RESUMEN

The Cartesian coordinate system is not sufficient to study wave propagation on the coastline or in the sea where the terrain is extremely complicated, so it is necessary to study it in an unconventional coordinate system, fractals. In this paper, from the governing equations of fluid, the fractional nonlinear Schrödinger equation is derived to describe the evolution of Rossby waves in fractal by using multi-scale analysis and perturbation method. Based on the equation, the rogue-wave solution is obtained by the integral preserving transformation to explain some serious threats at sea.

RESUMEN

Some automotive companies develop battery electric vehicles (BEVs) with an ultra-long range to address consumers' range anxiety. However, ultra-long-range BEVs have many problems, and whether they can truly solve consumers' range anxiety has not been studied. Thus, we build a technology-rich, bottom-up approach model to evaluate BEVs' performance, economy, and total cost of ownership (TCO) to reveal the necessity of developing ultra-long-range BEVs. The results show that the ultra-long-range BEVs' dynamic, safety, and economy performances are poor compared to short-range BEVs. Based on the TCO analysis considering battery replacement and alternative transportation costs, 400 km is the optimal range of BEVs for consumers. In addition, consumers' range anxiety is essentially anxiety about energy replenishment. Ultra-long-range BEV cannot really solve consumers' range anxiety except by reducing charging frequency. In the case of gradually improving the charging and swapping infrastructure, we believe that automotive companies do not need to develop ultra-long-range BEVs.

RESUMEN

Flying cars, essentially vertical takeoff and landing aircraft (VTOL), are an emerging, disruptive technology that is expected to reshape future transportation. VTOLs can be powered by battery electric, fuel cell, or internal combustion engine, which point to entirely different needs for industry expertise, research & development, supply chain, and infrastructure supports. A pre-analysis of the propulsion technology competition is crucial to avoid potential wrong directions of research, investment, and policy making efforts. In this study, we comprehensively examined the cost competitiveness of the three propulsion technologies. Here we show that battery electric has already become the lowest-cost option for below-200-km VTOL applications, covering intra-city and short-range inter-city travels. This cost advantage can be robustly strengthened in the long term under various technology development scenarios. Battery energy density improvement is the key to reducing cost. In particular, a 600 Wh/kg battery energy density provides battery electric with all-range cost advantage, and promises high return in business. Fuel cell and internal combustion engine, under certain technology development scenarios, can obtain cost advantage in long-range applications, but face intense competition from ground transportation such as high-speed rail. The findings suggest a battery-electric-prioritized VTOL development strategy, and the necessity of developing VTOL-customized high-energy-density batteries.

RESUMEN

Rapidly and accurately detect the total nitrogen (TN) concentration is enormously important for surface water protection considering the critical role it plays in reflecting the eutrophication of surface water. However, traditional TN detection methods have to experience a tedious oxygen digestion process, which tremendously limits the detection speed of TN. To solve this problem, we propose a novel online rapid TN detection method. The transformations of nitrogenous substances during the oxidative digestion process are observed by using ultraviolet (UV) spectroscopy and the concentration of TN can be predicted by only using the variation of spectrum in the early oxygen digestion process. To select the most informative variables hidden in the collected three-dimension spectrum, a new wavelength selection algorithm called spatial interval permutation combination population analysis (siPCPA) is proposed, which considers the spatial-temporal relationships among each variable in the spectrum. By using the real surface water samples collected from Houhu Lake, Changsha, China, the effectiveness of our proposed new detection and selection methods are verified and compared with other state-of-the-art methods. As a result, the practical application experiment shows that our methods can determine the concentration of TN in 5 min with a relative error of less than 5%.

Asunto(s)

Nitrógeno , Contaminantes Químicos del Agua , China , Monitoreo del Ambiente/métodos , Lagos , Nitrógeno/análisis , Oxígeno , Fósforo , Agua/análisis , Contaminantes Químicos del Agua/análisis

RESUMEN

As one of the most important preprocessing procedures in spectral detection, wavelength selection approaches play an irreplaceable role in reducing the model overfitting and prediction errors. In this paper, we propose a two-step wavelength selection method called interval permutation combination population analysis (iPCPA), which improves the selective performance by combining three different wavelength selection algorithms. First, interval partial least squares (iPLS) is used as the rough selection step to efficiently exclude the uninformative variables in the spectrum, which reduces the variable space and ensures that the following selection step can focus on selecting informative variables. Then, permutation combination population analysis (PCPA) is proposed, which introduces the core idea of permutation analysis into the variable combination population analysis (VCPA) and hence improves its ability in evaluating the importance of informative variables. Six state-of-the-art wavelength selection methods are used to compare with iPCPA and their performances are tested by using three real spectral datasets: corn, beer, and soil datasets. The final experimental results prove that iPCPA has the best predictive abilities, combined with a good selective performance.