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Al–Fe-rare earth (RE) ternary compounds have attracted much attention due to their excellent magnetic properties. Here, the crystal structure and magnetic properties of Al15Fe9RE2 (RE = Gd, Tb) have been focused. Al15Fe9RE2 (RE = Gd, Tb) are tetragonal structured crystals with space group I4/mmm (No. 139, tI26). The lattice constants of Al15Fe9Gd2 are a = 8.7441(1) Å and c = 5.0507(1) Å, and the lattice constants of Al15Fe9Tb2 are a = 8.7333(1) Å and c = 5.0466(1) Å. Under the magnetic field of 50 Oe, the Curie temperatures Tc of Al15Fe9Gd2 and Al15Fe9Tb2 are 347 K and 314 K, respectively. In a magnetic field of − 8 ~ 8 T at the temperature of 2 K, the maximum magnetic moment, remanence (Mr), coercivity (Hc), (BH)max and PH of Al15Fe9Gd2 are 0.5 μB/f.u., 0.32 μB/f.u., 2.19 T, 51.05 MJ/m3 and 81.08 kJ/m3; the maximum magnetic moment of Al15Fe9Tb2 is 2.30 μB/f.u., Mr is 1.29 μB/f.u., Hc is 1.52 T, (BH)max is 51.40 MJ/m3 and PH is 303.09 kJ/m3. In addition, their magnetic characteristics show significant differences at 300 K temperature. The results show that Al15Fe9Tb2 has the larger magnetic moment, remanent magnetization, (BH)max and PH, while Al15Fe9Gd2 has the larger coercivity. [ABSTRACT FROM AUTHOR]

This article considers estimating functional-coefficient models in panel quantile regression with individual effects, allowing the cross-sectional and temporal dependence for large panel observations. A latent group structure is imposed on the heterogeneous quantile regression models so that the number of nonparametric functional coefficients to be estimated can be reduced considerably. With the preliminary local linear quantile estimates of the subject-specific functional coefficients, a classic agglomerative clustering algorithm is used to estimate the unknown group structure and an easy-to-implement ratio criterion is proposed to determine the group number. The estimated group number and structure are shown to be consistent. Furthermore, a post-grouping local linear smoothing method is introduced to estimate the group-specific functional coefficients, and the relevant asymptotic normal distribution theory is derived with a normalization rate comparable to that in the literature. The developed methodologies and theory are verified through a simulation study and showcased with an application to house price data from U.K. local authority districts, which reveals different homogeneity structures at different quantile levels. [ABSTRACT FROM AUTHOR]

The selective broadband absorption of solar radiation plays a crucial role in applying solar energy. However, despite being a decade-old technology, the rapid and precise designs of selective absorbers spanning from the solar spectrum to the infrared region remain a significant challenge. This work develops a high-performance design paradigm that combines deep learning and multi-objective double annealing algorithms to optimize multilayer nanostructures for maximizing solar spectral absorption and minimum infrared radiation. Based on deep learning design, we experimentally fabricate the designed absorber and demonstrate its photothermal effect under sunlight. The absorber exhibits exceptional absorption in the solar spectrum (calculated/measured = 0.98/0.94) and low average emissivity in the infrared region (calculated/measured = 0.08/0.19). This absorber has the potential to result in annual energy savings of up to 1743 kW h/m2 in areas with abundant solar radiation resources. Our study opens a powerful design method to study solar-thermal energy harvesting and manipulation, which will facilitate for their broad applications in other engineering applications. [ABSTRACT FROM AUTHOR]

A new ternary intermetallic compound Al3GaCu9 was synthesized experimentally. A high-quality powder diffraction pattern of the compound was collected by an X-ray diffractometer, and its crystal structure was determined using the Rietveld refinement method. Results show that the compound has a cubic cell with the Al4Cu9 structure type (space group $P\bar{4}3m$ and Pearson symbol cP 52). The lattice parameter a = 8.7132(3) Å, unit-cell volume V = 661.52 Å3, calculated density D calc = 7.26 g/cm3, and Z = 4. The residual factors converge to R p = 2.96%, R wp = 4.06%, and R exp = 2.57%. The experimentally obtained reference intensity ratio value is 7.04. [ABSTRACT FROM AUTHOR]

Compared with traditional alloys, high-entropy alloys (HEAs) have been widely studied because of their unique phase formation rules and excellent physical properties. This work used the first-principle calculation method to study the effect of Cr content on the phase formation, stability, and mechanical properties of MoNbTiV refractory HEAs (RHEAs). The structural model of CrxMoNbTiV (x = 0.00, 0.25, 0.50, ..., 2.00) RHEAs was constructed by the virtual crystal approximation method. The structural model was geometrically optimized using the Cambridge Sequential Total Energy Package code, and the structures' binding energy, enthalpy of formation, and elastic constants were calculated. The results show that the CrxMoNbTiV RHEAs can form a stable body-centered cubic structure, and the addition of Cr significantly impacts the lattice constant, elastic constant, plastic toughness, and elastic anisotropy of the alloy. At the same time, the three-dimensional surface map of Young's modulus anisotropy is also drawn. [ABSTRACT FROM AUTHOR]

The effect of grain size and second-phase distribution on the corrosion performance of metal inert gas-welded Al–MgSi–Mn–Cr alloy in different regions was investigated. Due to the welding heat, the transformation of the strengthening phase β″ (Mg5Si6) to B′ phase (Al3Mg9Si7) in heat-affected zone I leads to the reduction in strengthening ability of the joint. In comparison with the equiaxed grain of weld zone, base metal exhibits high grain boundary density of the fibrous grain and a large amount of second phases on the grain boundary, which increases the anodic dissolution site, leading to the highest pitting corrosion susceptibility. Additionally, the continuous distribution of β (Mg2Si) precipitate and Al(MnFe)Si dispersoid at grain boundary forms a corrosion channel, which promotes the corrosion propagation along grain boundary. [ABSTRACT FROM AUTHOR]

In this study, a novel ultra-broadband absorber is suggested and numerically analyzed to demonstrate that the suggested absorber can achieve an average absorbance of 98.6% in the visible to near-infrared wavelength range (496–2100 nm). The structure of the proposed new ultra-wideband absorber consists of four thin films of silicon dioxide (SiO2), iron (Fe), magnesium fluoride (MgF2), and chromium (Cr). We have examined the structure's electromagnetic field intensity distribution at numerous selected optical wavelengths and the influence of various structural parameters on the absorption performance of the absorber to offer a physical mechanism underlying the ultra-broadband absorption effect. Furthermore, in the presence of high-performance absorption, the structure has the effect of stabilizing absorption at large angles of incidence and is polarization-independent at vertical angles of incidence. The study also assesses the solar absorption capability of this structure, indicating that the structure has potential applications in solar absorption, such as solar energy collection and conversion, solar power generation, and thermal emitters. [ABSTRACT FROM AUTHOR]

This article studies multiple structural breaks in large contemporaneous covariance matrices of high-dimensional time series satisfying an approximate factor model. The breaks in the second-order moment structure of the common components are due to sudden changes in either factor loadings or covariance of latent factors, requiring appropriate transformation of the factor models to facilitate estimation of the (transformed) common factors and factor loadings via the classical principal component analysis. With the estimated factors and idiosyncratic errors, an easy-to-implement CUSUM-based detection technique is introduced to consistently estimate the location and number of breaks and correctly identify whether they originate in the common or idiosyncratic error components. The algorithms of Wild Binary Segmentation for Covariance (WBS-Cov) and Wild Sparsified Binary Segmentation for Covariance (WSBS-Cov) are used to estimate breaks in the common and idiosyncratic error components, respectively. Under some technical conditions, the asymptotic properties of the proposed methodology are derived with near-optimal rates (up to a logarithmic factor) achieved for the estimated breaks. Monte Carlo simulation studies are conducted to examine the finite-sample performance of the developed method and its comparison with other existing approaches. We finally apply our method to study the contemporaneous covariance structure of daily returns of S&P 500 constituents and identify a few breaks including those occurring during the 2007–2008 financial crisis and the recent coronavirus (COVID-19) outbreak. An R package " BSCOV " is provided to implement the proposed algorithms. [ABSTRACT FROM AUTHOR]

The Al1.5Co3.5Nd compound was prepared by means of experimental synthesis, after which the Rietveld refinement of the powder X-ray diffraction pattern (PXRD) was used to determine its crystal structure. The results show that Al1.5Co3.5Nd crystallizes in the hexagonal cell, space group of P6/mmm (No. 191) with the lattice parameters of a = 5.1041(7) Ǻ and c = 4.0576(3) Ǻ, Dcalc = 7.09 g/cm3, and Z = 1. It is isostructural with the Al2NdNi3 compound (CaCu5-type). The temperature-dependent magnetic susceptibility curve of Al1.5Co3.5Nd was obtained in the temperature range of 2–600 K, which indicates that the Curie temperature (Tc) and paramagnetic Curie temperature (Tp) are 516 K and 522 K, respectively. The effective magnetic moment μeff is estimated to be 0.53 μB. Under the applied magnetic field of up to 8 T, the saturation magnetic moment and magnetic hysteresis loop of Al1.5Co3.5Nd compound were measured at different temperatures in the temperature range of 2–300 K. The results show that the saturation magnetic moment MS is 0.082 µB/f.u., the remnant magnetization Mr is 0.035µB/f.u., the coercivity Hc is 1.59 T at 2 K, and the compound is a magnetic material within the temperature range of measurement. [ABSTRACT FROM AUTHOR]

A ternary compound Al3CoNd2 was synthesized and its crystal structure parameters were determined by the Rietveld refinement method based on powder X-ray diffraction data. Results show that the compound crystallizes in the MgCu2-type structure (cubic Laves C15 phase, space group $Fd\bar{3}m$), with the lattice parameter of a = 7.8424(2) Ǻ, unit-cell volume of V = 482.33 Å3, and calculated density of Dcalc = 5.90 g.cm−3. The residual factors converge to Rp = 0.1024 and Rwp = 0.1287. The reference intensity ratio value obtained experimentally is 3.03. Magnetic susceptibility measurements indicate an agreement with the Curie–Weiss law in the temperature range of 385–450 K, and paramagnetic Curie temperature of θp = 379.9 K. Both rare-earth elements and cobalt ions contribute to the paramagnetic moment. The saturation magnetic moment and magnetic hysteresis loop were measured for the Al3CoNd2 compound at various temperatures. Results show that the saturation magnetic moment value decreases with an increase in temperature and the compound becomes a ferromagnet below the Curie temperature Tc. [ABSTRACT FROM AUTHOR]

This paper explores the homogeneity of coefficient functions in nonlinear models with functional coefficients and identifies the underlying semiparametric modelling structure. With initial kernel estimates, we combine the classic hierarchical clustering method with a generalised version of the information criterion to estimate the number of clusters, each of which has a common functional coefficient, and determine the membership of each cluster. To identify a possible semi-varying coefficient modelling framework, we further introduce a penalised local least squares method to determine zero coefficients, non-zero constant coefficients and functional coefficients which vary with an index variable. Through the nonparametric kernel-based cluster analysis and the penalised approach, we can substantially reduce the number of unknown parametric and nonparametric components in the models, thereby achieving the aim of dimension reduction. Under some regularity conditions, we establish the asymptotic properties for the proposed methods including the consistency of the homogeneity pursuit. Numerical studies, including Monte-Carlo experiments and two empirical applications, are given to demonstrate the finite-sample performance of our methods. [ABSTRACT FROM AUTHOR]

This article studies stationary functional time series with long‐range dependence, and estimates the memory parameter involved. Semiparametric local Whittle estimation is used, where periodogram is constructed from the approximate first score, which is an inner product of the functional observation and estimated leading eigenfunction. The latter is obtained via classical functional principal component analysis. Under the restrictive condition of constancy of the memory parameter over the function support, and other conditions which include rather unprimitive ones on the first score, the estimate is shown to be consistent and asymptotically normal with asymptotic variance free of any unknown parameter, facilitating inference, as in the scalar time series case. Although the primary interest lies in long‐range dependence, our methods and theory are relevant to short‐range dependent or negative dependent functional time series. A Monte Carlo study of finite sample performance and an empirical example are included. [ABSTRACT FROM AUTHOR]

The Al3FeNd2 single-phase alloy was prepared by melting stoichiometric Al, Fe, and Nd in a nonconsumable arc furnace filled with argon and then homogenizing annealing at a high temperature. The crystal structure of Al3FeNd2 was analyzed by an X-ray powder diffraction technique, Rietveld refinement analysis, and the first-principles simulation calculation method. The results show that the alloy crystallizes in the cubic cell, space group of Fd-3m (no. 227), and the lattice parameters of a = 7.8892 (1) Å, Z = 4, and Dcalc = 5.75 g/cm3. Al3FeNd2 exhibits ferrimagnetic properties at low temperatures and has a Curie temperature (Tc) of 353 K, and its saturation magnetic moment (Ms) is 3.33 μB/f.u. at 2 K. The simulation results also show that Al3FeNd2 is a ferrimagnet with a spontaneous magnetic moment of 4.11 μB/f.u., and it is believed that the spontaneous magnetization of this alloy originates from the electron spin in the Fe(16c)-3d band and Nd(8b)-4f. [ABSTRACT FROM AUTHOR]

In this article, we investigate the problem of nonparametrically estimating a conditional quantile function with mixed discrete and continuous covariates. A local linear smoothing technique combining both continuous and discrete kernel functions is introduced to estimate the conditional quantile function. We propose using a fully data-driven cross-validation approach to choose the bandwidths, and further derive the asymptotic optimality theory. In addition, we also establish the asymptotic distribution and uniform consistency (with convergence rates) for the local linear conditional quantile estimators with the data-dependent optimal bandwidths. Simulations show that the proposed approach compares well with some existing methods. Finally, an empirical application with the data taken from the IMDb website is presented to analyze the relationship between box office revenues and online rating scores. for this article are available online. [ABSTRACT FROM AUTHOR]

A new ternary compound, Al2Fe3Nd, was prepared via arc melting using a non-consumable tungsten electrode under an argon atmosphere with subsequent annealing at 923 K for 30 days. Its crystal structure was determined using the Rietveld refinement of powder X-ray diffraction data. The results show that Al2Fe3Nd has a hexagonal structure in a space group of P6/mmm (No. 191). It is isostructural with the Al2.5Ni2.5Y compound. It has lattice parameters of a = 8.8625(3) Ǻ and c = 4.1475(2) Ǻ with a calculated density Dcalc = 6.460 g/cm3. The residual factors converge to Rp = 0.0946 and Rwp = 0.1214. In the temperature range of 2–500 K, magnetic susceptibility has been measured. The magnetic susceptibility of Al2Fe3Nd follows the Curie–Weiss law in the temperature range of 410–500 K. The effective magnetic moment μeff and paramagnetic Curie temperature θP were estimated to be 8.59 μB and 399.8 K, respectively. The saturation magnetic moment and magnetic hysteresis loop for the compound were measured under room- and low-temperature conditions. The measurements indicate that the saturation magnetization moment declines with increasing temperature, and the compound is ferrimagnetic in the analytical temperature range of 2–300 K. [ABSTRACT FROM AUTHOR]

We introduce methods and theory for functional or curve time series with long-range dependence. The temporal sum of the curve process is shown to be asymptotically normally distributed, the conditions for this covering a functional version of fractionally integrated autoregressive moving averages. We also construct an estimate of the long-run covariance function, which we use, via functional principal component analysis, in estimating the orthonormal functions spanning the dominant subspace of the curves. In a semiparametric context, we propose an estimate of the memory parameter and establish its consistency. A Monte Carlo study of finite-sample performance is included, along with two empirical applications. The first of these finds a degree of stability and persistence in intraday stock returns. The second finds similarity in the extent of long memory in incremental age-specific fertility rates across some developed nations. for this article are available online. [ABSTRACT FROM AUTHOR]

Ligand exchange was triggered at toluene/water emulsion interface between homogeneous gold nanoparticles (Au NPs) with triphenylphosphine (PPh3) and D-penicillamine (D-PA), resulted in amphiphilic Janus Au NPs with both phosphine and thiolate ligands. TEM and XRD analyses indicate that the product is composed of Au nanocrystals in an average diameter of about 3.7 nm. XPS, FTIR, Raman, and 1H NMR analyses demonstrate that the Au NPs are protected with hydrophilic D-PA molecules and lipophilic PPh3 ligands in a molecular ratio of ca. 1.8. The NOESY analysis and contact angle measurement further suggest that the D-PA and PPh3 molecules are spontaneously separated to form compartmentalized hydrophilic and lipophilic regions on the individual Au NPs, which exhibit good catalytic performance and recyclability on the reduction of 4-nitrophenol. The results demonstrate that amphiphilic Janus Au NPs can be synthesized by partly exchange of PPh3 with D-PA at toluene/water emulsion interface and are potentially applicable for other phosphine/thiolate pairs to modify Au NPs. [ABSTRACT FROM AUTHOR]

This article introduces a new class of functional‐coefficient predictive regression models, where the regressors consist of auto‐regressors and latent factor regressors, and the coefficients vary with certain index variable. The unobservable factor regressors are estimated through imposing an approximate factor model on high dimensional exogenous variables and subsequently implementing the classical principal component analysis. With the estimated factor regressors, a local linear smoothing method is used to estimate the coefficient functions (with appropriate rotation) and obtain a one‐step ahead nonlinear forecast of the response variable, and then a wild bootstrap procedure is introduced to construct the prediction interval. Under regularity conditions, the asymptotic properties of the proposed methods are derived, showing that the local linear estimator and the nonlinear forecast using the estimated factor regressors are asymptotically equivalent to those using the true latent factor regressors. The developed model and methodology are further generalized to the factor‐augmented vector predictive regression with functional coefficients. Finally, some extensive simulation studies and an empirical application to forecast the UK inflation are given to examine the finite‐sample performance of the proposed model and methodology. [ABSTRACT FROM AUTHOR]

A straightforward approach is employed to synthesize silver nanoparticle/multiwalled carbon nanotube (Ag/MWNTs) hybrids through the direct reduction of silver nitrate in the presence of MWNTs, where Ag nanoparticles capped with tris(hydroxymethyl)phosphine oxide (d=2.9 nm) are uniformly deposited on MWNTs. The as‐synthesized Ag/MWNTs hybrids exhibit high catalytic activity toward the oxygen reduction, which increases with the loading amount of Ag nanoparticles. Rotating disk electrode and rotating ring‐disk electrode analyses further indicate that the Ag/MWNTs hybrids follow the same four‐electron pathway towards the oxygen reduction reaction as the Pt/C catalyst, and the Ag/MWNTs hybrid (22.8 wt.%) manifests comparable catalytic activity to the 20 % Pt/C catalyst, together with superior long‐term stability and methanol tolerance, demonstrating the potential application on direct methanol fuel cells as an effective oxygen reduction catalyst. [ABSTRACT FROM AUTHOR]

A new ternary compound Al5NdNi2 was prepared by melting a stoichiometric mixture of aluminum, neodymium, and nickel in an arc furnace and annealing in vacuum. The crystal structure of Al5NdNi2 was studied by X-ray powder diffraction technique and Rietveld analysis. All diffraction lines of Al5NdNi2 were indexed, and the lattice parameters were refined with an orthorhombic structure type of space group Immm (No.71) using Rietveld analysis program DBWS-9807. The lattice parameters are presented, a = 7.0508(1) Å, b = 9.5690(1) Å, c = 3.9792(1) Å, V = 268.47 Å3, Z = 2, ρ = 4.91 g cm−3, and RIR = 1.23. [ABSTRACT FROM AUTHOR]

We propose two semiparametric model averaging schemes for nonlinear dynamic time series regression models with a very large number of covariates including exogenous regressors and auto-regressive lags. Our objective is to obtain more accurate estimates and forecasts of time series by using a large number of conditioning variables in a nonparametric way. In the first scheme, we introduce a kernel sure independence screening (KSIS) technique to screen out the regressors whose marginal regression (or autoregression) functions do not make a significant contribution to estimating the joint multivariate regression function; we then propose a semiparametric penalized method of model averaging marginal regression (MAMAR) for the regressors and auto-regressors that survive the screening procedure, to further select the regressors that have significant effects on estimating the multivariate regression function and predicting the future values of the response variable. In the second scheme, we impose an approximate factor modeling structure on the ultra-high dimensional exogenous regressors and use the principal component analysis to estimate the latent common factors; we then apply the penalized MAMAR method to select the estimated common factors and the lags of the response variable that are significant. In each of the two schemes, we construct the optimal combination of the significant marginal regression and autoregression functions. Asymptotic properties for these two schemes are derived under some regularity conditions. Numerical studies including both simulation and an empirical application to forecasting inflation are given to illustrate the proposed methodology. Supplementary materials for this article are available online. [ABSTRACT FROM AUTHOR]

This article introduces a new specification for the heterogenous autoregressive (HAR) model for the realized volatility of S&P 500 index returns. In this modeling framework, the coefficients of the HAR are allowed to be time-varying with unspecified functional forms. The local linear method with the cross-validation (CV) bandwidth selection is applied to estimate the time-varying coefficient HAR (TVC-HAR) model, and a bootstrap method is used to construct the point-wise confidence bands for the coefficient functions. Furthermore, the asymptotic distribution of the proposed local linear estimators of the TVC-HAR model is established under some mild conditions. The results of the simulation study show that the local linear estimator with CV bandwidth selection has favorable finite sample properties. The outcomes of the conditional predictive ability test indicate that the proposed nonparametric TVC-HAR model outperforms the parametric HAR and its extension to HAR with jumps and/or GARCH in terms of multi-step out-of-sample forecasting, in particular in the post-2003 crisis and 2007 global financial crisis (GFC) periods, during which financial market volatilities were unduly high. [ABSTRACT FROM PUBLISHER]

We study a semivarying coefficient model where the regressors are generated by the multivariate unit root I(1) processes. The influence of the explanatory vectors on the response variable satisfies the semiparametric partially linear structure with the nonlinear component being functional coefficients. A semiparametric estimation methodology with the first-stage local polynomial smoothing is applied to estimate both the constant coefficients in the linear component and the functional coefficients in the nonlinear component. The asymptotic distribution theory for the proposed semiparametric estimators is established under some mild conditions, from which both the parametric and nonparametric estimators are shown to enjoy the well-known super-consistency property. Furthermore, a simulation study is conducted to investigate the finite sample performance of the developed methodology and results. [ABSTRACT FROM AUTHOR]

In this article, we consider estimation of common structural breaks in panel data models with unobservable interactive fixed effects. We introduce a penalized principal component (PPC) estimation procedure with an adaptive group fused LASSO to detect the multiple structural breaks in the models. Under some mild conditions, we show that with probability approaching one the proposed method can correctly determine the unknown number of breaks and consistently estimate the common break dates. Furthermore, we estimate the regression coefficients through the post-LASSO method and establish the asymptotic distribution theory for the resulting estimators. The developed methodology and theory are applicable to the case of dynamic panel data models. Simulation results demonstrate that the proposed method works well in finite samples with low false detection probability when there is no structural break and high probability of correctly estimating the break numbers when the structural breaks exist. We finally apply our method to study the environmental Kuznets curve for 74 countries over 40 years and detect two breaks in the data. Supplementary materials for this article are available online. [ABSTRACT FROM AUTHOR]

We obtain uniform consistency results for kernel-weighted sample covariances in a nonstationary multiple regression framework that allows for both fixed design and random design coefficient variation. In the fixed design case these nonparametric sample covariances have different uniform asymptotic rates depending on direction, a result that differs fundamentally from the random design and stationary cases. The uniform asymptotic rates derived exceed the corresponding rates in the stationary case and confirm the existence of uniform super-consistency. The modelling framework and convergence rates allow for endogeneity and thus broaden the practical econometric import of these results. As a specific application, we establish uniform consistency of nonparametric kernel estimators of the coefficient functions in nonlinear cointegration models with time varying coefficients or functional coefficients, and provide sharp convergence rates. For the fixed design models, in particular, there are two uniform convergence rates that apply in two different directions, both rates exceeding the usual rate in the stationary case. [ABSTRACT FROM AUTHOR]

This paper establishes uniform consistency results for nonparametric kernel density and regression estimators when time series regressors concerned are nonstationary null recurrent Markov chains. Under suitable regularity conditions, we derive uniform convergence rates of the estimators. Our results can be viewed as a nonstationary extension of some well-known uniform consistency results for stationary time series. [ABSTRACT FROM PUBLISHER]

In this paper, we consider a specification testing problem in nonlinear time series models with nonstationary regressors, and we propose using a nonparametric kernel-based test statistic. The null asymptotics for the proposed nonparametric test statistic have been well developed in the existing literature. In this paper, we study the local asymptotics of the test statistic (i.e. the asymptotic properties of the test statistic under a sequence of general nonparametric local alternatives) and show that the asymptotic distribution depends on the asymptotic behaviour of the distance function, which is the local deviation from the parametrically specified model in the null hypothesis. In order to implement the proposed test in practice, we introduce a bootstrap procedure to approximate the critical values of the test statistic and establish a new Edgeworth expansion, which is used to justify the use of such an approximation. Based on the approximate critical values, we develop a bandwidth selection method, which chooses the optimal bandwidth that maximizes the local power of the test while its size is controlled at a given significance level. The local power is defined as the power of the proposed test for a given sequence of local alternatives. Such a bandwidth selection is made feasible by an approximate expression for the local power of the test as a function of the bandwidth. A Monte Carlo simulation study is provided to illustrate the finite sample performance of the proposed test. [ABSTRACT FROM AUTHOR]

The new ternary compound of Al2Cu3Gd was prepared by melting with stoichiometric composition in an electric arc furnace. The X-ray powder diffraction data of Al2Cu3Gd have been collected by the Rigaku Smart Lab X-ray powder diffractometer. The Rietveld refinement method had been used to study the crystal structure of Al2Cu3Gd. The results showed that the Al2Cu3Gd, new compound have the hexagonal structure, space group P6/mmm (No. 191) with a = 5.1822 (1) Å, c = 4.1566 (1) Å, V = 96.67 Å3, Z = 1, and the density is 6.62 g cm−3, and the intensity ratio reference intensity ratio is 1.29. [ABSTRACT FROM PUBLISHER]

For discrete data, frequentist confidence limits based on a normal approximation to standard likelihood based pivotal quantities can perform poorly, even for quite large sample sizes. To construct exact limits requires the probability of a suitable tail set as a function of the unknown parameters. In this paper, importance sampling is used to estimate this surface and hence the confidence limits. The technology is simple and straightforward to implement. Unlike the recent methodology of Garthwaite and Jones (in J. Comput. Graph. Stat. 18, 184-200, ), the new method allows for nuisance parameters; is an order of magnitude more efficient than the Robbins-Monro bound; does not require any simulation phases or tuning constants; gives a straightforward simulation standard error for the target limit; includes a simple diagnostic for simulation breakdown. [ABSTRACT FROM AUTHOR]

A new ternary compound Ho2AlGe3 was synthesized and studied by means of X-ray powder diffraction technique. The powder pattern of Ho2AlGe3 was indexed and refined, giving an orthorhombic structure, space group Pnma (No. 62) with the Y2AlGe3 structure type: a = 6.743 98(8) Å, b = 4.163 73(5) Å, c = 17.5834(2) Å, V = 493.74 Å3, Z = 4, ρx = 7.73 g cm−3, F30 = 202.7 (0.004, 37), and RIR = 1.21. [ABSTRACT FROM PUBLISHER]

In this article, we study semiparametric estimation for a single-index panel data model where the nonlinear link function varies among the individuals. We propose using the refined minimum average variance estimation method to estimate the parameter in the single-index. As the cross-section dimensionNand the time series dimensionTtend to infinity simultaneously, we establish asymptotic distributions for the proposed estimator. In addition, we provide a real-data example to illustrate the finite sample behavior of the proposed estimation method. [ABSTRACT FROM AUTHOR]

In this article, we consider semiparametric estimation in a partially linear single-index panel data model with fixed effects. Without taking the difference explicitly, we propose using a semiparametric minimum average variance estimation (SMAVE) based on a dummy variable method to remove the fixed effects and obtain consistent estimators for both the parameters and the unknown link function. As both the cross-section size and the time series length tend to infinity, we not only establish an asymptotically normal distribution for the estimators of the parameters in the single index and the linear component of the model, but also obtain an asymptotically normal distribution for the nonparametric local linear estimator of the unknown link function. The asymptotically normal distributions of the proposed estimators are similar to those obtained in the random effects case. In addition, we study several partially linear single-index dynamic panel data models. The methods and results are augmented by simulation studies and illustrated by application to two real data examples. This article has online supplementary materials. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new diagnostic test for residual cross-section uncorrelatedness (CU) in a nonparametric panel data model. The proposed nonparametric CU test is a nonparametric counterpart of an existing parametric cross-section dependence test proposed in Pesaran (2004, Cambridge Working paper in Economics 0435). Without assuming cross-section independence, we establish asymptotic distribution for the proposed test statistic for the case where both the cross-section dimension and the time dimension go to infinity simultaneously, and then analyze the power function of the proposed test under a sequence of local alternatives that involve a nonlinear multifactor model. The simulation results and real data analysis show that the nonparametric CU test associated with an asymptotic critical value works well. [ABSTRACT FROM PUBLISHER]

Local linear fitting is a popular nonparametric method in statistical and econometric modeling. Lu and Linton (2007, Econometric Theory23, 37–70) established the pointwise asymptotic distribution for the local linear estimator of a nonparametric regression function under the condition of near epoch dependence. In this paper, we further investigate the uniform consistency of this estimator. The uniform strong and weak consistencies with convergence rates for the local linear fitting are established under mild conditions. Furthermore, general results regarding uniform convergence rates for nonparametric kernel-based estimators are provided. The results of this paper will be of wide potential interest in time series semiparametric modeling. [ABSTRACT FROM PUBLISHER]

Summary This paper is concerned with developing a non-parametric time-varying coefficient model with fixed effects to characterize non-stationarity and trending phenomenon in a non-linear panel data model. We develop two methods to estimate the trend function and the coefficient function without taking the first difference to eliminate the fixed effects. The first one eliminates the fixed effects by taking cross-sectional averages, and then uses a non-parametric local linear method to estimate both the trend and coefficient functions. The asymptotic theory for this approach reveals that although the estimates of both the trend function and the coefficient function are consistent, the estimate of the coefficient function has a rate of convergence of ( Th)−1/2, which is slower than ( NTh)−1/2 as the rate of convergence for the estimate of the trend function. To estimate the coefficient function more efficiently, we propose a pooled local linear dummy variable approach. This is motivated by a least squares dummy variable method proposed in parametric panel data analysis. This method removes the fixed effects by deducting a smoothed version of cross-time average from each individual. It estimates both the trend and coefficient functions with a rate of convergence of ( NTh)−1/2. The asymptotic distributions of both of the estimates are established when T tends to infinity and N is fixed or both T and N tend to infinity. Both the simulation results and real data analysis are provided to illustrate the finite sample behaviour of the proposed estimation methods. [ABSTRACT FROM AUTHOR]

A robust version of local linear regression smoothers augmented with variable bandwidths is investigated for dependent spatial processes. The (uniform) weak consistency as well as asymptotic normality for the local linear M-estimator (LLME) of the spatial regression function g( x) are established under some mild conditions. Furthermore, an additive model is considered to avoid the curse of dimensionality for spatial processes and an estimation procedure based on combining the marginal integration technique with LLME is applied in this paper. Meanwhile, we present a simulated study to illustrate the proposed estimation method. Our simulation results show that the estimation method works well numerically. [ABSTRACT FROM AUTHOR]

The ternary compound of AlCu4Y was synthesized by melting under argon atmosphere in the arc furnace. High-quality X-ray powder diffraction data of AlCu4Y have been collected using a Rigaku SmartLab X-ray powder diffractometer. The Rietveld refinement results of the X-ray diffraction pattern for the AlCu4Y compound showed that the AlCu4Y is the hexagonal structure, space-group P6/mmm (No. 191) with a = 5.0658(1) Å, c = 4.1569(1) Å, V = 92.38 Å3, Z = 1, and the density is 6.66 g cm−3, and the intensity ratio RIR is 1.96. [ABSTRACT FROM AUTHOR]

Abstract  We investigate the asymptotic behavior of a robust version of local linear regression estimators with variable bandwidth for spatial associated processes. The weak consistency of the proposed estimators is given under appropriate conditions. Furthermore, we establish the asymptotic normality of the estimators, from which expressions for the asymptotic bias and variance can be derived. [ABSTRACT FROM AUTHOR]

Abstract  The asymptotic behavior of S-estimators in a random design linear model with long-range-dependent Gaussian errors is considered. It turns out that the S-estimators of regression parameter and error variance are strongly consistent under mild conditions. Furthermore, the asymptotic distribution of the S-estimator of regression parameter is normal if the design vectors are i.i.d. and is non-normal if the design vectors are long-range dependent Gaussian vectors. We also show that the asymptotic distribution of S-estimator of the error variance is non-normal since the errors are long-range dependent. [ABSTRACT FROM AUTHOR]

A new quaternary compound PrAlFeNi3 was synthesized and studied by means of X-ray powder diffraction technique. The powder pattern of PrAlFeNi3 was indexed and refined, giving a hexagonal structure, space group P6/mmm (No. 191) with the CaCu5 structure type, a = 5.1132(2) Å, c = 4.0737(1) Å, V = 92.19 Å3, Z = 1, ρx = 7.20 g cm−3, F30 = 173.61 (0.0054, 32) and RIR = 0.77. [ABSTRACT FROM AUTHOR]

A new quaternary compound AlCeCo2Ni2 was synthesized and studied by means of X-ray powder diffraction technique. The powder pattern of AlCeCo2Ni2 was indexed and refined, giving a hexagonal structure, space group P6/mmm (No. 191) with the CaCu5 structure type. a = 4.9242(2) Å, c = 4.0524(1) Å, V = 85.1 Å3, Z = 1, ρx = 7.85 g cm−3, F30 = 130.2(0.010, 30), and RIR = 0.71(2). [ABSTRACT FROM AUTHOR]

The CeCo3Ni2 compound was synthesized by arc melting under argon atmosphere. High-quality powder X-ray diffraction (XRD) data of CeCo3Ni2 have been collected using a Rigaku SmartLab X-ray powder diffractometer. The refinement of the XRD pattern for the CeCo3Ni2 compound shows that the CeCo3Ni2 is a hexagonal structure, space group P6/mmm (No.191) with a = b = 4.9081(2) Å, c = 4.0034(2) Å, V = 83.52 Å3, Z = 1, and ρx = 8.6347 g cm−3. The Smith–Snyder FOM F30 = 112.7(0.0089, 30) and the intensity ratio RIR = 0.48. [ABSTRACT FROM PUBLISHER]