35 research outputs found
Recommended from our members
Wetting behaviour and reactivity between liquid Gd and ZrO2 substrate
The wetting behavior and reactivity between molten pure Gd and polycrystalline 3YSZ substrate (ZrO2 stabilized with 3 wt% of Y2O3)were experimentally determined by a sessile drop method using a classical contact heating coupled with drop pushing procedure. The test was performed under an inert flowing gas atmosphere (Ar) at two temperatures of 1362°C and 1412°C. Immediately after melting (Tm=1341°C), liquid Gd did not wet the substrate forming a contact angle of Ξ=141°. The non-wetting to wetting transition (Ξ < 90°) took place after about 110 seconds of interaction and was accompanied by a sudden decrease in the contact angle value to 67°. Further heating of the couple to 1412 °C did not affect wetting (Ξ=67°±1°). The solidified Gd/3YSZ couple was studied by means of optical microscopy and scanning electron microscopy coupled with X-ray energy dispersive spectroscopy. Structural investigations revealed that the wettability in the Gd/3YSZ system is of a reactive nature associated with the formation of a continuous layer of a wettable reaction product Gd2Zr2O7
Wettability and reactivity of ZrB2 substrates with liquid Al
Wetting characteristics of the Al/ZrB2 system were experimentally determined by the sessile drop method with application of separate heating of the ZrB2 and Al samples and combined with in situ cleaning of Al drop from native oxide film directly in vacuum chamber. The tests were performed in ultrahigh vacuum of 10â6 mbar at temperatures 710, 800, and 900 °C as well as in flowing inert gas (Ar) atmosphere at 1400 °C. The results evidenced that liquid Al does not wet ZrB2 substrate at 710 and 800 °C, forming high contact angles (Ξ) of 128° and 120°, respectively. At 900 °C, wetting phenomenon (Ξ < 90°) occurs in 29th minute and the contact angle decreases monotonically to the final value of 80°. At 1400 °C, wetting takes place immediately after drop deposition with a fast decrease in the contact angle to 76°. The solidified Al/ZrB2 couples were studied by scanning and transmission electron microscopy coupled with x-ray energy diffraction spectroscopy. Structural characterization revealed that only in the Al/ZrB2 couple produced at the highest temperature of 1400 °C new phases (Al3Zr, AlB2 and α-Al2O3) were formed
Experimentally feasible measures of distance between quantum operations
We present two measures of distance between quantum processes based on the
superfidelity, introduced recently to provide an upper bound for quantum
fidelity. We show that the introduced measures partially fulfill the
requirements for distance measure between quantum processes. We also argue that
they can be especially useful as diagnostic measures to get preliminary
knowledge about imperfections in an experimental setup. In particular we
provide quantum circuit which can be used to measure the superfidelity between
quantum processes.
As the behavior of the superfidelity between quantum processes is crucial for
the properties of the introduced measures, we study its behavior for several
families of quantum channels. We calculate superfidelity between arbitrary
one-qubit channels using affine parametrization and superfidelity between
generalized Pauli channels in arbitrary dimensions. Statistical behavior of the
proposed quantities for the ensembles of quantum operations in low dimensions
indicates that the proposed measures can be indeed used to distinguish quantum
processes.Comment: 9 pages, 4 figure
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 DĂaz, MDM.; Peluffo-Ordóñez, DH.; Herrera-Granda, ID. (2021). A Comparison of Machine Learning and Classical Demand Forecasting Methods: A Case Study of Ecuadorian Textile Industry. Lecture Notes in Computer Science. 131-142. https://doi.org/10.1007/978-3-030-64580-9_11S131142Silva, P.C.L., Sadaei, H.J., Ballini, R., Guimaraes, F.G.: Probabilistic forecasting with fuzzy time series. IEEE Trans. Fuzzy Syst. (2019). https://doi.org/10.1109/TFUZZ.2019.2922152Lorente-Leyva, L.L., et al.: Optimization of the master production scheduling in a textile industry using genetic algorithm. In: PĂ©rez GarcĂa, H., SĂĄnchez GonzĂĄlez, L., CastejĂłn Limas, M., QuintiĂĄn Pardo, H., Corchado RodrĂguez, E. (eds.) HAIS 2019. LNCS (LNAI), vol. 11734, pp. 674â685. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-29859-3_57Seifert, M., Siemsen, E., Hadida, A.L., Eisingerich, A.B.: Effective judgmental forecasting in the context of fashion products. J. Oper. Manag. 36, 33â45 (2015). https://doi.org/10.1016/j.jom.2015.02.001Tratar, L.F., StrmÄnik, E.: Forecasting methods in engineering. IOP Conf. Ser. Mater. Sci. Eng. 657, 012027 (2019). https://doi.org/10.1088/1757-899X/657/1/012027Prak, D., Teunter, R.: A general method for addressing forecasting uncertainty in inventory models. Int. J. Forecast. 35, 224â238 (2019). https://doi.org/10.1016/j.ijforecast.2017.11.004Gaba, A., Tsetlin, I., Winkler, R.L.: Combining interval forecasts. Decis. Anal. 14, 1â20 (2017). https://doi.org/10.1287/deca.2016.0340Zhang, B., Duan, D., Ma, Y.: Multi-product expedited ordering with demand forecast updates. Int. J. Prod. Econ. 206, 196â208 (2018). https://doi.org/10.1016/j.ijpe.2018.09.034Januschowski, T., et al.: Criteria for classifying forecasting methods. Int. J. Forecast. 36, 167â177 (2020). https://doi.org/10.1016/j.ijforecast.2019.05.008Box, G.E., Jenkins, G.M., Reinsel, C., Ljung, M.: Time Series Analysis: Forecasting and Control, 5th edn. Wiley, Hoboken (2015)Murray, P.W., Agard, B., Barajas, M.A.: Forecast of individual customerâs demand from a large and noisy dataset. Comput. Ind. Eng. 118, 33â43 (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, 122â139 (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, 481â485 (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, 1â7 (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. 362â373. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-20518-8_31Dudek, G.: Multilayer perceptron for short-term load forecasting: from global to local approach. Neural Comput. Appl. 32(8), 3695â3707 (2019). https://doi.org/10.1007/s00521-019-04130-ySalinas, D., Flunkert, V., Gasthaus, J., Januschowski, T.: DeepAR: probabilistic forecasting with autoregressive recurrent networks. Int. J. Forecast. (2019). https://doi.org/10.1016/j.ijforecast.2019.07.001Weng, Y., Wang, X., Hua, J., Wang, H., Kang, M., Wang, F.Y.: Forecasting horticultural products price using ARIMA model and neural network based on a large-scale data set collected by web crawler. IEEE Trans. Comput. Soc. Syst. 6, 547â553 (2019). https://doi.org/10.1109/TCSS.2019.2914499Zhang, X., Zheng, Y., Wang, S.: A demand forecasting method based on stochastic frontier analysis and model average: an application in air travel demand forecasting. J. Syst. Sci. Complexity 32(2), 615â633 (2019). https://doi.org/10.1007/s11424-018-7093-0Lorente-Leyva, L.L., et al.: Artificial neural networks for urban water demand forecasting: a case study. J. Phys: Conf. Ser. 1284(1), 012004 (2019). https://doi.org/10.1088/1742-6596/1284/1/012004Scott, S.L., Varian, H.R.: Predicting the present with Bayesian structural time series. Int. J. Math. Model. Numer. Optim. 5, 4â23 (2014). https://doi.org/10.1504/IJMMNO.2014.059942Gallego, V., SuĂĄrez-GarcĂa, P., Angulo, P., GĂłmez-Ullate, D.: Assessing the effect of advertising expenditures upon sales: a Bayesian structural time series model. Appl. Stoch. Model. Bus. Ind. 35, 479â491 (2019). https://doi.org/10.1002/asmb.2460Han, S., Ko, Y., Kim, J., Hong, T.: Housing market trend forecasts through statistical comparisons based on big data analytic methods. J. Manag. Eng. 34 (2018). https://doi.org/10.1061/(ASCE)ME.1943-5479.0000583Lee, J.: A neural network method for nonlinear time series analysis. J. Time Ser. Econom. 11, 1â18 (2019). https://doi.org/10.1515/jtse-2016-0011Trull, O., GarcĂa-DĂaz, J.C., Troncoso, A.: Initialization methods for multiple seasonal holt-winters forecasting models. Mathematics 8, 1â16 (2020). https://doi.org/10.3390/math8020268Biau, G., Scornet, E.: A random forest guided tour. Test 25(2), 197â227 (2016). https://doi.org/10.1007/s11749-016-0481-
On Some Problems in Discrete Wavelet Analysis of Bivariate Spectra with an Application to Business Cycle Synchronization in the Euro Zone
The paper considers some of the problems emerging from discrete wavelet analysis of popular bivariate spectral quantities like the coherence and phase spectra and the frequency-dependent time delay. The approach taken here, introduced by Whitcher and Craigmile (2004), is based on the maximal overlap discrete Hilbert wavelet transform (MODHWT). Firstly, we point at a deficiency in the implementation of the MODHWT and suggest using a modified implementation scheme resembling the one applied in the context of the dual-tree complex wavelet transform of Kingsbury (see Selesnick et al., 2005). Secondly, via a broad set of simulation experiments we examine small and large sample properties of two wavelet estimators of the scale-dependent time delay. The estimators are: the wavelet cross-correlator and the wavelet phase angle-based estimator. Our results provide some practical guidelines for empirical examination of short- and medium-term lead-lag relations for octave frequency bands. Besides, we show how the MODHWT-based wavelet quantities can serve to approximate the Fourier bivariate spectra and discuss certain issues connected with building confidence intervals for them. The discrete wavelet analysis of coherence and phase angle is illustrated with a scale-dependent examination of business cycle synchronization between 11 euro zone member countries. The study is supplemented with wavelet analysis of variance and covariance of the euro zone business cycles. The empirical examination underlines good localization properties and high computational efficiency of the wavelet transformations applied, and provides new arguments in favour of the endogeneity hypothesis of the optimum currency area criteria as well as a wavelet evidence on dating the Great Moderation in the euro zone
Investigating determinants of yawning in the domestic (Equus caballus) and Przewalski (Equus ferus przewalskii) horses
International audienceYawning is rare in herbivores which therefore may be an interesting group to disentangle the potential function(s) of yawning behaviour. Horses provide the opportunity to compare not only animals living in different conditions but also wild versus domestic species. Here, we tested three hypotheses by observing both domestic and Przewalski horses living in semi-natural conditions: (i) that domestic horses may show an elevated rate of yawning as a result of the domestication process (or as a result of life conditions), (ii) that individuals experiencing a higher level of social stress would yawn more than individuals with lower social stress and (iii) that males would yawn more often than females. The study involved 19 Przewalski horses (PHs) and 16 domestic horses (DHs) of different breeds living in large outdoor enclosures. The results showed that there was no difference between the PH and DH in yawning frequency (YF). PHs exhibited much higher levels of social interactions than DHs. There was a positive correlation between yawning frequency and aggressive behaviours in PHs, especially males, supporting the idea that yawning may be associated with more excitatory/stressful social situations. A correlation was found between yawning frequency and affiliative behaviours in DHs, which supports the potential relationship between yawning and social context. Finally, the entire males, but not castrated males, showed much higher levels of yawning than females in both species. The intensity (rather than the valence) of the interaction may be important in triggering yawning, which could therefore be a displacement activity that helps reduce tension
Business Cycle Synchronization of the Visegrad Four and the European Union
In this paper, we map the process of synchronization of the Visegrad Four within the framework of the European Union using the wavelet techniques. In addition, we show that the relationship of output and key macroeconomic indicators is dynamic and varies over time and across frequencies. We study the synchronization applying the wavelet cohesion measure with time-varying weights. This novel approach allows for studying the dynamic relationship among countries from a different perspective than usual timedomain models. Analysing monthly data from 1990 to 2014, the results for the Visegrad region show an increasing co-movement with the European Union after the countries began with preparation for the accession to the European union. The participation in a currency union possibly increases the co-movement. Further, analysing the Visegrad and South European countries' synchronization with the European Union core countries, we find a high degree of synchronization in long-term horizons
Fecal Glucocorticoid Metabolites as Biomarkers in Equids: Assay Choice Matters
From Wiley via Jisc Publications RouterHistory: received 2020-05-06, rev-recd 2021-03-29, accepted 2021-04-09, pub-electronic 2021-06-01Article version: VoRPublication status: PublishedFunder: Royal Society; Id: http://dx.doi.org/10.13039/501100000288; Grant(s): UF110641Funder: Chester Zoo; Id: http://dx.doi.org/10.13039/501100005359; Grant(s): Conservation FellowshipABSTRACT: Free ranging animals are exposed to environmental, demographic, and ecological challenges over time, which can affect their health and fitness. Nonâinvasive biomarkers can provide insight into how animals cope with these challenges and assess the effectiveness of conservation management strategies. We evaluated how free ranging ponies (Equus ferus caballus) on the Carneddau Mountain range, North Wales respond to 2 stimuli: an acute stressor of an annual roundup event in November 2014, and spatial and temporal variation in ecological factors in 2018. We evaluated fecal glucocorticoid metabolites using 2 enzyme immunoassays (EIAs): an 11âoxoetiocholanolone EIA (measuring 11,17âdioxoandrostanes [11,17âDOAs]) and a corticosterone EIA. The former assay has been validated in equids, whereas there is limited evidence for the suitability of the latter. We used an additional parent testosterone EIA to measure fecal androgen metabolites in response to the ecological challenges. Following the roundup, the metabolite concentrations measured by the 2 glucocorticoid EIAs were not correlated. The 11,17âDOAs were elevated from the second day following the roundup and then slowly returned to preâround levels over the next 2 weeks. In contrast, the metabolites measured by the corticosterone assay showed no response to the roundup. For the ecological data, all 3 assays detected a positive correlation between metabolites and social group size in males but not in females. The metabolite concentrations measured by the testosterone and corticosterone assays were highly correlated and were temporally associated with the onset of the breeding season, whereas the 11,17âDOAs were not. The coâvariance of metabolites measured by the corticosterone and testosterone assays, and the lack of an acute response in the corticosterone assay to the roundup, suggests that metabolites detected by the corticosterone assay were not primarily associated with increased glucocorticoid production. We recommend using wellâvalidated fecal biomarker assays of hypothalamusâpituitaryâadrenal axis activity to evaluate and compare the effect of different management interventions and environmental change. © 2021 The Authors. The Journal of Wildlife Management published by Wiley Periodicals LLC on behalf of The Wildlife Society
Recommended from our members
High-Temperature Interaction of Liquid Gd with Y2O3
The sessile drop method combined with contact heating procedure was applied for the investigation of high-temperature interaction between liquid Gd and Y2O3 substrate. Real-time behavior of Gd sample in flowing inert gas (Ar) atmosphere upon heating to and at temperature of 1362 °C was recorded using high-speed high-resolution CCD camera. The results evidenced that molten Gd wets Y2O3 substrate (the contact angle Ξ < 90°) immediately after melting of metal sample observed at T = 1324 °C (Tm = 1312 °C). During the first 3 min of the sessile drop test, the contact angle dropped from Ξ = 52° to Ξ = 24° and then stabilized at the final value of Ξf * = 33°. The solidified Gd/Y2O3 couple was subjected to structural characterization using optical microscopy, scanning electron microscopy coupled with x-ray energy-dispersive spectroscopy. The results evidenced that the wettability in the Gd/Y2O3 system has a reactive nature and the leading mechanism of the interaction between liquid Gd and Y2O3 is the dissolution of the ceramic in the liquid metal responsible for the formation of a deep crater in the substrate under the drop. Therefore, the final contact angle Ξf*, estimated from the side-view drop image, should be considered as an apparent value, compared to the more reliable value of Ξf = 70° measured on the cross section of the solidified couple. © 2019, The Author(s)