Optical solitons to the nonlinear Shrödinger’s equation with spatio-temporal dispersion using complex amplitude ansatz

In this work, we investigate the optical solitons to the non-linear Shrödinger’s equation with spatio-temporal dispersion. There are two types of non-linear media studied in this paper. They are Kerr law and parabolic law. By adopting a complex amplitude ansatz method composed of the addition of bright and dark optical solitons, we present the exact dark, bright and dark-bright or combined optical solitons to the model. Numerical results and discussions are also presented.     

Designing,modeling and performance investigation of bio-inspired flow field based DMFCs

In an attempt to improve upon conventional flow fields (e.g., serpentine flow field), Murray's Law was applied to design two different bio-inspired, leaf-shaped flow fields. This law governs the dimensions of natural networks, such as: the veins within plant leaves and human lungs. In this study, the serpentine, the lung, and the two leaf-shaped flow fields were used to form seven different anode–cathode combinations. The experiments focused on the effects of methanol concentration (0.50 M, 0.75 M, and 1.00 M) and the combined effect of methanol and oxygen flow rates (1.3 ml/min methanol and 400 ml/min oxygen, as well as 2 and 3 times both of these flow rates). An analytical model was also developed to help understand the experimental results. The results show that the highest performance could be achieved when the bio-inspired configurations were used on the cathode. The best configuration was the serpentine (anode) – second leaf design (cathode), with a peak power density of 888 W/m². For comparison, a peak power density of 824 W/m² was achieved when the serpentine flow field was used on the anode and cathode. Furthermore, of all the tested configurations, the lung-based flow field provided the lowest performance in all tests.     

Solid‐phase extraction and spectrophotometric determination of Allura Red (E129) in foodstuff,soft drink,syrup and energy drink samples: a comparison study

Amberlite XAD‐7 and XAD‐8 resins were used as adsorbents for preconcentration and determination of Allura Red (AR) food dye in aqueous medium. The effects of pH, sample volume, sample and eluent flow rates on the extraction of AR were optimised. The determination of dye was performed at 506.0 nm using spectrophotometry. Interference effects of matrix ions and some dyes were also investigated under optimised conditions. The methods permitted low detection limits which were 1.2 and 0.6 μg L^?1 for XAD‐7 and XAD‐8, respectively. Adsorption behaviours were investigated by adsorption isotherms and zero charge pH experiments. Validations of the method were performed by determination of AR contents in some foodstuffs. AR contents of liquid samples were found between 58 and 440 μg mL^?1. AR concentrations of solid samples were between 416 and 432 μg g^?1. The XAD‐7 and XAD‐8 resins presented a fast and reliable potential to determine AR dye in real samples.     

Evidence-based uncertainty sampling for active learning

Active learning methods select informative instances to effectively learn a suitable classifier. Uncertainty sampling, a frequently utilized active learning strategy, selects instances about which the model is uncertain but it does not consider the reasons for why the model is uncertain. In this article, we present an evidence-based framework that can uncover the reasons for why a model is uncertain on a given instance. Using the evidence-based framework, we discuss two reasons for uncertainty of a model: a model can be uncertain about an instance because it has strong, but conflicting evidence for both classes or it can be uncertain because it does not have enough evidence for either class. Our empirical evaluations on several real-world datasets show that distinguishing between these two types of uncertainties has a drastic impact on the learning efficiency. We further provide empirical and analytical justifications as to why distinguishing between the two uncertainties matters.