2-Phenyloxazole-4-carboxamide as a Scaffold for Selective Inhibition of Human Monoamine Oxidase B

A series of 2-phenyloxazoles bearing an amide group at position 4 were designed and synthesized for evaluation as potential inhibitors of human recombinant monoamine oxidases (hrMAOs). Results of kinetics experiments demonstrated that all compounds behave as competitive MAO inhibitors, with good selectivity toward the MAO-B isoform. The most potent and selective derivatives are characterized by inhibition constant (K_i) values in the sub-micromolar range and a good selectivity index (K_{i MAO-A}/K_{i MAO-B}>50). Some derivatives were also found to be able to inhibit MAO activity in nerve growth factor (NGF)-differentiated PC12 cells, taken as a model of neuronal cells. In particular, 2-(2-hydroxyphenyl)-N-phenyloxazole-4-carboxamide (compound 4 a ) may be a promising new scaffold, exerting the highest selectivity and inhibitory effect toward MAOs in NGF-differentiated PC12 cell lysates, without compromising cell viability. Molecular docking analysis allowed a rationalization of the experimentally observed binding affinity and selectivity.     

Separation of hematite from banded hematite jasper (BHJ) by magnetic coating

The separation of iron oxide from banded hematite jasper(BHJ) assaying 47.8% Fe, 25.6% Si O2 and 2.30%Al2O3 using selective magnetic coating was studied. Characterization studies of the low grade ore indicate that besides hematite and goethite,jasper, a microcrystalline form of quartzite, is the major impurity associated with this ore. Beneficiation by conventional magnetic separation technique could yield a magnetic concentrate containing 60.8% Fe with 51% Fe recovery. In order to enhance the recovery of the iron oxide minerals, fine magnetite, colloidal magnetite and oleate colloidal magnetite were used as the coating material. When subjected to magnetic separation, the coated ore produces an iron concentrate containing 60.2% Fe with an enhanced recovery of56%. The AFM studies indicate that the coagulation of hematite particles with the oleate colloidal magnetite facilitates the higher recovery of iron particles from the low grade BHJ iron ore under appropriate conditions.     

Coupling in situ experiments and modeling – Opportunities for data fusion,machine learning,and discovery of emergent behavior

This paper reviews recent studies, that not only includes both experiments and modeling components, but celebrates a close coupling between these techniques, in order to provide insights into the plasticity and failure of polycrystalline metals. Examples are provided of studies across multiple-scales, including, but not limited to, density functional theory combined with atom probe tomography, molecular dynamics combined with in situ transmission electron miscopy, discrete dislocation dynamics combined with nanopillars experiments, crystal plasticity combined with digital image correlation, and crystal plasticity combined with in situ high energy X-ray diffraction. The close synergy between in situ experiments and modeling provides new opportunities for model calibration, verification, and validation, by providing direct means of comparison, thus removing aspects of epistemic uncertainty in the approach. Further, data fusion between in situ experimental and model-based data, along with data driven approaches, provides a paradigm shift for determining the emergent behavior of deformation and failure, which is the foundation that underpins the mechanical behavior of polycrystalline materials.     

Three‐dimensional color prediction modeling of single‐ and double‐layered woven fabrics

In this research, the three‐dimensional structural and colorimetric modeling of three‐dimensional woven fabrics was conducted for accurate color predictions. One‐hundred forty single‐ and double‐layered woven samples in a wide range of colors were produced. With the consideration of their three‐dimensional structural parameters, three‐dimensional color prediction models, K/S‐, R‐, and L*a*b*‐based models, were developed through the optimization of previous two‐dimensional models which have been reported to be the three most accurate models for single‐layered woven structures. The accuracy of the new three‐dimensional models was evaluated by calculating the color differences ΔL*, ΔC*, Δh°, and ΔE_CMC(2:1) between the measured and the predicted colors of the samples, and then the error values were compared to those of the two‐dimensional models. As a result, there has been an overall improvement in color predictions of all models with a decrease in ΔE_CMC(2:1) from 10.30 to 5.25 units on average after the three‐dimensional modeling.     

Study of MW-scale biogas-fed SOFC-WGS-TSA-PEMFC hybrid power technology as distributed energy system: Thermodynamic,exergetic and thermo-economic evaluation

Advanced biogas power generation technology has been attracting attentions, which contributes to the waste disposal and the mitigation of greenhouse gas emissions. This work proposes and models a novel biogas-fed hybrid power generation system consisting of solid oxide fuel cell, water gas shift reaction, thermal swing adsorption and proton exchange membrane fuel cell (SOFC-WGS-TSA-PEMFC). The thermodynamic, exergetic, and thermo-economic analyses of this hybrid system for power generation were conducted to comprehensively evaluate its performance. It was found that the novel biogas-fed hybrid system has a gross energy conversion efficiency of 68.63% and exergy efficiency of 65.36%, indicating high efficiency for this kind of hybrid power technology. The market sensitivity analysis showed that the hybrid system also has a low sensitivity to market price fluctuation. Under the current subsidy level for the distributed biogas power plant, the levelized cost of energy can be lowered to 0.02942 $/kWh for a 1 MW scale system. Accordingly, the payback period and annual return on investment can reach 1.4 year and about 20%, respectively. These results reveal that the proposed hybrid system is promising and economically feasible as a distributed power plant, especially for the small power scale (no more than 2 MW).     

Towards optimization of the osmotic drying process of alumina-gelatin objects: Regression analysis and verification

In this study, further analysis of the osmotic drying process was conducted to identify the optimum combination of parameters for drying rectangular alumina-gelatin beams. This study was designed to determine the effect of three variables related to the osmotic drying process (osmotic pressure, molecular weight, and immersion time) on the interaction between the liquid desiccant and the submerged alumina-gelatin samples. The water loss from the alumina-gelatin samples was positively correlated with the molecular weight, osmotic pressure, and immersion time. Up to 40% by weight of the initial water content was removed during the osmotic drying process. The samples also experienced solids gain due to the counterflow of solute from the liquid desiccant. The least amount of solids gain resulted from drying for the shortest immersion time at low osmotic pressure and high molecular weight. Evidence of possible interactions between variables was noted for the sintered density metric. Statistical methods were used to form regression equations for the measured responses (water loss, solids gain, bulk density). A verification experiment was conducted to compare the experimental outcomes to the predicted outcomes. The responses were simultaneously optimized to identify the combination of variable settings required to meet specified goals. In order to maximize water loss, minimize solids gain, and maximize bulk density, the ceramic-gelatin object should be immersed for approximately 60?min in an aqueous solution of 100,000?g/mol poly(ethylene oxide) at an osmotic pressure of 2.50?MPa. These values are valid for the range of parameter settings tested and the sample fabrication and drying methods used.     

The roles of conceptual modelling in improving construction simulation studies: A comprehensive review

The conceptual modelling phase of simulation studies has proven to be effective in enhancing the impact of simulation modelling in different domains. However, this simulation phase did not receive much attention in the construction simulation domain. The objective of this paper is to identify the roles that conceptual modelling can play in advancing the engagement, accuracy, and adoption (among other things) of discrete-event simulation studies in construction. In this paper, a Systematic Literature Review (SLR) is conducted, which involves a comprehensive search of databases and researchers’ profiles to identify journal papers, conference articles, books, and theses that have reported the benefits of conceptual modelling for discrete-event simulation studies. The review resulted in 82 documents that were published from 2000 to 2020. Results indicate that the benefits of conceptual modelling include facilitating communications between stakeholders, capturing sufficient information for the simulation model, improving the quality of simulation models, guiding other simulation modelling activities, and facilitating verification and validation of simulation models. By linking these benefits to the current research agenda in construction simulation, this paper shows the significance and potential of the conceptual modelling phase to enhance the impact of discrete-event simulation studies in construction.