Recombination luminescence in alkali metal sulfates

In this paper we present the results of investigation of the nature of intrinsic luminescence caused by photon excitation in a wide spectral range from 10.3 eV to 4 eV at a temperature of 15–300 K. It is shown that in alkali metal sulfates the main emission band formed after excitation by X-rays and photons with an energy of 9–11 eV and 4–7.5 eV at 15–300 K is located in the spectral range of 3.65–3.9 eV. When the sulfates are excited by 4–7.75 eV photons, in addition to the emission band at 3.65–3.9 eV the other effective long-wave band at 3.1–2.5 eV appears. It is assumed that the 3.65–3.9 eV radiation results from the recombination of electrons with unevenly located holes of SO₄⁻ type. The long-wave emission bands in the alkali metal sulfates may be connected with the formation of electron-hole trapping centers after irradiation by photons with energies above 4.4 eV.     

Detecting outlier pairs in complex network based on link structure and semantic relationship

In this paper, we propose an outlier pair detection method, called LSOutPair, which discovers the vast differences between link structure and semantic relationship. LSOutPair addresses three important challenges: (1) how can we measure the target object's link similarity among multi-typed objects and multi-typed relations? (2) how can we measure the semantic similarity using the short texts? (3) how can we find the objects’ maximum differences between link structure and semantic relationship? To tackle these challenges, LSOutPair applies three main techniques: (1) two matrices are used to store link similarity and semantic similarity, (2) a k-step index algorithm, which calculates the term weighting for each object, (3) applying the linear transformation of Frobenius norm to matrices can obtain the top-K outlier pairs. LSOutPair considers link and semantics in complex network simultaneously, which is a new attempt in data mining. Substantial experiments show that LSOutPair is very effective for outlier pair detection.     

Effect of surface modification with 3-aminopropyltriethyloxy silane on mechanical and crystallization performances of ZnO/poly(butylenesuccinate) composites

The surface modifications of tetrapod-shaped ZnO whisker (T-ZnO) and nano-ZnO (N-ZnO) were treated with 3-aminopropyltriethyloxy silane (APS), which were further utilized to reinforce poly(butylene succinate) (PBS) by melt extrusion. This work explored the interface compatibilities between the PBS matrix and the two types of ZnO fillers (T-ZnO and N-ZnO), and discussed the effect of the ZnO fillers on the mechanical and the crystallization performances of the ZnO/PBS composites. FT-IR and XPS analyses confirm the existence of APS on the surfaces of the modified ZnO fillers. The SEM images suggest that the surface modifications of two ZnO fillers by APS can enhance the interface adhesion between the ZnO fillers and the PBS matrix. The mechanical properties of the composites increase to different degree, and the dispersity of N-ZnO in PBS matrix is improved, thus N-ZnO has better reinforcing effect on the PBS matrix. However, T-ZnO does not show the reinforcing effect as expected. The crystallization kinetics of the ZnO/PBS composites shows that N-ZnO with better nucleation than that of T-ZnO and the surface modifications of T-ZnO and N-ZnO by APS can accelerate the crystallization rates of the two types of ZnO/PBS composites.     

An arrayed uniform eddy current probe design for crack monitoring and sizing of surface breaking cracks with the aid of a computational inversion technique

This study demonstrates that eddy current testing can be an effective method for monitoring the growth of surface breaking cracks with the aid of computational inversion techniques. A uniform eddy current probe with 23 arrayed detectors was designed, and pseudo monitoring tests were carried out to measure signals due to six mechanical fatigue cracks introduced into type 316L austenitic stainless steel plates. In the test the position of the probe was fixed to simulate monitoring. The depths of the cracks were evaluated using a computational inversion method developed on the basis of k-nearest neighbor algorithm. The depths of the mechanical fatigue cracks whose actual depths were 1.1, 2.1, 3.1, 5.5, 6.7, and 8.5 mm were evaluated to be 0.9, 1.9, 3.8, 4.3, 7.0, and 5.7 mm, respectively. Additional simulations were conducted to demonstrate the stability of the method.     

Effect of N and C on stress corrosion cracking susceptibility of austenitic Fe18Cr10Mn-based stainless steels

Stress corrosion cracking (SCC) susceptibility of austenitic Fe18Cr10Mn alloys with 0.3N, 0.6N and 0.3N0.3C was investigated in aqueous chloride environment using a slow strain rate test method. The SCC susceptibility of Fe18Cr10Mn alloys in 2 M NaCl solution at 50 °C under constant anodic potential condition decreased with increase in N content from 0.3 to 0.6 wt%, and with addition of 0.3 wt% C to the Fe18Cr10Mn0.3N alloys. The present study strongly suggested that the beneficial effects of N and C on the SCC behavior of Fe18Cr10Mn alloys would be associated with the resistance to pitting corrosion initiation and the repassivation kinetics.     

Free carrier absorption in self-activated PbWO4 and Ce-doped Y3(Al0.25Ga0.75)3O12 and Gd3Al2Ga3O12 garnet scintillators

Nonequilibrium carrier dynamics in the scintillators prospective for fast timing in high energy physics and medical imaging applications was studied. The time-resolved free carrier absorption investigation was carried out to study the dynamics of nonequilibrium carriers in wide-band-gap scintillation materials: self-activated led tungstate (PbWO₄, PWO) ant two garnet crystals, GAGG:Ce and YAGG:Ce. It was shown that free electrons appear in the conduction band of PWO and YAGG:Ce crystals within a sub-picosecond time scale, while the free holes in GAGG:Ce appear due to delocalization from Gd³⁺ ground states to the valence band within a few picoseconds after short-pulse excitation. The influence of Gd ions on the nonequilibrium carrier dynamics is discussed on the base of comparison the results of the free carrier absorption in GAGG:Ce containing gadolinium and in YAGG without Gd in the host lattice.     

Two-level defect-correction Oseen iterative stabilized finite element method for the stationary conduction–convection equations

In this paper, a two-level defect-correction Oseen iterative finite element method is presented for the stationary conduction–convection equations based on local Gauss integration. The method combines the defect-correction method, the two-level strategy, and the locally stabilized method. The stability and convergence of the proposed method are deduced. Finally, numerical examples verify the theoretical results of the proposed algorithm and show that it is highly efficient and reliable for the considered problem.     

Data classification with binary response through the Boosting algorithm and logistic regression

The task of classifying is natural to humans, but there are situations in which a person is not best suited to perform this function, which creates the need for automatic methods of classification. Traditional methods, such as logistic regression, are commonly used in this type of situation, but they lack robustness and accuracy. These methods do not not work very well when the data or when there is noise in the data, situations that are common in expert and intelligent systems. Due to the importance and the increasing complexity of problems of this type, there is a need for methods that provide greater accuracy and interpretability of the results. Among these methods, is Boosting, which operates sequentially by applying a classification algorithm to reweighted versions of the training data set. It was recently shown that Boosting may also be viewed as a method for functional estimation. The purpose of the present study was to compare the logistic regressions estimated by the maximum likelihood model (LRMML) and the logistic regression model estimated using the Boosting algorithm, specifically the Binomial Boosting algorithm (LRMBB), and to select the model with the better fit and discrimination capacity in the situation of presence(absence) of a given property (in this case, binary classification). To illustrate this situation, the example used was to classify the presence (absence) of coronary heart disease (CHD) as a function of various biological variables collected from patients. It is shown in the simulations results based on the strength of the indications that the LRMBB model is more appropriate than the LRMML model for the adjustment of data sets with several covariables and noisy data. The following sections report lower values of the information criteria AIC and BIC for the LRMBB model and that the Hosmer–Lemeshow test exhibits no evidence of a bad fit for the LRMBB model. The LRMBB model also presented a higher AUC, sensitivity, specificity and accuracy and lower values of false positives rates and false negatives rates, making it a model with better discrimination power compared to the LRMML model. Based on these results, the logistic model adjusted via the Binomial Boosting algorithm (LRMBB model) is better suited to describe the problem of binary response, because it provides more accurate information regarding the problem considered.