Reversible switching of room temperature ferromagnetism in CeO2-Co nanoparticles

We investigated the reversible ferromagnetic (FM) behavior of pure and Co doped CeO2 nanopowders. The as-sintered samples displayed an increasing paramagnetic contribution upon Co doping. Room temperature FM is obtained simply by performing thermal treatments in vacuum at temperatures as low as 500^{\circ}C and it can be switched off by performing thermal treatments in oxidizing conditions. The FM contribution is enhanced as we increase the time of the thermal treatment in vacuum. Those systematic experiments establish a direct relation between ferromagnetism and oxygen vacancies and open a path for developing materials with tailored properties.Comment: 20 pages, 3 figures; Applied Physics Letters Vol. 100, Issue 17, APR201

Carbon Dioxide Injection for Hypervelocity Boundary Layer Stability

An approach for introducing carbon dioxide as a means or stabilizing a hypervelocity boundary layer over a slender bodied vehicle is investigated through the use of numerical simulations. In the current study, two different test bodies are examined. The first is a five-degree-half-angle cone currently under research at the GALCIT T5 Shock Tunnel with a 4 cm porous wall insert used to transpire gas into the boundary layer. The second test body is a similar cone with a porous wall over a majority of cone surface. Computationally, the transpiration is performed using an axi-symmetric flow simulation with wall-normal blowing. The effect of the injection and the transition location are gauged by solving the parabolized stability equations and using the semi-empirical e^N method. The results show transition due to the injection for the first test body and a delay in the transition location for the second test body as compared to a cone without injection under the same flight conditions. The mechanism for the stabilizing effect of carbon dioxide is also explored through selectively applying non-equilibrium processes to the stability analysis. The results show that vibrational non-equilibrium plays a role in reducing disturbance amplification; however, other factors also contribute

Carbon Dioxide Injection for Hypervelocity Boundary Layer Stability

An approach for introducing carbon dioxide as a means or stabilizing a hypervelocity boundary layer over a slender bodied vehicle is investigated through the use of numerical simulations. In the current study, two different test bodies are examined. The first is a five-degree-half-angle cone currently under research at the GALCIT T5 Shock Tunnel with a 4 cm porous wall insert used to transpire gas into the boundary layer. The second test body is a similar cone with a porous wall over a majority of cone surface. Computationally, the transpiration is performed using an axi-symmetric flow simulation with wall-normal blowing. The effect of the injection and the transition location are gauged by solving the parabolized stability equations and using the semi-empirical e^N method. The results show transition due to the injection for the first test body and a delay in the transition location for the second test body as compared to a cone without injection under the same flight conditions. The mechanism for the stabilizing effect of carbon dioxide is also explored through selectively applying non-equilibrium processes to the stability analysis. The results show that vibrational non-equilibrium plays a role in reducing disturbance amplification; however, other factors also contribute

A Comparison of Machine Learning and Classical Demand Forecasting Methods: A Case Study of Ecuadorian Textile Industry

[EN] This document presents a comparison of demand forecasting methods, with the aim of improving demand forecasting and with it, the production planning system of Ecuadorian textile industry. These industries present problems in providing a reliable estimate of future demand due to recent changes in the Ecuadorian context. The impact on demand for textile products has been observed in variables such as sales prices and manufacturing costs, manufacturing gross domestic product and the unemployment rate. Being indicators that determine to a great extent, the quality and accuracy of the forecast, generating also, uncertainty scenarios. For this reason, the aim of this work is focused on the demand forecasting for textile products by comparing a set of classic methods such as ARIMA, STL Decomposition, Holt-Winters and machine learning, Artificial Neural Networks, Bayesian Networks, Random Forest, Support Vector Machine, taking into consideration all the above mentioned, as an essential input for the production planning and sales of the textile industries. And as a support, when developing strategies for demand management and medium-term decision making of this sector under study. Finally, the effectiveness of the methods is demonstrated by comparing them with different indicators that evaluate the forecast error, with the Multi-layer Neural Networks having the best results with the least error and the best performance.The authors are greatly grateful by the support given by the SDAS Research Group (https://sdas-group.com/).Lorente-Leyva, LL.; Alemany Díaz, MDM.; Peluffo-Ordóñez, DH.; Herrera-Granda, ID. (2021). 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Wiley, Hoboken (2015)Murray, P.W., Agard, B., Barajas, M.A.: Forecast of individual customer’s demand from a large and noisy dataset. Comput. Ind. Eng. 118, 33–43 (2018). https://doi.org/10.1016/j.cie.2018.02.007Bruzda, J.: Quantile smoothing in supply chain and logistics forecasting. Int. J. Prod. Econ. 208, 122–139 (2019). https://doi.org/10.1016/j.ijpe.2018.11.015Bajari, P., Nekipelov, D., Ryan, S.P., Yang, M.: Machine learning methods for demand estimation. Am. Econ. Rev. 105, 481–485 (2015). https://doi.org/10.1257/aer.p20151021Villegas, M.A., Pedregal, D.J., Trapero, J.R.: A support vector machine for model selection in demand forecasting applications. Comput. Ind. Eng. 121, 1–7 (2018). https://doi.org/10.1016/j.cie.2018.04.042Herrera-Granda, I.D., et al.: Artificial neural networks for bottled water demand forecasting: a small business case study. In: Rojas, I., Joya, G., Catala, A. (eds.) IWANN 2019. LNCS, vol. 11507, pp. 362–373. 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Pharmacological Properties of Chalcones: A Review of Preclinical Including Molecular Mechanisms and Clinical Evidence

Chalcones are among the leading bioactive flavonoids with a therapeutic potential implicated to an array of bioactivities investigated by a series of preclinical and clinical studies. In this article, different scientific databases were searched to retrieve studies depicting the biological activities of chalcones and their derivatives. This review comprehensively describes preclinical studies on chalcones and their derivatives describing their immense significance as antidiabetic, anticancer, anti-inflammatory, antimicrobial, antioxidant, antiparasitic, psychoactive, and neuroprotective agents. Besides, clinical trials revealed their use in the treatment of chronic venous insufficiency, skin conditions, and cancer. Bioavailability studies on chalcones and derivatives indicate possible hindrance and improvement in relation to its nutraceutical and pharmaceutical applications. Multifaceted and complex underlying mechanisms of chalcone actions demonstrated their ability to modulate a number of cancer cell lines, to inhibit a number of pathological microorganisms and parasites, and to control a number of signaling molecules and cascades related to disease modification. Clinical studies on chalcones revealed general absence of adverse effects besides reducing the clinical signs and symptoms with decent bioavailability. Further studies are needed to elucidate their structure activity, toxicity concerns, cellular basis of mode of action, and interactions with other molecules

Dynamics of Tachyon and Phantom Field beyond the Inverse Square Potentials

We investigate the cosmological evolution of the tachyon and phantom-tachyon scalar field by considering the potential parameter $\Gamma$($=\frac{V V"}{V'^2}$) as a function of another potential parameter $\lambda$($=\frac{V'}{\kappa V^{3/2}}$), which correspondingly extends the analysis of the evolution of our universe from two-dimensional autonomous dynamical system to the three-dimension. It allows us to investigate the more general situation where the potential is not restricted to inverse square potential and .One result is that, apart from the inverse square potential, there are a large number of potentials which can give the scaling and dominant solution when the function $\Gamma(\lambda)$ equals $3/2$ for one or some values of $\lambda_{*}$ as well as the parameter $\lambda_{*}$ satisfies condition Eq.(18) or Eq.(19). We also find that for a class of different potentials the dynamics evolution of the universe are actually the same and therefore undistinguishable.Comment: 8 pages, no figure, accepted by The European Physical Journal C(2010), online first, http://www.springerlink.com/content/323417h708gun5g8/?p=dd373adf23b84743b523a3fa249d51c7&pi=