Results 1 - 10 of 1626
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[en] In order to overcome the difficulty of choosing appropriate grading parameters of filling material for mines which are using filling mining method, the fractal theory is introduced, and a fractal equation of grading is built to represent gradation. Meanwhile taken Dahongshan copper mine as an example to discuss the relationship between fractal dimension and porosity, cementing strength under different parameters. A prediction model of cementing strength is built based on the experimental data, and the results show that the optimal grading parameters of Dahongshan copper mine is fractal dimension = 2.82. The optimized grading parameters of filling material in Dahongshan run steady, which greatly reduced the filling cost. (paper)
[en] In this paper we take advantage of technological advances and use high frequency multidimensional textual news data available in the internet and propose a new index of inflation expectations. We utilize the power of text mining and its ability to convert large collections of text from unstructured to structured form for in-depth quantitative and qualitative analysis of Guardian news data. Main contribution of his paper is to explore online news as novel data source to capture the inflation expectations in real time. We do so by building an index of inflation expectations and capture the intensity and uncertainty of expectations as well as the quantitative value. The preliminary results show that the new inflation index is correlated with the actual inflation dynamics. Moreover, the inflation news precedes actual inflation by a few months. To validate our results, we build a linear regression using our newly built indices and market-based inflation expectations and confirm that our methodology results in a model with good forecasting power.
[en] Highlights: • Capillary filling kinetics of deionized water in nanochannels with heights of 50–120 nm were studied. • The position of the moving meniscus was proportional to the square root of time, as predicted by the classical LW equation. • The extracted slopes were significantly smaller than the predictions based on the bulk properties. • This unusual behavior at nanoscale was found to be mainly caused by the electro-viscous effect and dynamic contact angle. We investigated the capillary filling kinetics of deionized water in nanochannels with heights of 50–120 nm. The measured position of the moving meniscus was proportional to the square root of time, as predicted by the LW equation. However, the extracted slopes were significantly smaller than the predictions based on the bulk properties. This unusual behavior was found to be mainly caused by the electro-viscous effect and dynamic contact angle, which was significantly larger than the static angle. In addition, when the filling distance reached about 600 μm, bubbles tended to be formed, leading to the main meniscus was almost immobile.
[en] A kinematic model based on the superposition of p + p collisions, relativistic geometry and final-state hadronic rescattering is used to predict two-boson HBT parameters in √sNN = 2.76 TeV Pb + Pb collisions. A short proper time for hadronization is assumed. Previous calculations using this model which were performed for √sNN = 200 GeV Au + Au collisions were shown to describe reasonably well the trends of two-pion HBT in experiments carried out at that energy, giving the present predictions for Pb + Pb at higher energy some degree of credibility.
[en] In this contribution to the J. Phys.: Condens. Matter memorial issue in honor of Sandro Massidda I reflect on a phenomenon Sandro had been a part of. While theoretical condensed matter physicists have made, over the years, exciting and most elegant contributions to the theory of superconductivity (which, in and by itself, is one of the most beautiful constructs in theoretical physics), some of them of utmost importance, they have had less success in predicting and explaining superconducting states and mechanisms in specific materials. More down-to-earth computational materials scientists, who often go by the moniker ‘band theorists’, have been much more successful in applying (usually other people’s) ideas in such circumstances. In this essay I give some examples, largely drawn from my own experience, and speculate on their meaning. (paper)
[en] A quantitative model for the size-dependent Young’s modulus Y(D) of nanomaterials is established in this work by considering the modulus of single bond and bond number in nanomaterials. Due to bond relaxation, the single bond strength and it’s elastic modulus are enhanced as size drops, while bond number is decreased. This makes the Young’s moduli of nanomaterials possess different change with size. If compared with bulk Young’s modulus Y0, both the stiffer with Y(D) > Y0 and the softer with Y(D) < Y0 for different nanomaterials are predicted. The corresponding experimental or simulation results show their good consistence with the model predictions, which greatly confirms the reasonability of the established model. (paper)
[en] This paper applies Gaussian processes classification to predict recessions one year ahead. It shows that while the commonly used probit model can produce poorly calibrated estimates in this case, replacing the single index assumption of the probit model with a Gaussian processes model provides estimates that are well calibrated. Results from Gaussian process models restricted to be monotonically related to the indicator imply that breaking the monotonicity assumption and not just the linearity assumption of a single index model is required for well calibrated conditional probability estimates.
[en] We develop a class of tests for the structural stability of infinite order regression models, when the time of a structural change is unknown. Examples include the infinite order autoregressive model, the nonparametric sieve regression and many others whose dimensions grow to infinity. When the number of parameters diverges, the traditional tests such as the supremum of Wald, LM or LR statistic or their exponentially weighted averages diverge as well. However, we show that a suitable transformation of these tests converges to a proper weak limit as the sample size n and the dimension p grow to infinity simultaneously. In general, this limit distribution is different from the sequential limit, which can be obtained by increasing the order p of the standardized tied-down Bessel process in Andrews (1993). More interestingly, our joint asymptotic analysis discovers that the joint asymptotic distribution depends on a higher order serial correlation. We also establish a weighted power optimality property of our tests under certain regularity conditions. A new result on partial sums of random matrices is established. We examine finite-sample performance in a Monte Carlo study and illustrate the test with a number of empirical examples.
[en] This paper builds and implements multifactor stochastic volatility models. The main objective is volatility prediction and its relevance for equity markets. The paper outlines stylised facts from volatility literature showing density tails, persistence, mean reversion, asymmetry and long memory, all contributing to systematic dependencies. Applying long simulations from stochastic volatility (SV) models and filter volatility using a form of nonlinear Kalman filtering, the un observables of the nonlinear latent variables can be forecasted with associated fit characteristics. The paper uses European equity data from United Kingdom (Ftse100) and Norway (Equinor) for relevance arguments and illustrational prediction purposes. Multifactor SV models seem to enrich volatility predictions empowering equity market relevance.