping of sorghum plant architecture using stereo vision

Sorghum (Sorghum bicolor) is known as a major feedstock for biofuel production. To improve its biomass yield through genetic research, manually measuring yield component traits (e.g. plant height, stem diameter, leaf angle, leaf area, leaf number, and panicle size) in the field is the current best practice. However, such laborious and time‐consuming tasks have become a bottleneck limiting experiment scale and data acquisition frequency. This paper presents a high‐throughput field‐based robotic phenotyping system which performed side‐view stereo imaging for dense sorghum plants with a wide range of plant heights throughout the growing season. Our study demonstrated the suitability of stereo vision for field‐based three‐dimensional plant phenotyping when recent advances in stereo matching algorithms were incorporated. A robust data processing pipeline was developed to quantify the variations or morphological traits in plant architecture, which included plot‐based plant height, plot‐based plant width, convex hull volume, plant surface area, and stem diameter (semiautomated). These image‐derived measurements were highly repeatable and showed high correlations with the in‐field manual measurements. Meanwhile, manually collecting the same traits required a large amount of manpower and time compared to the robotic system. The results demonstrated that the proposed system could be a promising tool for large‐scale field‐based high‐throughput plant phenotyping of bioenergy crops.     

Organic Additives for the Enhancement of Laminar Flow in a Brain‐Vessels‐Like Microchannel Assembly

Organic polymers were extracted from okra, aloe vera, and hibiscus leaves and used as drag‐reducing additives (DRAs) to enhance the laminar flow in custom‐made microchannels that simulate the human brain vessels. The experiment was conducted using an open‐loop microfluidic system. The flow enhancement performance was evaluated as the function of percentage of flow increment of mucilage additives at different concentrations. Okra mucilage showed greater flow enhancement performance at higher mucilage concentration while both aloe vera and hibiscus mucilage performed better at lower additive concentration. The findings prove the potential of these organic polymers as DRAs to enhance the blood flow.     

Stochastic grid bundling method for backward stochastic differential equations

ABSTRACT

In this work, we apply the Stochastic Grid Bundling Method (SGBM) to numerically solve backward stochastic differential equations (BSDEs). The SGBM algorithm is based on conditional expectations approximation by means of bundling of Monte Carlo sample paths and a local regress-later regression within each bundle. The basic algorithm for solving the backward stochastic differential equations will be introduced and an upper error bound is established for the local regression. A full error analysis is also conducted for the explicit version of our algorithm and numerical experiments are performed to demonstrate various properties of our algorithm.     

Metrics-based profiling of university research engagement with Africa: research management,gender, and internationalization perspective

Scientometrics - U.S. university engagement with Africa in various areas including global health, education, environment, and agriculture has grown in the last 15 years. However, there is...     

Chemotherapy drugs derived nanoparticles encapsulating mRNA encoding tumor suppressor proteins to treat triple-negative breast cancer

Triple-negative breast cancer (TNBC) is one type of the most aggressive breast cancers with poor prognosis. It is of great urgency to develop new therapeutics for treating TNBC. Based on current treatment guideline and genetic information of TNBC, a combinational therapy platform integrating chemotherapy drugs and mRNA encoding tumor suppressor proteins may become an efficacious strategy. In this study, we developed paclitaxel amino lipid (PAL) derived nanoparticles (NPs) to incorporate both chemotherapy drugs and P53 mRNA. The PAL P53 mRNA NPs showed superior properties compared to Abraxane^® and Lipusu^® used in the clinic including high paclitaxel loading capacity (24 wt.%, calculated by paclitaxel in PAL), PAL encapsulation efficiency (94.7% ± 6.8%) and mRNA encapsulation efficiency (88.7% ± 0.7%). Meanwhile, these NPs displayed synergetic cytotoxicity of paclitaxel and P53 mRNA in cultured TNBC cells. More importantly, we demonstrated in vivo anti-tumor efficacy of PAL P53 mRNA NPs in an orthotopic TNBC mouse model. Overall, these chemotherapy drugs derived mRNA NPs provide a new platform to integrate chemotherapy and personalized medicine using tumor genetic information, and therefore represent a promising approach for TNBC treatment.